Released today, the latest version of the web-based Leica CrossCheck service for GNSS reference station network integrity and deformation monitoring now comes with enhanced visualization and reporting options. Customizable, automatically generated reports can be distributed to multiple viewers, according to Leica Geosystems. Dashboard and status views allow easy and fast interpretation of complex data of reference network coordinates and area deformation, the company said.
Highly trained experts at Leica Geosystems process monitoring data using the latest geodetic software and algorithms to provide highly accurate assessments of any site movement on various types of infrastructure platforms such as oil platforms, bridges or dams. Customizable reports can then be distributed via email or downloaded on demand.
Leica CrossCheck is a secure web-based application that provides interactive and flexible, round the clock access to project data. Intuitive and easy-to-use tools simplify project site movement analysis, speed up decision making when there is a need to react to changes.
In late June, I had the honor and privilege of attending and participating in the Institute of Navigation’s Joint Navigation Conference (ION-JNC) in Orlando, Fla. This year attendance was up by 20 percent. The entire event was FOUO (For Official Use Only) with a classified (SECRET) day on Thursday held at, as improbable as it seems, a joint military and Walt Disney location known as Shades of Green. It gives Mickey Mouse and the military a whole new meaning!
The classified day included a remarkable War Fighter Panel, which, full disclosure, I have had the honor along with my colleague Jim Doherty at IDA (Institute For Defense Analyses) of co-chairing for the last several years. It is always heart-warming and invariably enlightening to hear our warfighters discuss capabilities that GPS enables for them in times of peace and war. You could even say this was the theme of the conference: “The capabilities that GPS technology enables.”
You might assume an FOUO- and SECRET-level conference would be slim pickings for a journalist. If that is all that transpired, then you would be correct; however, all the conversations outside the official sessions, especially around the displays and exhibitors’ booths, make it more than worthwhile. Not to mention all the tidbits you pick up at breakfast, lunch, dinner and evening socials. One of the most common phrases I heard all week was, “Now don’t quote me on this, but…” or the one I like to hear, “OK, this is on the record” or “You are recording this, right?” Everyone has a message!
ION-JNC in Dayton, Ohio
For the next two years (2016-17) ION-JNC will be held in beautiful downtown Dayton, Ohio, at the Dayton Convention Center. Dayton is home to the famous Wright Brothers Cycle Shop and the Wright Flyer.
Take-off of the 1903 Wright Flyer, the world’s first powered, sustained and controlled heavier-than-air flight on Dec. 17, 1903.
Dayton also hosts the world-famous National Museum of the USAF (United States Air Force) located on Wright-Patterson Air Force Base (WPAFB). The classified day will be held at the prestigious USAF Institute of Technology (AFIT), also on WPAFB, where many an Air Force officer has earned a master’s and or Ph.D. The papers and sessions should be outstanding in view of the venue and the presence of the Air Force Research Laboratory (AFRL) at WPAFB, which is known as the Air Force’s only organization wholly dedicated to leading the discovery, development and integration of warfighting technologies for air, space and cyberspace forces.
Register early and send your clearance if you have one; it just gets better every year.
SpaceX and Falcon 9
Elon Musk,CEO Space Exploration Technology Corp. (Photo Courtesy of Tesla Motors)
I arrived in Orlando on Sunday, June 21 (yes, I traveled on Father’s Day) because events start bright and early Monday morning, to hear about the Falcon 9 launch failure, the first for that family of launchers. Even though it occurred 130+ seconds into the launch segment, if the rocket fails to deliver the payload or supplies to orbit or their destination, it is generally referred to as a launch failure. Technicians and subject-matter experts will be debating for some time exactly what caused the failure, but there can be no doubt this is a big blow to the Space Exploration Technology Corporation — better known as SpaceX.
I have known Elon Musk and experienced his outsize ego casually for more than 20 years, and I am constantly amazed at his accomplishments and would never bet against him. I do not mean the ego remark in a negative way, because history proves that if Elon says he will accomplish the seemingly impossible, then he will do just that. Can you say Tesla Motors? Setbacks just make him and his team more determined.
“It is difficult to say what is impossible, for the dream of yesterday is the hope of today and the reality of tomorrow.” — Dr. Robert Goddard
Gwynne Shotwell, COO Space Exploration Technology Corp. (Photo Courtesy of SpaceX)
However, launch setbacks are played out on a national stage where lives may well be at stake. SpaceX President and COO (Chief Operating Officer) Gwynne Shotwell, the brains of the outfit, who is as alluring as she is brilliant, said following the launch failure, “I’m sure we will find the cause rapidly and resume normal launch operations within a year.”
Reportedly, SpaceX is already a bit tardy in scheduled launches with an enviable backlog totaling approximately $7B, many of which are government payloads. In the end, this merely highlights that the launch business is a tough nut to crack, and attention to detail is paramount. Every little detail must be scrutinized numerous times.
BAR
In the mid 1990s, Dr. John Darrah and I (then AFSPC Chief Scientist and Deputy respectively) under the auspices of Air Force Space Command and the Institute For Defense Analyses (IDA) formed a high-level group of subject matter experts (SMEs) to review why the U.S. government, in the matter of a few months, put several billion dollars worth of space hardware into saltwater instead of the vacuum of space. The group was labeled the BAR, or Broad Area Review, and its task was to euphemistically “bar” this type of abnormal launch activity from ever happening again. I can honestly say the BAR has been wildly successful.
There have been five separate BARs to date, and there has not been a military or national security space launch failure since the BAR’s inception. There have begen more than 120 successful launches by Lockheed Martin, Boeing and the combined organization known as ULA or United Launch Alliance. I am not at liberty to reveal the findings of the various BARs, but obviously attention to detail is key to any successful endeavor.
SpaceX vaulted from an upstart small company with a few employees to a certified government space launch contractor with more than $7 billion in contracts and 3,000+ personnel on the payroll in only 13 years. SpaceX previously successfully launched two cargo resupply missions to the space station. To date, it is the only predominantly commercial space company to accomplish that task.
Therefore, I am sanguine without a doubt (now I sound like Elon) that SpaceX will quickly discover the malfunction that caused the launch failure and correct it immediately. This is not to say that anyone at SpaceX has been intentionally careless, but the successful space launch business today is by necessity an OCD (obsessive compulsive disorder) culture of attention to detail where items are checked not once or twice but 20 times to make sure nothing has been overlooked or assumed. However, for SpaceX the critical task, for the success of the company and future astronauts’ lives, depends on SpaceX’s assurance there will be no more failures for any reason. The U.S. military has proven for the last 16 years — 16 years without a single national security space launch failure — that it is an achievable goal. Note: Currently SpaceX launches do not fall under the purview of the BAR, a situation easily rectified.
Assured Access to Space
General (USAF, Ret) Thomas S. Moorman Jr. (Photo Courtesy of the USAF)
Lest we forget, behind all the technological arguments and/or failures is the crux of the matter, which is nothing less than assured access to space and all that capability enables, which of course includes GPS. In 2006, General (USAF Retired) Thomas S. Moorman Jr., former AFSPC commander and VCSAF, wrote in the highly esteemed AFSPC publication High Frontier regarding a Senior Leader’s Perspective on Assured Access to Space. He stated clearly that
“Assured access [to space] is a requirement for critical national security, homeland security and civil missions, and is defined as a sufficiently robust, responsive and resilient capability to allow continued space operations, consistent with risk management and affordability.”
In referring to his now famous and eponymous study, he stated that,
“The study found that most people wanted to describe assured access in terms of reliability. As the study team progressed in our analysis, it became apparent that often what people were describing was the need for resiliency rather than reliability. Reliability describes the dependability of a specific booster while resiliency considers the collective ability of all available launch systems to meet national security need.
“While our recent launch record…is indeed impressive, we should not rest on our laurels. Assured access is not a destination, but rather a journey. As a nation, we need to continue to adequately fund space launch operations and develop the next-generation technologies that will increase responsiveness, improve reliability, and reduce costs. Through these actions, we can ensure the nation will have continuous, uninterrupted access to space for decades to come.”
In that light it is possible — even probable — that SpaceX will help us strive, reach and continue with that vaunted goal; contrarily, you may remember a few months ago SpaceX sued the U.S. government because the government was not moving quickly enough for Space X with certifications and validations for SpaceX launch vehicles. The U.S. government knows first hand how difficult the space launch business can be, and it wanted to ensure that not only was SpaceX ready but that their family of vehicles were reliable. The government’s caution has unfortunately been validated, as this was the second SpaceX launch failure, although the first and hopefully the last in the Falcon 9 family of vehicles. All is not lost, and the future actually looks bright for SpaceX if it will just put egos aside, listen to the launch subject matter experts and pay attention to every little detail.
Competition may well be viewed as a “good thing” in the space launch business. However, it is always trumped by assured access to space, which is a critical national security requirement. Competition and national security needs must be balanced with the emphasis on what is gained by assured access to the high ground of space. Elon Musk, Gwynne Shotwell and the SpaceX team may well be capable of showing the rest of us “how it is done,” but first they must demonstrate unerring dependability, reliability and resiliency. I wish SpaceX the best of luck and every success.
Nascent Leadership Paradigm — People on the Move
For some unfathomable reason, at least intellectually, all the USAF Leadership Schools, or at least the majority, are located in Montgomery, Ala. Now personally I happen to like Montgomery and its laid-back southern charm. It was also once the capitol of the Confederacy, which is apropos nothing except it seems to be a hot topic or trigger word these days. Be that as it may, Montgomery and Air University are not exactly Oxford, Cambridge or Eton, and yet the university in its many incarnations has produced outstanding military leaders in its 95-year history. And yet in my numerous tenures at this prestigious institution, it has been made clear by the staff that this is an institution with bipolar tendencies.
On the one hand, it is made clear to every officer and student that the national military establishment thrives on rules and regulations, and those wishing to abuse or ignore them can readily and rapidly be replaced. Some instructors I encountered (not all certainly, and probably not the cream of the crop) would have you believe that individualism has its place — just not in the U.S. military. Then, in the next class or session, you hear stories about visionaries such as Claire Chennault, Jimmy Doolittle and William “Billy” Mitchell, who never colored within the lines. Not to disparage Air University, but I have always had a problem with this school tenet, as it tends to disregard personality, relationships and leadership. I often think of General Dwight Eisenhower’s comments concerning his rebellious, unorthodox and rule-breaking friend U.S. Army General George Patton. Eisenhower made numerous famous comments about Patton’s rebellious nature, his inability to follow orders and his swashbuckling uniforms that once paraded 24 general’s stars at one time on one non-standard uniform, and yet in official comments written after Patton’s untimely death Eisenhower wrote:
“He [Patton] was one of those men born to be a soldier, an ideal combat leader whose gallantry and dramatic personality inspired all he commanded to great deeds of valor. His presence gave me the certainty that the boldest plan would be even more daringly executed. It is no exaggeration to say that Patton’s name struck terror at the heart of the enemy.”
In other words personality, individualism, reputation and leadership do make a difference, and in times of war, leaders bearing those qualities are difficult if not impossible to replace. But in times of peace, those qualities still matter, and we should never take those leaders for granted. I mention this because in the past several months, several Air Force leaders considered key to the GPS program have either retired, been promoted or left government service for personal reasons.
USAF General Ellen Pawlikowski is only the third female four-star general in USAF history, and she recently left SMC (Space and Missile Systems Center) for a job at the Pentagon, where she worked space and GPS acquisition and policy issues. From there she was promoted to four stars and now sits as just the ninth commander of Air Force Materiel Command. Gen. Pawlikowski was replaced at SMC by Lt. Gen. Samuel Greaves (USAF).
Brigadier General William Cooley (USAF) recently pinned on his first star while serving as the director of the GPS Directorate at SMC. He was recently selected for reassignment as program executive, Programs and Integration, Office of the Under Secretary of Defense for Acquisition, Technology and Logistics, Missile Defense Agency (MDA), Redstone Arsenal, Alabama —an organization where Lt. Gen. Sam Greaves once served as the deputy commander. Can you say career broadening? Brig. Gen. “Wild Bill” Cooley is being replaced by USAF Colonel Steve Whitney, who has distinguished himself with yeoman service at the directorate as the GPS Military User Equipment (MUE) guru.
David W. Madden serves as a member of the Defense Intelligence Senior Executive Service and functions as the executive director, Space and Missile Systems Center, Air Force Space Command, Los Angeles Air Force Base, Calif. He is the senior civilian executive and the deputy program executive officer for Space. His responsibilities include managing the research, design, development, acquisition and sustainment of satellites and the associated ground command and control systems and user terminals. In his military career, Dave served as the GPS Wing Commander at SMC. For personal and professional reasons, Dave has decided to leave government service soon, and my sources tell me he will take up a position in Denver, Colo. Unfortunately, I am not currently at liberty to say where. I have been told the name of Dave’s replacement, but it was in an FOUO session and therefore not currently releasable. Suffice it to say, the individual is eminently qualified.
Each of the individuals mentioned has a very strong personality and a certain way of doing business. I have known them all for years and can honestly say their personalities and personal leadership styles dominated their successful careers to date. Frankly, I don’t see that changing. So, when you hear that military personnel are interchangeable and personalities don’t matter, as I unfortunately heard a very senior official say publicly recently, please take that with a huge grain of salt and skepticism. People, personalities and leadership styles do matter, especially outside-the-box thinkers and leaders. Let’s wish everyone the best in their new endeavors.
Until next time, Happy Navigating, and remember: GPS is brought to you courtesy of the United States Air Force.
Microsoft will no longer collect its own map data, according to the website re/code. As part of the change, Microsoft is selling some of its assets to rideshare company Uber, including a data center, cameras, intellectual property and roughly 100 engineers. Uber is also buying a data center near Boulder, Colo.
Microsoft plans to continue to offer Bing Maps using data licensed from partners.
Microsoft already gets much of its map data from Nokia and other partners, but had been collecting its own aerial, 3D and street-level maps. It will now source those images from partners, focusing its Bing Maps work on the user experience that overlays the map data and imagery.
Industry watchers suggest the cameras might soon end up on the roofs of Uber vehicles. Uber already has hundreds of thousands of cars being tracked around the world every day.
EGNOS Service Provision Workshop 2015 will be held in Copenhagen September 29-30. The workshop is sponsored by the European Satellite Services Provider (ESSP).
The agenda, now available online, includes program and status updates on EGNOS on Day 1, as well as a focus on aviation. Included are an update on the EGNOS Safety-of-Life Service for aviation and several sessions focused on successful EGNOS implementation stories in aviation.
On Day 2, sessions include EGNOS market status and the adoption plan, EDAS for added value applications, E-GNSS benefits in the environmental domain, EGNOS in the maritime application domain and EGNOS in land application domain.
To learn more or to register, go to the ESSP website.
TeleCommunication Systems (TCS) has purchased location-based technology and intellectual property from Loctronix. TCS is integrating the newly acquired assets from Loctronix with its location solution portfolio. Combined, the location-based services (LBS) solutions will enable TCS to further develop indoor-location technology applications ranging from advertising and marketing to navigation and public safety, TCS said.
TCS specializes in secure and reliable wireless communications. The company’s patented solutions enable 9-1-1, commercial location-based services and deployable wireless infrastructure; cybersecurity; defense and aerospace components; and applications for mobile location-based services and messaging.
“Purchasing LBS technology and intellectual property from Loctronix not only adds to our already vast set of intellectual property rights for LBS, more importantly it underpins our continued commitment to further building out our advanced location product portfolio,” said Jay Whitehurst, TCS senior vice president and Commercial Software Group president. “In addition to expanding the breadth of our current location product offering, the Loctronix assets will provide clear differentiators in device location, and increase our market and revenue opportunities — both for commercial and public safety applications.”
“We have exciting news,” Loctronix announced on its website. “The global leader in Precise Device location, TeleCommunication Systems, Inc. (TCS) has integrated our assets with theirs. We have always said that our mission was to locate any device anywhere — indoors or outdoors. With our technology, TCS will now be able to do just that.”
TCS plans to roll out new solutions leveraging the Loctronix assets by year’s end.
Public Works and Government Services Canada (PWGSC) has selected NovAtel’s GAJT-AE antenna electronics for testing on Canadian Army platforms. The GAJT-AE, developed in Calgary at NovAtel’s global headquarters, is a GPS anti-jam solution suitable for small and weight constrained applications. The testing is being conducted through PWGSC’s Build in Canada Innovation Program (BCIP).
PWGSC will procure a number of GAJT-AE’s on behalf of the Department of National Defence (DND). The Director Land Requirements (DLR), with the assistance of the Quality Engineering Test Establishment (QETE), will oversee all testing on DND’s behalf. Field testing is expected to take place in the latter half of 2015 at 4th Canadian Division Support Garrison Petawawa.
The testing will analyze the performance of GAJT-AE on Canadian Army equipment in operational conditions to confirm the suitability and robustness of the NovAtel technology for this role. The process is expected to be completed by the end of March 2016.
GAJT is a null-forming technology that negates jammers, ensuring the satellite signals necessary to compute position and time are always available. Three categories of GAJT are manufactured by NovAtel:
GAJT-710ML: for use with military land vehicles, networks and timing infrastructure
GAJT-710MS: for marine vessels, from small boats to capital ships
GAJT-AE: for use with an external antenna in size and weight constrained applications
“NovAtel has had great success working closely with the Canadian Army on the previous round of BCIP,” said Jason Hamilton, NovAtel’s vice president of marketing. “It is essential to have military users test our products in operational scenarios. We look forward to the valuable feedback that the Canadian Army testing of GAJT-AE GPS anti-jam antenna electronics will provide. NovAtel will use this feedback to continue developing products in support of Canada and its Allied partners.”
The BCIP was created by the Government of Canada to strengthen Canadian innovation. The program offers procurement and testing of pre-commercialized products and services, at a late stage of development. The BCIP:
Bridges the “pre-commercialization gap”
Supports Canadian suppliers by connecting innovators and government users and by testing innovations
Provides real-world evaluation of pre-commercial goods and services
Improves the efficiency and effectiveness of government operations.
Trimble has announced the addition of a Supervisor app to its FieldMaster suite of mobile applications. The latest addition to the suite is designed to enable managers to stay efficient and effective on the go by empowering them to do more work in the field and manage their day-to-day operations remotely. With the FieldMaster Supervisor app, managers can leave the office and still have visibility into their fleet and mobile workers from their smartphone or tablet.
“Mobility is an increasingly valuable tool for field service organizations,” said John Cameron, general manager of Trimble’s Field Service Management (FSM) Division. “It allows a traditional office role to move into the field and still access up-to-date information about the performance of the field operation. The result is a more effective operation where managers in the field have the information they need at their fingertips.”
“I’m often meeting with customers or surveying a job so it’s important for me to know my technicians’ location,” said Dave Rowan, manager of Del-Mar Doors in Delaware. “I use FieldMaster Supervisor whenever I’m on the road. I can open the app and see where my team is, where they’ve been and how long they’ve been at each location. Having quick access to this information has improved my efficiency and productivity. FieldMaster Supervisor is an excellent tool.”
FieldMaster Supervisor is available with Trimble Fleet Management and Trimble Work Management solutions. Features include:
Viewing all locations of your entire team on a map
Seeing each team member’s job progress, including tasks at riskF
Finding the nearest worker to another team member or customer
Navigating to key locations using turn-by-turn directions
Inspecting job performance and documenting status in the field
Receiving important vehicle and driver performance alerts in real-time
FieldMaster mobile applications are a core component of FSM’s integrated suite of field service management solutions that includes Fleet Management, Work Management and Driver Safety. FieldMaster also includes a Technician app, which is an advanced collaboration tool for mobile technicians that allow them to receive, access and update job information in real-time for improved effectiveness on the job.
GEOINT 2015, like other major conferences, was both fascinating and frustrating. There was so much to see and learn and absolutely not enough time to take it all in. GEOINT 2015 took place June 22-25 in Washington, D.C.
Fortunately, the USGIF staff along with the USGIF Trajectory magazine staff under CEO Keith Masback’s direction made the best of this mega event through superb event planning and top-notch documentation, both in print and video. This column is just one man’s view and covers highlights that I saw and documented.
I shot video clips of technology that caught my eye, but with more than 300 exhibitors, keynote sessions, break-out and educational sessions plus special interest meetings (such as the Army Geospatial Center GeoPDF workshop), covering it all was not possible. However…
Every day of the conference, the USGIF Trajectory magazine staff published and printed a Show Daily. This slick publication was available every morning and served as a guide to the day’s events, along with providing highlights of the previous day. You can view/download each day’s issue. These five documents are probably the fastest way to get a full overview of the conference.
Below is a playlist of the videos I shot.
Key presentations that are a must-read:
Retired General Stanley McChrystal talked about transforming the Joint Special Operations Command from a purely top-down organization to one of shared intelligence and responsibility. Thanks to this “shared consciousness,” local units were able to act quickly, responding to rapidly changing events with smart autonomy because everyone shared the same intelligence.
National Security Agency (NSA/CSS) Director Adm. Michael Rogers said that each component of the signals intelligence (SIGINT) world has a physical location, and described how he has directed a much closer working relationship with the National Geospatial-intelligence Agency (NGA) to further intel and cyber efforts. He said that humans are very visually oriented, and although NSA’s SIGINT tools and products are very powerful, a more complete picture could be visualized if enhanced with GEOINT.
I was able to interview NGA Director Cardillo and Admiral Thad Allen, former commandant of the Coast Guard. I asked Director Cardillo about the NGA Emerald program and Adm. Allen about eLoran, one possible back up to GPS/PNT.
The pre-conference included education sessions and a fascinating group of five-minute lightning talks (pecha-kucha). I’m going to cover these in detail sometime in the next few months.
Generally, when I attend conferences I try to visit the small booths on the periphery of the exhibit hall. I’ve found that many showcase emerging technologies or are uniquely interesting. One example at GEOINT was the “Cartographic and Geographic Information Society” booth manned by Dr. Eric Anderson and Dr. Lynn Usery. They really struck a nerve with me — in the massive exhibit hall packed with high-tech wonders was this simple booth with a simple message: promoting good cartography. In this day of computer mapping and electronic media, too many technicians produce maps and sites that are really terrible looking and hard to grasp, so I fully appreciate the importance of good cartography to communicate effectively. See my Powerpoint/mapping rant several years ago to get my perspective.
Here are my videos of other exhibitors on the floor:
CACI — The ability to predict human activity with very high correlation using social media
GeoWeb3D — Very rapid display of imagery and 3D models
TerraGo — Edge, a disruptive technology for data collection
USGIF CEO Keith Masback (right) presents Bosarge with the USGIF Academic Research Award.
Tipping my hat to my adopted state of Alabama, I was pleased to see a Huntsville booth touting the 70-plus geospatial firms in the city along with a keynote from Huntsville Mayor Tommy Battle highlighting GEOHuntsville’s pending 2015 GEOINT Workshop August 12. Additionally, native son George Stanley Bosarge, University of South Alabama, was awarded the USGIF Academic Research Award for his work in assessing post-oil spill recovery and reef habitat off the coast of Alabama.
In general, attending GEOINT was like drinking from a firehose: lots of information in a very short period of time. However, I did build a list of great material for future columns, including a potentially small underground revolution growing in the GEOINT community.
A Vision-Aided Integrity Monitor for Precision Relative Navigation Systems
By Sean M. Calhoun, John Raquet and Gilbert L. Peterson
INNOVATION INSIGHTS by Richard Langley
TO MEET THE ACCURACY, availability, continuity and integrity requirements for many navigation applications, multiple-sensor systems are commonly used. For example, a GPS receiver might be combined with an inertial measurement unit, electronic compass and an altimeter to permit enhanced navigation accuracy, availability and continuity in obstructed or otherwise difficult environments. The use of arrays of sensors can also help to ensure that systems used in safety-critical navigation applications provide safe information by maintaining a high level of integrity.
An important group of devices that can be used in multi-sensor systems is one whose processes are based on light. These optical or vision-based devices include laser rangefinders and digital cameras. We could even consider our eyes to be in this group. In common with many other animals, we have built-in visual sensors to get around in our daily lives. Together with our memories, we use our eyes to get safely from one place to another. Ancient mariners tended to sail close to shore so that they could use visual cues for navigation. Later on, they learned how to use the light from celestial objects to navigate in the open ocean. And these days, while we could use the so-called “Mark 1 Eyeball” to continuously monitor the performance of a navigation system, this is often impractical, impossible or unwise.
In this month’s column, we’ll take a look at the development of a generalized vision-aided integrity monitor for precision relative navigation applications. The work is based on the concept of using a single-camera vision system, such as a visible-light or infrared electro-optical sensor, to monitor the occurrence of unacceptably large and potentially unsafe relative navigation errors. A vision-aided integrity monitor of this type could be extremely valuable in augmenting existing precision relative navigation systems, such as GPS, for many different safety-critical aerospace applications such as formation flying, aerial refueling, rendezvous/docking systems, and even precision landing.
It is particularly appropriate that such vision-aided systems be discussed at the present time since 2015 is the International Year of Light and Light-based Technologies, or IYL 2015. This United Nations initiative aims to raise awareness of the achievements of light science and its applications, and its importance to humankind. As mentioned on the IYL 2015 website, “[l]ight plays a vital role in our daily lives and is an imperative cross-cutting discipline of science in the 21st century. It has revolutionized medicine, opened up international communication via the Internet, and continues to be central to linking cultural, economic and political aspects of the global society.”
2015 is also an important anniversary year for several notable developments in our understanding of light. It is the 1,000th anniversary of the work of the Arabic scholar Ibn Al-Haytham, which culminated in his Book of Optics. A Latin translation significantly influenced a number of scholars in medieval and renaissance Europe including Leonardo da Vinci, Galileo Galilei, and Johannes Kepler. 2015 is also the 200th anniversary of Augustin-Jean Fresnel’s proposal that light behaves as a wave and the 150th anniversary of the publication of James Clerk Maxwell’s paper describing electromagnetic wave propagation as we discussed in “Insights” this past March. And we should also mention that 2015 is the 100th anniversary of the publication of Albert Einstein’s general theory of relativity, which includes a description of the propagation of light and other electromagnetic waves in the presence of a gravitational field. And where would GPS and the other global navigation satellite systems and their augmentations be without the understanding that general relativity provides? Nowhere.
“Innovation” is a regular feature that discusses advances in GPS technology and its applications as well as the fundamentals of GPS positioning. The column is coordinated by Richard Langley of the Department of Geodesy and Geomatics Engineering, University of New Brunswick. He welcomes comments and topic ideas. Email him at lang @ unb.ca.
Recently, there has been an increased recognition of GNSS limitations in terms of robustness, availability and interference. As a result of this recognition, there has been renewed interest in developing non-GNSS-based navigation systems to augment system capability. This has become particularly important with the trend toward autonomous systems, where required navigation performance (RNP) metrics, such as accuracy, integrity, continuity and availability become operational drivers. Because of this trend, there is renewed interest in gaining navigational diversity using imaging or vision-aided navigation approaches. Early research with vision systems used 3-D terrain databases and imaging systems to provide periodic position updates in collaboration with onboard inertial navigation systems (INS), much like radar systems did prior to the wide proliferation of GNSS.
For precision relative navigation applications such as formation flying, aerial refueling, rendezvous and docking systems and even precision landing, there is a significant body of research for the use of vision navigation systems. For example, a vision-based relative navigation solution for aerial refueling with the use of an a priori 3-D tanker model has been developed. Results from flight tests showed that image-rendering relative navigation is a viable precision navigation technique for close formation flight, specifically aerial refueling, and demonstrated 95% relative navigation accuracies on the order of 35 centimeters within the operational envelope.
As the body of vision-aided navigation research continues to grow, consideration of other RNP metrics is required. Ensuring that systems are providing safe information and maintaining a high level of integrity is paramount when considering safety-critical navigation applications, but is largely neglected in current vision-navigation research.
The concept of integrity, particularly for navigation systems, refers to the level of trust that can be placed in a navigation system in terms of detecting gross errors and divergences. Many navigation applications have adopted the use of protection levels, which are real-time navigation system outputs that bound the navigation errors to the required probability of integrity risk. For the case of vertical navigation, the vertical navigation system error (NSE) is bounded by the real-time vertical protection level (VPL), and as the long as the VPL is below the vertical alert limit (VAL), the system can continue its operation. Loss of integrity is defined by the case when the NSE > VAL without an alert or, in other words, when NSE > VAL and VPL ≤ VAL.
One of the richest sources of information for how integrity can be handled for precision relative navigation systems can be found with the Local Area Augmentation System (LAAS), which focused on providing integrity under fault-free and single ground reference receiver failure conditions. LAAS employs several quality monitors such as receiver autonomous integrity monitoring (RAIM).
Much of the vision-aided navigation research to date has focused more on system and algorithmic robustness, rather than quantitative and verifiable integrity, particularly for feature-based processing. One approach has introduced the concept of regional bounding for feature correspondence between time-sequenced image frames, including some feature-unique criteria that can provide some protection from feature correspondence errors. Although this approach does yield some robustness for the algorithms, no quantitative integrity characterization was developed. Another approach introduced a truly quantitative integrity monitor for failures in the mapping of features to pixels, particularly in the presence of a bias. This approach predicts the largest possible position error in the presence of one such bias due to feature mismatch using a GPS RAIM-type approach. The current state of research addressing integrity for vision navigation, using an image-rendering or template-matching approach, is even less mature. In fact, we have not identified any previous integrity-specific work for image-rendering vision navigation.
The research presented in this article generalizes the concept of integrity in terms of operating and alerting regions. Applications that use navigation systems generally have objective operating regions that require a certain navigation performance, whether this be around a glide-slope, a formation flight position or even a flight-path clearance. Navigation integrity becomes critical because large divergences from these operating regions, without an alert, can become safety risks. The alert limit is simply the instantiation of this concept. It is the threshold or measure of how much undetected divergence from the operating region can be tolerated without inducing unacceptably large safety risks.
The remaining sections of this article will describe the development of a rigorous and quantitative vision-aided integrity monitor for precision relative navigation systems. First, an introduction to relative navigation using image rendering will be covered in order to describe the fundamental vision navigation approach. This will be followed by a detailed derivation of the proposed vision-aided integrity monitor and simulation based performance results.
Using Image Rendering
The basis of our research is that vision-aided techniques, specifically image rendering, can be used to construct a high-performance integrity monitor for precision relative navigation systems. Image rendering approaches and/or template matching have been used extensively in vision applications such as machine vision, medical image registration, object detection and pose estimation, and recently as a precision navigation system for applications such as aerial refueling and formation flight. The general concept of image-rendering precision relative navigation was evaluated for an automated aerial refueling application, using the approach illustrated in Figure 1. The image rendering approach is based on comparing image sensors with rendered imagery from high-fidelity models, to estimate a relative location based on the best image correspondence.
The image correspondence process is the most critical aspect of the image-rendering or template-matching navigation approach, but the focus of our research is not to make claims of optimality or performance-difference judgments between these image correspondence techniques, but rather show feasibility in the overall vision-aided integrity approach using some of these techniques. Most image correspondence approaches transform the images into feature space, such as scale-invariant feature transform, silhouette, edges and corners, to name a few, and then compute a distance metric between the feature sets, such as Minkowski or Mahalanobis distance, to determine the degree of matching.
Once the actual sensor image is converted to feature space, rendered images are generated based on the relative navigation state estimate using the model, converted to feature space, and compared to the sensor features. This process is repeated across the navigation state space, computing an image correspondence value for each state estimate. The selected navigation state estimate is based on the “best” image correspondence value across the state space.
An example result of this process is presented in FIGURE 2, which shows correspondence values for an edge-based image-correspondence process. In this case, the minimum correspondence value represents the best estimate of the relative navigation state. These image correspondence values between the sensor image (IS) and the rendered reference images (IR) will form the basis for the integrity monitor detection rule.
FIGURE 2. GRD-based image correspondence illustration as a function of 2-D relative navigation state.
Vision-Aided Integrity Monitor Development
As indicated in the preceding sections, our research is based on defining a vision-aided integrity monitor in terms of detecting when the system navigation state (x) is within a specified operating region (XOR) versus being within the alert region state space (XAR). The integrity monitor can yield four distinct conditions: rejection (PR), misdetection (PMD), detection (PD) and false-alarm (PFA). The performance of this type of binary (H0/H1) detection scheme can be characterized using just two of these metrics, the detection and false-alarm rates, which will be the two primary performance metrics for this research. PD is the primary metric measuring navigation integrity, describing the probability that the monitor successfully detects the condition when x ∈ XAR.
Bayesian, Minimax and Neyman-Pearson are a few of the detection schemes available to solve this type of binary detection problem. These detection schemes rely on the knowledge of the underlying statistics of the H0 and H1 condition, often characterized in terms of the probability density functions (PDFs). The main difference between these approaches is the resulting detection rule value (δ). Once δ has been established, the resulting theoretical performances of the detectors are computed by integrating the underlying PDFs of the H0 and H1 conditions, pH0 and pH1 respectively. The probability of detection (PD) is computed as
(1)
The integrity performance of the monitor can also be described in terms of integrity risk or probability of missed detection
(PMD), which is computed as
(2)
Similarly, the probability of false-alarm (PFA) is computed as
(3)
This is represented graphically in FIGURE 3.
FIGURE 3. Graphical illustration of detection performance.
The PDFs represent the statistical distributions of image correspondence values for the respective H0/H1 condition. The general detection rule premise is such that for a given sensor image, the underlying PDF for the “best” image correspondence with the rendered reference set is sufficiently distinct when the sensor image is in an H0 condition versus H1. The characteristics of the H0/H1 PDFs that dictate the monitor performance are dependent on many factors, including the fidelity and accuracy of the world model, the general observability of the image rendering process and the image correspondence approach for the specific application. For our research, we used two image correspondence techniques to evaluate the overall integrity monitor approach.
The first image correspondence technique evaluated is a simple binary silhouette (SIL). In this approach, both the sensor image IS(x) and reference image set IR() are converted to a silhouette using pre-defined thresholds to first convert the red-green-blue (RGB) images to gray scale and then subsequently to a binary image. An image correspondence function computes the percentage of overlap between the silhouettes.
The resulting image correspondence is based on the ratio of the cardinality of these sets. The navigation state estimate () that yields the maximum image correspondence value from the set of rendered reference images or template database is considered the most likely for that particular image sensor (IS).
The second image correspondence utilizes edge features for the image correspondence process. Under this approach, magnitude of gradient (GRD) processing is used, in which the sensor image and the rendered reference images are preprocessed through a Prewitt filter to determine changes in image intensities between adjacent pixels. This process computes the components of the gradient. The gradient magnitude is computed by root-sum-squaring the x-y components and normalized, resulting in an edge detection. A Gaussian blur filter is then applied to the output of the edge detection.
The application of the Gaussian blurring compensates for the spatial discrepancies between the discrete reference set or template database and the sensor image. Finally, the resulting feature images, including both the reference image (IR_GRD) and the sensor image (IS_GRD), are processed through a sum-squared-difference (SSD) image correspondence.
The resulting PDFs are based on the best image correspondence with the RE reference set, which is the minimum for the GRD processing.
These image correspondences build the basis of the detection metric, utilizing both the sensor image (IS) and the rendered reference set (IR), which is spatially distributed across the operating region, illustrated by FIGURE 4. This illustrated example shows instances of both a H0 and H1 sensor image (blue and red, respectively). The underlying H0/H1 PDFs for establishing the detection threshold are determined by sampling sensor images from XOR and XAR and computing the image correspondence against IR. This can be done through a combination of high-fidelity simulation and/or test data. The overall performance of the integrity monitor will be dictated by these underlying distributions. The following sections show the results of this integrity monitor approach for an aerial refueling application.
FIGURE 4. Simplified example of rendered reference set (IR) illustrating image correspondence process for integrity monitoring.
Simulation Evaluation
To explore the performance of the proposed integrity monitor approach, an aerial refueling (AR) application was modeled within a simulation environment. The AR operation lends itself well to the construct of the proposed integrity monitor and is developed to show that the system (refueling aircraft) is in the refueling envelope (RE) and has not violated the alert limit, which in the AR case is the safety boundary (SB). In this operational case, H0 is defined as the condition when the integrity monitor determines the refueling aircraft is in the RE, and H1 as the case when the integrity monitor determines the refueling aircraft to be within the SB. A validity region is also defined in order to bound the problem, in which it is assumed that the refueling aircraft is always within, under both H0 and H1 conditions, as shown in FIGURE 5.
FIGURE 5. Integrity regions of interest for an aerial refueling application and illustrated example of a rendered H0 image set for the refueling envelope used as the correspondence basis for the integrity detection metric.
To determine the underlying H0/H1 distributions, a set of reference images uniformly sampled from the RE was rendered using the associated tanker and camera models. This rendered image set was used as the common basis for performing the image correspondence with the actual sensor image.
The baseline RE reference set used for this research was developed using 504 rendered images distributed in a spherically uniform manner across the entire RE volume. Then, two random sets of simulated sensor images were generated and drawn from both RE and SB regions. It is assumed that the refueling aircraft and corresponding sensor images are within the validity region in order to bound the simulation. This bounding assumption is an acceptable constraint, given that the system most likely had to pass several operational checks to ensure the refueling aircraft is in the general region of the RE as defined by the validity region. To get detailed statistical representation of the PDFs, particularly at the tails of the distribution, both RE and SB image sets included more than 100,000 simulated sensor images, representing true states of the refueling aircraft. The simulation environment for this analysis uses the same refueling tanker model for the sensor images and the RE reference set, which eliminates the effects of modeling errors. Additionally, variations in the attitude are currently not considered. The resulting PDFs for H0 (blue) and H1 (red) conditions are shown in FIGURE 6.
FIGURE 6. Underlying image correspondence distribution for H0 (blue) and H1 (red) conditions.
Figure 6 shows generally good distinction between the H0 and H1 hypotheses — a necessary condition to achieve good detection performance. Several techniques were evaluated for determining the PDF including histogram, nearest neighbor and kernel with a Gaussian weighting function. These underlying H0 and H1 distributions will be used as the basis for designing the detection thresholds, based on the image correspondence of the sensor image with the RE reference set. These results assume uniform prior distributions across the RE and SB regions; however, it would be relatively straightforward to incorporate non-uniform prior information, based on a particular application, as available.
Detection schemes are often characterized using receiver operating characteristics or ROC curves, which illustrate the detection-monitor trade-off between probability of detection and probability of false alarm. The predicted detection performance for this AR application is a function of these underlying H0/H1 PDFs, and this performance is captured in the ROC curves shown in FIGURE 7. The ROC curves show that 10-3 level integrity-monitor detection performance (PD) is realizable for both SIL and GRD image correspondence approaches, while still maintaining a reasonable probability of false alarm (PFA) of less than 0.05 (5%). The SIL approach demonstrates slightly better performance than GRD under the chosen image resolution and RE reference set density. Normally, theoretical ROC curves would extend through the whole range of values [0,1] for both PD and PFA; however, this assumes unbounded PDFs. Doing so would require an infinite number of simulation cases and is obviously not practical for a simulation evaluation to gain statistics necessary to extend the PDFs near the entire theoretical ranges. Overbounding of the PDF tails could be performed to extrapolate and extend the tails of H0/H1 PDFs to determine the integrity detection performance beyond the current ranges, but this was not performed as part of this research.
FIGURE 7. Predicted integrity detection performance for both SIL and GRD image correspondence techniques.
In most applications, conditions exist that are outside of the nominally defined operational envelope, but yet are not significant enough deviations to be considered safety risks that require alerts and action. Such a case exists for the refueling operation under consideration in this research, where there exists a region outside the RE, but not in the SB, which we will refer to as the operational limit volume (OLV). The current definitions of H0 and H1 for the vision-aided integrity-monitor approaches developed above only consider conditions within the RE or the SB volume, and not within the OLV volume. OLV conditions were omitted since they technically aren’t considered a safety or integrity risk. However, it is possible under certain implementations and operational considerations that integrity monitoring coverage is desired under these OLV conditions.
Using the same analysis process as the original evaluation, an updated simulation was performed, this time considering all points within the validity region, including the OLV points. To construct a detection scheme under this new paradigm, the OLV conditions must be either mapped to the existing H0 or H1 hypotheses, or a new hypothesis must be defined, possibly creating an M-ary hypothesis scenario. The approach taken for this research was to consider OLV conditions as a safety risk, which is a conservative approach, rather than defining any new hypotheses. The resulting image correspondence distributions are shown in FIGURE 8. Subplots (a) and (b) show the difference the OLV points have on the underlying PDF distributions. As expected, when the OLV points are excluded, the PDFs track the original distributions quite well. The impact of including sensor locations from the OLV is clear from these figures, yielding a much bigger overlap between the H0/H1 conditions.
FIGURE 8. Simulation testing results assuming OLV states are a safety risk. The prediction represents expected performance without consideration of the OLV states. (a) SIL image correspondence PDFs,(b) GRD image correspondence PDFs, (c) SIL ROC curve, (d) GRD ROC curve.
Much like the PDFs, the ROC curves align with the previous results quite well when the OLV conditions are omitted, but take a order of magnitude integrity performance hit when OLV is captured under the existing H0/H1 definition and detection thresholds. Even under this conservative assumption, the overall monitor performance still yields a 0.96 (96%) detection rate at a 0.05 (5%) false-alarm rate, as illustrated by the ROC curves shown in subplots (c) and (d) of Figure 8. It is likely that these results could be significantly improved by redefining the terms of the H0 and H1 conditions or defining an H2 condition specifically for the OLV region.
Sensitivity Analysis
In addition to the baseline integrity monitor results, various sensitivity studies were performed to evaluate the integrity monitor performance impacts of environmental and hardware considerations. These sensitivity evaluations focused on common vision-based considerations such as sensor distortions and lighting conditions, and monitor design choices such as pixel resolution and reference image density. The sensitivity aspects that were evaluated under this research included the number of reference images, the effects of image distortion, pixel resolution and lighting conditions.
Reference Set Density. In addition to our standard reference set of 504 RE images, we conducted tests using 288 and 729 images. While a larger number of images improves integrity detection performance, processing speed is decreased. It is possible to trade off processing power for performance as necessary for a particular application and the associated integrity monitor performance requirements.
Image Distortion. We applied radial and tangential distortions to the simulated sensor images (IS) such that they represented a 95% certainty of the residual error to represent an outer envelope case for this type of sensor. The impact on the H0/H1 PDFs is very minimal, and the results demonstrate a potential robustness to this common type of sensor effect.
Pixel Resolution. We evaluated eight different pixel resolutions from 12 × 9 to 1280 × 1024 pixels per image. Our results showed a surprising robustness to pixel resolution, indicating only marginal performance impacts down to extremely limited pixel densities.
Lighting Conditions. To explore the impact of lighting conditions, the simulated sensor images (IS) used as the basis for the sensitivity analysis were regenerated under a secondary lighting condition, intended to emulate a much brighter background environment, and processed against the original RE reference set. The results demonstrate that under these varying lighting conditions, the system again demonstrates a high level of robustness, particularly using the SIL image correspondence approach.
Ratio Test Integrity Test
The initial integrity monitor results discussed thus far only used reference images from the operational region, RE. However, it is also possible to use a reference image set created with rendered images from the alert region, SB, by including an additional image correspondence process between the sensor image and rendered SB reference set. This is done to create a ratio test statistic as the detection metric. We compute the ratio of the highest image correspondence between the RE and SB reference sets. This approach is very analogous to the use of ratio tests for GNSS carrier-phase integer fixing.
The resulting ROC detection performance of the ratio threshold approach showed that, as with the single RE reference set, the SIL image correspondence approach yields the best H1 detection performance, resulting in the best integrity protection.
The GRD ratio detection performance also yields improved performance and is comparable to the SIL image correspondence approach solely with RE reference set.
Conclusions and Future Work
In this article, we have discussed the feasibility of a vision-aided integrity monitor for precision relative navigation systems. The research posed the relative navigation integrity problem within the context of an aerial refueling application. Using image rendering, where an imaging sensor and high-fidelity 3-D model is used, we have shown that 10-3 to 10-5 level of integrity monitoring is attainable for aerial refueling and formation flight applications. Having this level of independent monitoring could provide significant relief to a GPS-based precision relative-navigation system from a system-safety and certification perspective. The research demonstrated the proposed integrity monitor was robust against several degrading imaging effects, including lens distortions, lighting conditions and reductions in pixel resolution. Although more work is required to validate the results of this research, which was based on simulated images, the results show high promise for this type of integrity monitor approach.
Disclaimer
The views expressed in this article are those of the authors and do not reflect the official policy or position of the United States Air Force, Department of Defense, or the U.S. Government.
Acknowledgment
This article is based on the paper “Vision-Aided Integrity Monitor for Precision Relative Navigation Systems” presented at ITM 2015, the 2015 International Technical Meeting of The Institute of Navigation held in Dana Point, Calif., Jan. 26–28, 2015.
SEAN CALHOUN is the managing director at CAL Analytics, Columbus, Ohio, and is pursuing his Ph.D. degree at the Air Force Institute of Technology (AFIT), Wright-Paterson Air Force Base, Ohio.
JOHN RAQUET is the director of the Autonomy and Navigation Technology Center at AFIT, where he is also a professor of electrical engineering.
GILBERT L. PETERSON is a professor of computer science at AFIT and vice chair of the International Federation for Information Processing Working Group 11.9, Digital Forensics.
FURTHER READING
Authors’ Conference Paper
“Vision-Aided Integrity Monitor for Precision Relative Navigation Systems” by S.M. Calhoun, J. Raquet and G. Peterson in Proceedings of ITM 2015, the 2015 International Technical Meeting of The Institute of Navigation, Dana Point, Calif., Jan. 26–28, 2015.
Image-Sensor Navigation
“Flight Test Evaluation of Image Rendering Navigation for Close-Formation Flight” by S.M. Calhoun, J. Raquet and J. Curro in Proceedings of ION GNSS 2012, the 25th International Technical Meeting of the Satellite Division of The Institute of Navigation, Nashville, Tenn., Sept. 17–21, 2012, pp. 826–832.
“Fusing Low-Cost Image and Inertial Sensors for Passive Navigation” by M. Veth and J. Raquet in Navigation: Journal of The Institute of Navigation, Vol. 54, No. 1, Spring 2007, pp. 11–20. doi: 10.1002/j.2161-4296.2007.tb00391.x.
“Automated Rendezvous and Docking Sensor Testing at the Flight Robotics Laboratory” by J.D. Mitchell, S.P. Cryan, D. Strack, L.L. Brewster, M.J. Williamson, R.T. Howard and A.S. Johnston in Proceedings of 2007 IEEE Aerospace Conference, Big Sky, Mont., March 3–10, 2007, doi: 10.1109/AERO.2007.352723.
“Performance of Integrated Electro-Optical Navigation Systems” by T. Hoshizaki, D. Andrisani II, A.W. Braun, A.K. Mulyana and J.S. Bethel in Navigation: Journal of The Institute of Navigation, Vol. 51, No. 2, Summer 2004, pp. 101–121, doi: 10.1002/j.2161-4296.2004.tb00344.x.
Simultaneous Localization and Mapping
“A Review of Recent Developments in Simultaneous Localization and Mapping” by G. Dissanayake, S. Huang, Z. Wang and R. Ranasinghe in Proceedings of 6th IEEE International Conference on Industrial and Information Systems, Kandy, Sri Lanka, Aug. 16–19, 2011, pp. 477–482, doi: 10.1109/ICIINFS.2011.6038117.
Navigation Integrity
“Developing a Framework for Image-based Integrity” by C. Larson, J.F. Raquet and M.J. Veth in Proceedings of ION GNSS 2009, the 22nd International Technical Meeting of the Satellite Division The Institute of Navigation, Savannah, Ga., Sept. 22–25, 2009, pp. 778–789.
“From RAIM to NIOAIM: A New Integrity Approach to Integrated Multi-GNSS Systems” by P.Y. Hwang and R.G. Brown in Inside GNSS, Vol. 3, No. 4, May-June 2008, pp. 24–33.
Minimum Aviation System Performance Standards for Local Area Augmentation System (LAAS), DO-245A, by RTCA SC-159 WG-4, RTCA Inc., Washington, D.C., December 2004.
Camera Calibration
“Flexible Camera Calibration by Viewing a Plane from Unknown Orientations” by Z. Zhang in Proceedings of ICCV’99, the Seventh IEEE International Conference on Computer Vision, Kerkya, Greece, Sept. 20–27, 1999, Vol. 1, pp. 666–673, doi: 10.1109/ICCV.1999.791289.
Digital Image Processing
Digital Image Processing, 4th Ed., by W.K. Pratt, published by John Wiley & Sons, New York, 2007.
Digital Image Processing, 3rd Ed., by R.C. Gonzalez and R.E. Woods, published by Prentice Hall, Upper Saddle River, N.J., 2007.
Signals and Noise
Detection of Signals in Noise, 2nd Ed., by R. N. McDonough and A.D. Whalen, published by Academic Press, Inc., Waltham, Mass., 1995.
An Introduction to Signal Detection and Estimation, 2nd Ed., by H.V. Poor, published by Dowden & Culver, an imprint of Springer, New York. 1994.
Figure 1. Example of the GNSS signal propagation using ray-tracing and a 3D building map.
A particle-filter-based positioning method using a 3D map to rectify the errors created by multipath and non-line-of-sight signals on the positioning result delivered by a low-cost single-frequency GPS receiver takes a multi-GNSS approach, using the combined signals of GPS, GLONASS and QZSS. The method outperforms conventional positioning in availability and positioning accuracy. It will likely be fused with other sensors in a future pedestrian navigation application.
By Li-Ta Hsu, Shunsuke Miura and Shunsuke Kamijo
GPS provides an accurate and reliable positioning/timing service for pedestrian application in open field environments. Unfortunately, its positioning performance in urban areas still has a lot of room for improvement, due to signal blockages and reflections caused by tall buildings. The signal reflections can be divided into multipath and non-line-of-sight (NLOS) effects. Recently, use of 3D building models as aiding information to mitigate or exclude multipath and NLOS effects has become a promising area of study.
At first, researchers used the 3D map model to simulate multipath effects to assess the single-reflection environment of a city. Subsequently, the metric of NLOS signal exclusion using an elevation-enhanced map, extracted from a 3D map, was developed and tested using real vehicular data. An extended idea of identifying NLOS signals using an infrared camera onboard a vehicle has been suggested. The potential of using a dynamic 3D map to design a multipath-exclusion filter for a vehicle-based tightly coupled GPS/INS integration system has also been studied. A forecast satellite visibility based on a 3D urban model to exclude NLOS signals in urban areas was developed.
The research approaches outlined above seek to exclude the NLOS signal; however, the exclusion is very likely to cause a horizontal dilution of precision distortion scenario, due to the blockage of buildings along the two sides of streets. In other words, the lateral (cross direction) positioning error would be much larger than that of the along-track direction.
Therefore, approaches applying multipath and NLOS signals as measurements become essential. One of the most common methods, the shadow-matching method, uses 3D building models to predict satellite visibility and compare it with measured satellite visibility to improve the cross street positioning accuracy. A multipath and NLOS delay estimation based on software-defined radio and a 3D surface model based on a particle filter was proposed and tested in a static experiment in the Shinjuku area of Tokyo.The research team of The University of Tokyo developed a particle-filter-based positioning method using a 3D map to rectify the positioning result of commercial GPS single-frequency receiver for pedestrian applications.
An evaluation of the QZSS L1-submeter-class augmentation with integrity function (L1-SAIF) correction to the proposed pedestrian positioning method was also discussed in an earlier paper by the authors of this article. However, satellite visibility in the urban canyon using only GPS and QZSS would not be enough for this proposed method. The use of emerging multi-GNSS, encompassing GLONASS, Galileo and BeiDou, could furnish a potential solution to the lack of visible satellites for this method. This article assess the performance of the proposed pedestrian positioning method using GPS, GLONASS and QZSS.
Building Models Construction
Our work established a 3D building model by a 2D map that contained building location and height information of buildings from 3D point-clouds data. The Fundamental Geospatial Data (FGD) of Japan, which provided by Japan geospatial information authority, is open to the Japanese public. This FGD data is employed as 2D geographic information system (GIS) data. Thus, the layouts and positions of every building on the map could be obtained from the 2D GIS data. In this article, the 3D digital surface model (DSM) data is provided by Aero Asahi Corporation. Figure 2 shows the process of constructing the 3D building model used here. This process first extracts the coordinates of every building corner from FGD as shown in the left of Figure 2. Then, the 2D map is integrated with the height data from DSM. The right of Figure 2 illustrates an example of a 3D building model established in this way. The 3D building map contains a very small amount of data for each building in comparison to that of the 3D graphic application. For our purposes, the file only contains the frame data of each building instead of the detail polygons data. This basic 3D building map is utilized in the simulation of ray-tracing.
Figure 2. The construction of the 3D building map from a 2D map and DSM.
Our version of the ray-tracing method does not consider diffractions or multiple reflections because these signals occurred under unfavorable conditions. Here, we utilize only the direct path and a single reflected path. The developed ray-tracing simulation can be used to distinguish reflected rays and to estimate the reflection delay distance. Our research work assumes that the surfaces of buildings are reflective smooth planes, that is, mirrors. Therefore, the rays in the simulation obey the laws of reflection. In the real world, the roughness and the absorption of the reflective surface might create a mismatch between the ray-tracing simulation and the real propagation. Here we ignore this effect, as the roughness of the building surface is much smaller than the propagation distance.
The opening figure (Figure 1) shows an example of the GNSS signal propagation using ray-tracing and a 3D building map. Red, green and white lines denote the LOS path, reflected paths and the NLOS paths, respectively. In this environment, a conventional positioning method such as weighted least squares (WLS) usually estimates the position on the wrong side of street as shown in the red balloon. With the aid of 3D building model and ray-tracing, the map-based positioning method is able to provide a result close to the ground truth.
Map-Based Pedestrian Positioning
The flowchart of the 3D city building model-based particle filter is shown in Figure 3. This method first implements a particle filter to distribute position candidates (particles) around the ground-truth position. In Step 2, when a candidate position is given, the method can evaluate whether each satellite is in LOS, multipath or NLOS by applying the ray-tracing procedure with a 3D building model. According to the signal strength, namely carrier-to-noise ratio (C/N0), the satellite could be roughly classified into LOS, NLOS and multipath scenarios. If the type of signal is consistent between C/N0 and ray-tracing classification, the simulated pseudorange of the satellite for the candidate will be calculated. In the LOS case, simulated pseudoranges can be estimated as the distance of the direct path between the satellite and the assumed position. In the multipath and NLOS cases, simulated pseudoranges can be estimated as the distance of the reflected path between the satellite and the candidate position via the building surface.
Figure 3. Flowchart of the particle filter using 3D city building models.
Ideally, if the position of a candidate is located at the true position, the difference between the simulated and measured pseudoranges should be zero. In other words, the simulated and measured pseudoranges should be identical. Therefore, the likelihood of each valid candidate is evaluated based on the pseudorange difference between the pseudorange measurement and simulated pseudorange of the candidate, which is simulated by 3D building models and ray-tracing.
Finally, the expectation of all the candidates is the rectified positioning of the proposed map method. This method can therefore find the optimum position through a dedicated optimization algorithm of these assumptions and evaluations. The positioning principle of the proposed method is very different from the conventional GPS positioning method, that is, WLS. As a result, the calculation of the positioning accuracy of the 3D map method should be also different.
We define two positioning performance measures for the 3D map method: user range accuracy of the 3D map method (URA3Dmap) and positioning accuracy.
The value of URA3Dmap is to indicate its level of positioning service, which is similar to the user range accuracy (URA) of conventional GPS. The URA3Dmap is defined based on the percentage of the valid candidates from all candidates outside the building. The higher percentage of the valid candidate implies a higher confidence of the estimated position. Ideally, if the center of the candidate distribution is not far from the ground truth, the simulated pseudorange of the candidates located at the center of distribution would be very similar to the measurement pseudorange. We define the URA3Dmap as shown in Table 1.
Table 1. The definition of URA and URA3Dmap used in this article.
Experiments and Discussion
We selected the Hitotsubashi and Shinjuku areas in Tokyo to construct a 3D building model because of the density of the tall buildings. In this area, multipath and NLOS effect are frequently observed. We tested pedestrian navigation in a typical path that included walking both sides of street and passing through/waiting at a road intersection. The cut-off angle is 20 degrees. The data were collected in November and December 2014.
We compare here two single point positioning methods: single-point positioning solutions provided by open source RTKLIB software (RTKLIB SPP), and the proposed 3D map method. RAIM FDE of the RTKLIB SPP is used here as a conventional NLOS detection algorithm. The test used a geodetic-grade GNSS receiver and a commercial grade receiver. The geodetic receiver was only used to collect the QZSS L1-SAIF correction signal. The antenna of the commercial receiver was attached in the strap of the backpack as shown in Figure 4. The receiver is connected to a tablet to record the GNSS measurements and is set to output pseudorange measurements and positioning results every second.
Figure 4. Equipment set-up.
We generated a quasi-ground truth using a topographical method.Video cameras were set in the ninth and18th floors of a building near the Hitotsubashi and Shinjuku areas, respectively, to record the traveled path. The video data output by the cameras are used in combination with one purchased high-resolution aerial photo to get the ground truth data. The aerial photo is 25 cm/pixel and therefore the error distance for each estimate can be calculated. The synchronization between video camera and commercial GNSS receiver is difficult to get as accurate as in the topographical method. As a result, we used point to “points” positioning error to evaluate the performance of the dynamic experiment. The synchronization error is limited to 1 second. Hence, for each estimated position x(t), the ground truth points used to calculate the positioning error is xGT (t-1), xGT (t) and xGT (t+1). The point to “points” positioning error is calculated as:
Three performance metrics are used here: mean, standard deviation of the point to points error, and the availability of positioning solution. The availability defined here means the percentage of given solutions in a fixed period. For example, if a method outputs 80 epochs in 100 seconds, the availability of the method is 80 percent.
This research demonstrates two dynamic data. The skyplot of the data are shown in Figure 5. The satellites are tracked by the commercial receiver. The grey areas indicate the obstruction of the surrounding buildings. The two dynamic data are typical signal receptions at Hitotsubashi (middle urban canyon) and Shinjuku (deep urban canyon) areas.
Hitotsubashi Mid-Canyon. To study the benefit of using different GNSS constellations in the 3D map method, Figure 6 shows the trajectory estimated by the proposed method under different satellite constellations. The different colors indicate different values of URA3Dmap of each point. This walking trajectory is divided into five sections (identified as A, B, C, D and E in the right-most of the three plots). In the GPS-only case (left), results in A and B sections have much better performance than sections D and E, because more than half of the GPS satellites are blocked at D and E, as shown in the left of Figure 5.
Figure 5. The left and right are the skyplot of the dynamic experiment at the Hitotsubashi and Shinjuku areas, respectively, in Tokyo.
The middle plot in Figure 6 shows the trajectory using GLONASS. It is obvious that the positioning results located at the right side of street are greatly increased, derived from the greater number of satellites in view. However, the quality of the GLONASS signal is not as good as GPS because multipath has a double effect on GLONASS.
Figure 6. Positioning results of the proposed 3D map method using different combinations of satellite constellations in a middle urban canyon.
In summary, the positioning error of applying GLONASS maintains a similar level, and availability increases about 12 percent compared to using GPS only. The right plot of Figure 6 shows the result after adding QZSS L1 C/A and L1-SAIF. This increases the results of C, D and E sections, because QZSS provides a high-elevation-angle satellite to the 3D map method. As a result, the number of valid candidate points in C, D and E sections increases dramatically. The reliability in C, D and E sections is also much higher than that of GPS+GLONASS. In addition, the trajectory became smoother than before.
Table 2 compares the positioning results of both RTKLIB SPP and the 3D map method, showing the 3D map method using GPS, GLONASS and QZSS to have the best performance among three scenarios. The positioning error mean and availability are 3.89 meters and 96.72 percent, respectively. The positioning error mean could be further improved to 3.23 meters if selecting the position point with URA3Dmap ≤ 3 (yellow, orange and red points in Figure 6). This selection will lose about 17 percent of availability.
Table 2. Positioning results of the 3D map method using different combinations of satellite constellations in a middle urban canyon.
Shinjuku Deep Canyon. We conducted a similar experiment in the Shinjuku area of Tokyo, the most urbanized area in Japan (Figure 7). The positioning results and skyplot are shown in Figure 8 and the right of Figure 5, respectively. Table 3 compares the results of the two methods using the three constellation configurations.
Figure 7. Deep urban canyon environment, Shinjuku, Tokyo. (Courtesy Google Earth)Figure 8. Positioning results of the proposed 3D map method using different combinations of satellite constellations in a deep urban canyon.Table 3. Performance comparison of RTKLIB SPP and the proposed 3D map method using different combinations of satellite constellations in a deep urban canyon.
As shown in the left of Figure 8, only half of the GPS-only solutions are on the correct side of the street. A few points are incorrect due to the insufficient number of satellites. Adding GLONASS measurements greatly increases the availability, and most of the GPS-only outliers are corrected. The positioning error mean improves from 12.7 to 10.3 meters, and the availability improves from 53.2 to 75.9 percent. GLONASS measurements provide such a significant improvement because the distribution of GPS and GLONASS satellites are complementary.
After adding the QZSS measurements, availability further increases to 88.6 percent, and positioning error mean is reduced to 5.7 meters. The positioning error mean could be further improved to 4.2 meters if selecting the position points with URA3Dmap ≤ 3: the red, orange and yellow points in Figure 8. Although this selection will lose about 12 percent of availability, it could be easily compensated by a simple filtering technique.
Comparing Table 2 and Table 3, we find the positioning error of the proposed method in the middle urban canyon is about 1 meter worse than that in the deep urban canyon. This is because of the increase of multiple reflected signals.
The target application of this 3D map method is consumer-based pedestrian navigation. Most of these applications benefit from an integrated system of multiple sensors. The 3D map method could serve as one sensor for such an integrated system. The calculation of positioning accuracy is required to indicate the quality of the point solution estimated by this method. Figure 9 shows the relationship between the calculated accuracy and positioning error. We can find that the calculated accuracy is able to describe the performance of the proposed method.
Figure 9. Positioning error of the 3D map method using GPS+GLONASS+QZSS. The purple line denotes the calculated 68 percent accuracy of the proposed method.
The performance of the conventional method is very inaccurate in this deep urban canyon. Its positioning error is larger than 40 meters. Figure 10 shows the number of satellites in this data. Note the number of LOS satellites is determined by the ray-tracing simulation according to the ground truth trajectory.
Figure 10. Number of LOS satellites, the number of satellites used in the 3D map method, and the total number of satellites tracked by the commercial-grade receiver.
The number of LOS satellites means the light-of-sight path of satellite is not blocked by buildings. Note that the LOS signal also contains the multipath effect. In this deep urban canyon, the number of LOS signals is much less than that of all received satellites. This implies a lot of NLOS is received, which deteriorates the performance of the conventional method. The map-based method is able to correct most of the NLOS signals.
The number of satellites used in the map-based method is close to the number of all the satellites received. Therefore the map-based method can achieve better performance than the conventional method. Figure 11 demonstrates the comparison between the map-based method and the commercial GNSS receiver. The map-based method is simply smoothed by a moving average filter with 3 seconds data. It is difficult to understand the pedestrian trajectory by the commercial-grade receiver result. In some cases, the commercial receiver will estimate the pedestrian to be on the wrong side of the streets. The proposed method, instead, is capable of estimating the result at the correct side of the street.
Figure 11. Positioning results of the proposed 3D map method and commercial-grade receiver using GPS+GLONASS+QZSS in the deep urban canyon.
Li-Ta Hsu is a post-doctoral researcher at the Institute of Industrial Science of the University of Tokyo. He received his Ph.D. degree in aeronautics and astronautics from National Cheng Kung University, Taiwan.
Shunsuke Miura received an M.S. degree in information science from the University of Tokyo in 2013.
Shunsuke Kamijo received a Ph.D. in information engineering from the University of Tokyo, where he is now an associate professor.
From our July issue comes this showcase featuring products for surveyors, geographic information systems (GIS) professionals, field workers, and anyone who is looking to expand the capabilities of their smartphone or tablet.
Dedicated Survey/Geospatial
Three-Accuracy Series
The LT500 series of handheld GPS receivers, LT500H/T/N, covers three accuracy ranges from sub-meter to centimeter. It is a cost-effective full GNSS positioning solution for survey, construction and GIS professionals.
Powered by the Windows Embedded Handheld 6.5 operating system, the LT500 is accurate, rugged and versatile. User productivity is enhanced with the built-in gyroscope, an innovative laser plummet for positioning the accurate handheld receiver over a point, an E-compass for showing the direction and G-sensors for leveling. The LT500 series comes bundled with software including SurvCE, DigiTerra and MapCloud. The LT500H has120 channels (GPS L1/L2/L2C, GLONASS G1, G2, BeiDou B1 and Galileo E1), the LT500T has 220 channels (L1, G1, B1), and the LT500N has 12 channels (L1).
The all-in-one TRIUMPH-LS by JAVAD GNSS combines a high-performance 864-channel GNSS receiver, all-frequency GNSS antenna, and a modern featured handheld. The 864 all-in-view channels include Galileo E1/E5A/E5B, GPS L1/L2/L5, GLONASS L1/L2/L3, QZSS L1/L2/L5, BeiDou B1/B2 and SBAS L1/L5.
More than 100 channels are dedicated to continuous interference monitoring, allowing safe GNSS operation in a city, airport and military environment.
The GEOmeter MX system is designed to gather GIS information in heavily wooded areas, with object description, area coordinates and measurement time grasped automatically. The system consists of the GEOsat MXbox receiver, a combination antenna, a PDA such as the Trimble Recon or the Handheld Nautiz X8, and GEOfield software for mobile GIS.
The Mxbox receiver is a Hemisphere multi-constellation GNSS OEM board with GPS, GLONASS, BeiDou, Galileo and QZSS, plus code- and carrier-phase tracking for increased positioning accuracy and availability. The GEOfield software offers reliabe recording, representation and processing of geodata. Measurement quality is indicated in the field with statistics and graphics, in either German or English.
The Matchstiq S10 is a software-defined radio (SDR) platform. It provides increased RF flexibility, RF performance and signal processing capacity in a small package. The Matchstiq S10 platform combines the Epiq Solutions’ Sidekiq SDR with a quad-core processor system running Linux. The Sidekiq MiniPCIe SDR card provides an independently tunable RF transmitter and receiver covering 70 Mhz to 6 Ghz with an RF bandwidth up to 50 Mhz, plus FPGA. The Matchstiq S10 platform also integrates GPS, Gigabit ethernet (with PoE), USB 2.0 OTG, HDMI and real-time clock in a very small form factor package.
Leica Captivate software provides a 3D view for the Leica Viva GNSS, merging the overlay of measured points, 3D models and point clouds into a single view.
Using Leica Captivate, users can capture and manage complex data with the touchscreen on both the Leica CS20 handheld controller and the CS35 tablet.
The CS20 runs on Windows EC7 and is IP68 and MIL-STD-810F rated. It has a 5-inch WVGA color touchscreen that allows for comfortable and quick data processing and a fully integrated radio and antenna for long range robotic total station control. The CS35’s 10.1-inch screen is visible in all conditions. It runs on Windows 8.1 Pro, enabling workers to take their office into the field. It is IP65 and MIL-STD-810G rated.
The FOIF F55 series GIS handheld comes in two models: F55-A and F55-B. The onboard software FOIF SuperGiS allows users to conduct field mapping with powerful functions for data collecting, data editing and data querying.
The F55 measures 234 x 99 x 56 mm and weighs 895 grams. It has an IP65 rating for water and dust protection. The F55-A supports four GNSS (GPS, GLONASS, Galileo and Beidou) as well as SBAS, and can search for up to 120 channels. The F55-B supports GPS and SBAS and provides 12 channels.
With Differential GPS, the F55-A has an accuracy of 0.4 meters, and the F55-B has an accuracy of 0.5 meters. RTK surveying on the F55-A obtains high precision of 1 cm + 1 ppm. Real-time correction service and post-processing are available.
The geoDVR Gen2 is an advanced multi-channel high-definition/standard-definition geospatial digital video recorder designed for aerial and mobile environments.
Unlike a DVR, the rugged geoDVR permanently embeds videos with important GPS location, time and other data — the GPS metadata remains intact even when a video is edited. Most video cameras and gyro-stabilized gimbals can be connected to the geoDVR for recording of HD or geospatial video files.
Video files created by the geoDVR can be analyzed in the RemoteGeo LineVision suite of mapping applications, including tools for Google Earth, Esri ArcGIS, PLS-CADD and the LineVision Cloud. The administrative dashboard allows for monitoring up to four video streams in real-time.
The G1-m1 receiver is part of the G1 family of products from Geomatics USA. The G1 system is scalable from a single-frequency semi-mobile receiver — for control networks and some semi-kinematic mapping applications — to a dual-frequency network RTK solution. It was designed to be lightweight, accurate and portable, especially suited to building a system for travel; for example, all the G1-m1 components, including tripod, will easily pack into a baseball-style bag for transport. The G1-m1 offers centimeter and sub-foot accuracy (centimeter-level accuracy is possible for OPUS-compliant static sessions).
The Panasonic Toughpad FZ-M1 is a thin, light and rugged 7-inch Windows tablet with dedicated GPS — the u-blox Neo M8 series — as an option. The FZ-M1 is built to enable mission-critical mobile worker productivity. Powered by Windows 8.1 Pro and a choice of two Intel processors, it features a long life, user-replaceable battery and a daylight-readable, high-sensitivity multi touchscreen for use with heavy gloves. With a broad range of configuration options, the customizable Toughpad FZ-M1 is rated MIL-STD-810G and IP65, resistant to five-foot drops, weather, dust and water.
Trimble’s RTX technology-based correction services — Trimble CenterPoint RTX, Trimble RangePoint RTX and the new Trimble ViewPoint RTX — are now available on Trimble Geo 7X handhelds.
Trimble RTX technology provides compatible GNSS receivers with correction services that significantly improve accuracy and reliability in obtaining positions worldwide. Operational efficiency and productivity in the field is improved by delivering real-time DGNSS corrections directly to the Trimble Geo 7X handheld.
The handheld solution is designed for industries such as utility companies, municipalities and environmental management agencies, in which workers are highly mobile and require a reliable, flexible data-collection and asset management solution.
A choice of RTX correction services ranging from 4 centimeters to submeter-level horizontal accuracies is available.
The Spike device and Spike mobile app allow users to measure an object by capturing a photo from a smartphone or tablet. From the photo, users can capture real-time measurements, including height, width, area, length and target location. Location data includes latitude, longitude and altitude. Spike is useful for construction, inspection, safety, advertising, real estate, insurance and government applications.
Measurements and location data are saved with the picture and can be shared via email as a PDF, XML and KMZ. KMZ files can be imported into GIS tools such as ArcGIS and Google Earth. The photo can be referenced via the Spike app to take new measurements or view original measurements.
The Spike device pairs with an Android or Apple iOS smartphone or tablet via Bluetooth. Its laser rangefinder works with a smartphone’s camera, GPS, compass and Internet connection.
The iSXBlue II+ GNSS is a palm-sized receiver that delivers real-time, high-accuracy performance using GPS+GLONASS satellites and free SBAS corrections for an iPad or iPhone. Its battery-powered lightweight design is for a variety of mapping applications including GIS, forestry, mining, utilities, agriculture, surveying and environmental. It delivers high accuracy in real time without the need for post-processing or another correction source when SBAS (WAAS, EGNOS, MSAS or GAGAN) are available. Using both GPS and GLONASS satellites, the iSXBlue II+ GNSS will work where GPS receivers struggle, such as in the forest, around buildings and in other difficult mapping environments. The L1/G1, GPS+GLONASS receiver has 372 channels.
TerraGo Edge allows organizations to collect data and share field information on their smartphones and tablets. TerraGo Edge replaces traditional GPS handheld devices with a mobile cloud-based solution. Users can collect GPS data points at any accuracy level, either by using the onboard GPS on a smartphone or by attaching a centimeter-level GPS receiver to a mobile device.
TerraGo Edge 3.6 features enhanced support for high-accuracy GPS receivers such as EOS and SXBlue on both iOS and Android, as well as better mapping features, basemap sources and integration with Google Earth.
For managers, TerraGo Edge provides a real-time dashboard for monitoring field users and data collection.
MachineryGuide enables a tablet or smartphone to be used as a precision tractor GPS system. The MachineryGuide Android guidance program functions as a precision farming application using an antenna capable of receiving and processing EGNOS and WAAS corrections. It can be used for any farming activity that is done by tractor or other agricultural machinery, including fertilization, manure application and spraying. It even can be used for land measurements.
MachineryGuide sells the software separately; a GNSS receiver + antenna separately; and a package bundle that includes software, GNSS receiver and antenna. The receiver uses GPS, GLONASS, SBAS and QZSS signals for a position accuracy of 2.5 meters CEP.
The TomTom Bandit Action Camera allows creation of videos within moments of the action. It comes with a built-in media server, eliminating the need to download footage before editing. The camera works with a companion app, making it possible to create and share videos in a matter of minutes — by shaking a smartphone.
The TomTom Bandit Action Camera is equipped with in-camera motion and GPS sensors to automatically find and tag footage based on speed, altitude, G-force, acceleration and heart rate. Highlights can also be tagged manually with a tagging button on the camera or the remote control.
The Forerunner 225 integrates optical heart-rate technology by Mio and features a colorful graphic interface showing runners their zone and beats per minute at a glance. A built-in accelerometer provides distance and pace data for indoor running with no need for a separate foot pod. To keep runners active between workouts, it doubles as an activity tracker, counting steps, calories and distance.
When paired with a compatible smartphone, the Forerunner 225 will automatically upload a completed run to the Garmin Connect Mobile app for post-run analysis and sharing on social media sites. Runners can also use live tracking to allow friends and family to follow along during training or on race day to see stats in real time.
The Garmin dezlCam trucking navigator has a built-in dash cam.
Garmin International Inc. is offering dēzlCam, an all-in-one trucking navigator with a built-in dash cam that serves as an onboard eyewitness. Truckers can rely on firsthand video footage that continually records the drive and automatically saves video footage on impact.
The dēzlCam provides custom truck routingfor the size and weight of a driver’s truck as well as route warnings for bridge heights, weight limits, sharp curves, steep grades and more.
“The dēzlCam is an innovative navigation solution for truckers,” said Dan Bartel, Garmin vice president of worldwide sales. “As technology evolves, so do the needs of truck drivers who spend their lives on the road. Truckers will like dēzlCam especially because of its premium trucking features combined with an integrated dash cam that records proof of road incidents and protects their driving reputation. The combination of these features adds significant value to our trucking community.”
This premium truck navigator features a six-inch pinch-to-zoom display, a built-in dash cam with an adjustable swivel lens, and a magnetic mount to quickly secure or remove the dēzlCam from a driver’s truck. The built-in dash cam starts recording as soon as the dēzlCam is powered on, while the Incident Detection (G-sensor) automatically saves footage of collisions upon impact.
Location, speed, date and time data can be optionally recorded allowing drivers to know precisely when and where an incident occurred. The Snapshot feature captures still images and provides truckers the freedom to remove the dēzlCam from their truck to take close-up pictures. Users can also play back driving footage directly on the device, or review on a computer using garmin.com/dashcamplayer.
A comprehensive directory of preloaded TruckDownLocations and Services make it easy to find places highly rated by truckers. Drivers can filter trucking points of interest to find locations with their preferred brands or amenities.
The dēzlCam is also bundled with Foursquare data that adds millions of new and popular points of interest to the navigator’s searchable database. Easy Route Shaping lets drivers modify a route to include preferred cities or roads by touching the screen. The Up Ahead feature displays a constant stream of nearby services, such as upcoming rest areas, fuel stations and restaurants.
The dēzlCam also provides a history log to record fuel usage, IFTA mileage and hours of service, and displays mile-marker information, automatic time zone changes and alerts drivers of upcoming state and country borders.
Created with safety in mind, the dēzlCam offers advanced navigation features that aid truckers in reaching their desired destination. Voice-activated navigation lets truckers control the dēzlCam with their voice, while Bluetooth technology allows for hands-free calling and pairing with a Bluetooth-enabled headset (sold separately). The dēzlCam is also compatible with the Garmin BC 30 Wireless Backup Camera (sold separately) to easily see behind a truck when in reverse. Spoken Garmin Real Directions can help drivers locate hard-to-find addresses with spoken directions that use recognizable landmarks, buildings and traffic lights. Active Lane Guidance with helpful voice prompts indicates the proper lane needed for a trucker’s route, while realistic Junction View imagery helps navigate complex interchanges with ease.
The dēzlCam comes equipped with preloaded maps of North America with free lifetime map updates, as well as free HD Digital traffic that provides updates as often as every 30 seconds. Drivers can also download the free Smartphone Link app to access live weather radar on the dēzlCam and other real-time data services from a compatible iPhone or Android™ smartphone.
The Garmin dēzlCam is expected to be available this month with a suggested retail price of $499.99.
