Trimble introduced today several new features to further enhance its Connected Farm solution. Connected Farm is an integrated operations management solution that provides information exchange across the entire farm. New features include additional viewing capabilities between vehicles operating in the same field, and reports on the productivity and delay of field equipment.
Trimble’s Connected Farm vehicle-to-vehicle communication allows real-time wireless data transmission between multiple vehicles and mixed fleets operating in the same field. The new features allow operators to:
View virtual tank levels of nearby devices that are planting or applying product, allowing applicators to coordinate seed and chemical refill.
Share instant yield, instant moisture, and combined coverage layers for yield and moisture with different displays that are in the same field.
Share “as-applied” coverage layers between displays for vehicles conducting the same operation with the same material.
View coverage data from multiple vehicles in the same field that are performing different operations without affecting row shutoff. For example, when tilling and planting simultaneously, operators can assess which areas have been covered by the other vehicle.
View a combined coverage map with a legend of multiple vehicles in the same field to quickly pinpoint each vehicle’s covered area.
Trimble’s Connected Farm solution provides a Web-based application for managing fleets including real-time vehicle position and a cab dashboard showing valuable engine information. New, expanded features of the solution give managers the ability to analyze the efficiency and productivity of their fleet by providing reports that detail total time spent idling, traveling, speeding, moving, working and delayed. When used with a Trimble FmX integrated display, operators will be prompted to select a “Delay Reason” when they stop working. These reasons are available in reports using the Connected Farm Web application to assess the productivity of fleet operations.
“These new Connected Farm features are designed to help customers save time and make better decisions about the management of their farms,” said Ian Harley, business area director for Trimble’s Agriculture Division. “By providing farmers with access to information where and when they need it, and by providing the right type of information, farmers can more easily determine how best to increase the productivity and efficiency of their fleet and farm operations.”
The new Connected Farm features are expected to be available in December.
Symmetricom, Inc., today launched a new small cells-focused category within its SyncWorld Ecosystem Program. Developed to support the integration with Symmetricom’s SCr/SCe NTP/ PTP and sGPS SoftClocks and interoperability between Symmetricom Grandmaster clocks and other small cells solutions, the category aims to facilitate validated deployments of timing and synchronization with various small cells products in 3G and 4G/LTE architectures. Current partners in the program include leading small cell players Alcatel-Lucent, Broadcom, Cavium, Contela, CS Corporation, Mindspeed, Node-H, Qualcomm Atheros, and Rakon.
Small cells are a key component of 3G and 4G architectures as they add capacity to the mobile network and allow service providers the maximum leverage of scarce spectrum resources. Successful HetNet deployments require small cells to synchronize seamlessly with the macro base stations irrespective of backhaul type. Also, small cell design cycles need to be short to meet the fast evolving market needs. SyncWorld brings together all players in the ecosystem including semiconductors, oscillators, software, test equipment and system vendors to drive cost effective and shortened design cycles by enabling architectural harmony and interoperability.
Analyst firm Infonetics forecasts the global small cell market to grow to $2.1 billion in 2016 as small cells have emerged as a key solution to deliver increased network capacity. Symmetricom has delivered a number of solutions with partners along with the introduction of the industry’s first small cell synchronization solution, SCr/SCe NTP/ PTP and sGPS SoftClocks for residential and enterprise small cells. The small cells segment within the SyncWorld Ecosystem Program will ensure that interoperability needs are met as service providers accelerate their deployment plans.
“The small cells category represents leaders across the entire value chain,” said Manish Gupta, vice president of marketing and business development for Symmetricom. “Working together, SyncWorld small cell members will be able to give service providers a comprehensive, integrated and simplified solution that is interoperable and supports the specifications required to support 4G/LTE networks.”
The SyncWorld Ecosystem Program enables vendors to cooperate with the goal of providing complete solutions that interoperate with the most recognized timing and synchronization solution provider in the industry. Vendors that produce silicon, small cell access point, software and oscillators are invited to apply for the program online.
With solutions deployed globally in more than 150 networks, Symmetricom is committed to partnering with trusted end-to-end technology providers which deploy and maintain networks on behalf of operators.
earthmine, Inc., announced today that it is has entered into an agreement to be acquired by Nokia. earthmine, based in Berkeley, California, is a privately owned company that develops a powerful end-to-end 3D street level imaging solution — from collection hardware to processing workflows, cloud hosting and client software.
The earthmine team is expected to join the Nokia location and commerce business, and Berkeley will become a key site for the development of 3D reality capture technology. “We are very excited to be joining Nokia, a company with a huge presence and vision in mapping,” said John Ristevski, co-CEO of earthmine Inc. “We could not hope for a better place to fulfill and accelerate our mission of indexing the world in 3D.”
The transaction is expected to close by the end of 2012. The terms of the transaction are confidential.
earthmine, Inc., provides 3D street-level imagery, delivering an end-to-end solution including 3D mobile mapping systems, automated data-processing pipelines, cloud-based hosting services and server software, desktop software, client-side developer tools, and direct integration with GIS software. earthmine technology is being used in local search, mobile, mapping, GIS, safety, and security markets in the United States, Mexico, Brazil, Canada, France, Australia, Japan, Malaysia, Singapore, Korea, Saudi Arabia, as well as other countries around the world.
The month of October and now into November was filled with several conferences, but not a lot of location news. A few news snippets, while not blockbusters, were important. One was Waze’s decision to offer its own location-based advertising. Another was a milestone for Ford, which said its Sync information system is now in five million vehicles. On an end-of-an-era note, of which there have been quite a few in the last two years, Sprint has decided to drop the Nextel name. Nextel was one of the innovative companies in the late 1990s and early 2000s, placing location capability into mobile phones and jump-starting an industry.
Waze recently said it is offering a global location-based advertising platform that will be directed to its 30 million users. Waze, founded in 2009 in Israel, says smartphone users can try the service for free — the profit for them is ad revenue from local and large brands.
GPS World’s LBS Insider recently reported that Tim Cook, Apple’s chief executive, actually endorsed Waze as an alternative to its own mapping service after users were experiencing problems with it. Waze, which is offering the advertisements in the United States, said it saw a jump in downloads after the announcement.
Some industry analysts say it may be a mistake for Waze to swim in the deep end of the pool to compete with such mobile advertising giants as Google.
Waze raised a total of $67 million from investor Kleiner Perkins and Hong Kong investor Li Ka-shing. They cite big partners such as Circle K, Dunkin’ Donuts, MACS, Kum & Go, Wyndham Hotels, Jamba Juice, and P&G.
Palo Alto-based Waze is probably best known for its driving directions based on user input. The company says that its users spend an average of more than 7 hours in their vehicles a month.
The company, in order not to annoy users, is minimizing the number of pins on a map advertisement. According to published reports, the company said its advertisements will include coupons.
From the Waze blog: “We don’t want to bombard you, so you’ll never see too many businesses crowded on the map at once. Instead, the algorithm that powers Waze Ads aims to bring you a helpful selection of the various retailers around you on your daily drive.”
Waze is also making advertising inroads in Europe. It recently announced a partnership with Lumata, an Italy-based mobile marketing company. The deal allows Lumata to have a an exclusive right for advertising on Waze’s app in Italy, according to published reports.
Waze announced in June that car models will soon integrate the company’s mapping software. The company’s iOS and Android app’s users contribute road data while they drive, share accident reports, police speed traps, traffic jams and other data.
Five Million Sync Units in Five Years…
Ford and Microsoft’s Sync infotainment system has been installed in five million Ford and Lincoln vehicles. The unit, which was rolled out at the 2007 Consumer Electronics Show in Las Vegas, was one of the first products to allow smartphones to work with car components.
Sync was innovative in that it bundled turn-by-turn navigation, hands-free calling, text message reading, and other features. Earlier aftermarket products, such as Clarion’s AutoPC, were busts — but perhaps five-to-seven years too early for the market.
Ford jazzed up Sync with touchscreens and voice recognition since it rolled out its first model, which only used push buttons. It integrated other features such as audio, air conditioning/climate control, and navigation. Soon the newer version, MyFord Touch, offered video streaming, music, and a voice-activated climate control system.
Ford announced earlier this year that it was working with State Farm to add all Sync-equipped vehicles to the insurance giant’s Drive Safe & Save approved vehicles. A customer, through a voluntary sign up, can run a Vehicle Health Report that sends information to State Farm. Potential insurance savings for a customer could be 40 percent.
Ford is working with several industry companies, including Pandora and TeleNav Scout, through its AppLink program, which was globally offered earlier this year.
In other LBS news:
Sprint’s recent decision to drop the Nextel name was the end of an era, but not a surprise. It was Nextel, before its 2005 merger with Sprint, that truly innovated consumer and enterprise applications and markets on the mobile handset. In the wake of Japan’s Softbank purchase of 70 percent of Sprint, the Nextel part of the Sprint name will go away in mid-2013. The new name will be Sprint Corp. The Nextel brand was known for its iDEN technology and network, which is gradually being shut down by Sprint.
The recent U.S. presidential election had an LBS story. Foursquare had an app that had the goal of encouraging users to vote. The “I Voted” app allowed users to find their local polling station on Election Day and check in to show they cast a vote. Foursquare, trying to show that it offers more than “check-in” capability, recently announced a rating system for businesses. It is not clear whether the service, with 25 million users, is going after companies such as TripAdvisor and Yelp for a share of the evaluation/services market.
Samsung Electronics’ Galaxy S III managed to knock Apple’s iPhone 4S off the pedestal as the world’s most popular smartphone, in terms of sales, in the third quarter, said Strategy Analytics. Samsung sold around 18 million S III phones during the quarter, compared to Apple’s 16.2 million iPhone 4S units. The Galaxy S features a large touchscreen and GPS for location-based services.
A new report from Juniper Research has found that with brands and retailers increasingly keen to deploy augmented reality (AR) capabilities within their apps and marketing materials, AR applications will generate close to $300 million in revenues globally in 2013.
The report found that while the traditional pay-per-download payment model would continue to account for the largest share of revenues in the medium term, the scale of retailer engagement with AR suggested that ad spend had upscaled dramatically in 2012 and was poised for further strong growth next year.
Crucially, it also found that many retailers now perceived AR as a key means of increasing engagement with consumers, both as a means of providing additional product information or in the form of branded virtual games and activities.
Consumer Expectations Not Yet Met. The report cautioned that while lack of consumer awareness of AR remained a key hurdle which needed to be overcome, it was by no means the only barrier to growth. It argued that technological limitations of AR-enablers such as the phone camera, GPS, digital compasses and marker-less tracking meant that in many cases, the AR experience was failing to live up to consumer expectations.
The report claimed that even some higher-end smartphone cameras lacked sufficient sensitivity to trigger an AR experience unless light conditions were optimal. Furthermore, the need to recalibrate digital compasses — allied to poor in-building functionality of GPS – means that under certain circumstances the level of location accuracy would not be sufficient for many potential corporate applications. As a result, the report stated that enterprise adoption would be limited in the medium term.
Other key findings from the report include:
More than 2.5 billion AR apps to be downloaded to smartphones and tablets each year by 2017, with games accounting for the largest share of downloads.
AR is increasingly being deployed in prototype wearable devices, with Google Glass the most high-profile innovation.
Topcon Positioning Systems has launched the second annual “How do you Topcon?” video contest with the slogan, “However and whenever you Topcon, we want to see it!”
The contest includes four categories:
Most innovative or creative use of Topcon equipment;
Funniest video or infomercial;
Best testimonial or “on-the-job” story;
The “wow” Factor.
The contest will run through December 15, 2012.
Participants will upload a short video (maximum length of three minutes) showing how they use Topcon products and services. Any use of Topcon equipment across all business segments — construction, survey, emerging business and agriculture — will be eligible. Prizes for the contest range from a preselected Topcon product, iPad or gift cards from $50 to $750.
“We want to engage our customers in a fun way through a social media forum and are finding that the video contest, and the recent ‘Topcon is Everywhere’ and ‘Spirit of Agriculture’ photo contests are excellent ways for everyone to get involved, from first-time-users of Topcon equipment to those who rely on it heavily for extensive projects,” Scott Langbein, director of product marketing said.
Esri has released ArcGIS for Windows Mobile 3.1, coinciding with the release of Trimble Positions field collection software. The Trimble Positions software suite extends the ArcGIS for Windows Mobile application and software developer kit (SDK) with support for high-accuracy GNSS mobile GIS data collection.
The Trimble Positions software suite is designed for users who require high-accuracy data collection workflows using Esri’s ArcGIS for Windows Mobile technology. The latest version of ArcGIS for Windows Mobile, combined with Trimble Positions software, simplifies field collection activities and requires little to no GNSS or GIS data collection experience, Esri said. ArcGIS for Windows Mobile and Trimble Positions support both real-time and postprocessing workflows, streamlining the process of collecting GPS data.
With ArcGIS for Windows Mobile, data collected with Trimble Positions can be automatically synced to an enterprise server when Trimble Positions Desktop is used to manage data from incoming field crews. Office administrators can easily check for new sessions, differentially correct the data, and verify that it meets accuracy requirements before updating the enterprise database at the touch of a button, Esri said.
Trimble has expanded coverage of its satellite-delivered Trimble RTX technology for surveyors to most of the world. Trimble has also introduced post-processing capability for its CenterPoint RTX positioning service for farmers. Both announcements were made at the Trimble Dimensions 2012 conference being held in Las Vegas this week.
RTX technology enables Trimble xFill, a new technique in RTK and VRS surveying that allows surveyors to continue working in the event the primary RTK or VRS correction stream is not available.
Trimble RTX technology, first introduced in 2011, combines real-time data and positioning algorithms to deliver centimeter accuracy around the world. While RTX technology is available worldwide via IP and cellular delivery methods, Trimble RTX has been available via satellite L-Band only in North and South America. Now, the expanded satellite coverage includes most of Europe, Russia, and the Commonwealth of Independent States (CIS), Africa, Asia, and Australasia.
Powered by Trimble RTX technology, Trimble xFill, a feature integrated into the new Trimble R10 GNSS Receiver, enables a new and innovative technique in RTK surveying, according to Trimble. It seamlessly “fills in” for RTK or VRS corrections for up to five minutes in the event of a temporary connection outage with the primary correction source. Minimizing downtime, Trimble xFill enables higher productivity for field survey crews, allowing them to continue working until radio or cellular connectivity is restored, Trimble said.
“The expanded coverage of satellite-delivered Trimble RTX technology further extends our commitment to providing different ways of realizing high accuracy positioning solutions,” said Patricia Boothe, general manager of Trimble’s Positioning Services Division. “The power of RTX is proven. Trimble RTX is the backbone of Trimble’s latest positioning innovations including the Trimble CenterPoint RTX service for farmers, the Trimble Pivot RTX App, and Trimble Pivot RTX-PP App infrastructure solutions and now, the Trimble xFill feature for surveyors.”
Trimble xFill feature allows satellite corrections to be delivered directly to the receiver with no need for additional equipment such as radios and antennas. With its built-in capability, the Trimble R10 automatically tracks these corrections and will use them when needed. Trimble xFill across the expanded satellite coverage area is expected to be available by late November 2012.
CenterPoint RTX Positioning Services. Enabled by Trimble RTX technology, CenterPoint RTX provides centimeter level positions in real time via satellite L-band and IP/cellular. The new post-processing capability delivers better than one-centimeter accuracy and is available worldwide.
Trimble CenterPoint RTX post-processing is a cloud-based service accessed through www.TrimbleRTX.com, allowing users around the globe to upload static GNSS observation data and receive positioning corrections calculated in the well-defined ITRF 2008 reference frame. The post-processed solution can be transformed to a variety of regional reference frames by selecting a coordinate system and tectonic plate.
“With the introduction of post-processing capability to the CenterPoint RTX portfolio, we continue to extend the breadth of the service,” said Patricia Boothe, general manager of Trimble’s Positioning Services Division. “CenterPoint RTX post-processing gives geospatial professionals another tool for their toolbox, utilizing Trimble’s globally available RTX technology to enable higher-accuracy positioning solutions.”
The open service allows any user to post process 10 data sessions per month.
Washington, D.C. — The Federal Communications Commission’s Enforcement Bureau today launched a dedicated jammer tip line – 1-855-55-NOJAM (or 1-855-556-6526) – to make it easier for the public to report the use or sale of illegal GPS, cell phone or other signal jammers. It is against the law for consumers to use, import, advertise, sell or ship a GPS or cell jammer or any other type of device that blocks, jams or interferes with authorized communications, whether on private or public property.
The FCC asks people to call the toll-free Jammer Tip Line immediately if:
you are aware of the ongoing use of a cell, GPS, or other signal jammer;
your employer operates a jammer in your workplace;
you observe a jammer in operation at your school or college;
you observe an advertisement for a jammer at a local store; or
you observe a jammer being operated on your local bus, train or other mass transit system.
“We need consumers to be our eyes and ears. Jammers do not just weed out noisy or annoying conversations and disable unwanted GPS tracking, they can prevent 9-1-1 and other emergency phone calls from getting through in a time of need,” Michele Ellison, chief of the Enforcement Bureau, said.
Calls to the Jammer Tip Line will be handled by experienced Enforcement Bureau staff. Callers are encouraged to provide as much detail as possible, including the time and location of the incident, a description of the jamming device (if available), and the name and contact information of the individual or business using or selling the device.
While callers may remain anonymous, the bureau urges callers to provide a contact phone number in case additional information is needed. “Every tip can make a difference,” Ellison said. “While our agents are actively pursuing these violations online and on the street, you can help. We encourage concerned parents, commuters, employees, and anyone else with credible information to tip us off. Working together, we can stop the spread of illegal jammers.
For more information, Frequently Asked Questions about cell, GPS, and Wi-Fi jammers are available at www.fcc.gov/jammers, or email [email protected].
By J. Blake Bullock, Mahesh Chowdhary, Dimitri Rubin, Donald Leimer, Greg Turetzky, and Murray Jarvis
A new chip fuses input from several sensors, using the best combination at any given time to maximize coverage and accuracy while keeping power draw to a minimum. This produces continuous position availability in indoor environments, as demonstrated by performance measurements in real-world test environments.
Users of GPS receivers in smartphones and many other consumer electronic devices expect these devices to work in all environments, including dense urban canyons, parking garages, and indoors, enabling a wide range of location-based services such as mapping, search, tracking, and navigation. Recent advancements in assisted-GPS (A-GPS) technology have enabled improved positioning indoors, but GPS receivers are still not sensitive enough to determine position everywhere that users go.
Several consumer products now use GLONASS and assisted-GLONASS (A-GLONASS) measurements to improve coverage and accuracy of GPS receivers. We refer to such combo receivers as GNSS receivers here. GLONASS measurements have similar characteristics to GPS measurements in that they are subject to blockage and multipath. In dense urban canyons, GLONASS measurements help to improve availability and accuracy of a position solution. However,GLONASS provides little performance improvement indoors.
Various emerging technologies for indoor positioning use installed wireless transmitters as beacons for making measurements for positioning. Existing Wi-Fi access points (APs) can be used in this way to determine position when indoors. Other solutions include the emerging Bluetooth Smart transmitters, GSM, 3G, and other mobile phone transmitters, the NextNav network, and other dedicated beacons for indoor positioning. Each technology has advantages and disadvantages for use as an indoor solution, to be discussed here.
The SiRFstarV location chip with SiRFusion combines A-GPS and A-GLONASS advances with Wi-Fi positioning and dead reckoning using low-cost micro-electro-mechanical systems (MEMS) sensors. Smartphones, tablets, cameras, fitness products, and other consumer electronics are equipped with an increasing array of MEMS sensors including accelerometers, magnetometers, gyroscopes, and barometers. The SiRFstarV chip acts as a gateway to receive input from all available MEMS sensors so that the output signals can be combined with the GPS, GLONASS, and Wi-Fi measurements that give absolute position. The observations from all these sources are fused together using a Kalman Filter. Smart location management makes use of the best combination of sensors at any given time to maximize coverage and accuracy while keeping power draw to a minimum. This produces continuous position availability in indoor environments.
Target Performance and Use Cases
The last 10 years have seen great improvements in GPS positioning indoors, primarily driven by the mobile market and the FCC E911 directive to be able to locate mobile-phone users. Today, it is possible to locate a mobile phone indoors using A-GPS, advanced forward link trilateration (AFLT), or Wi-Fi positioning. Typically it takes several seconds to determine a fix indoors, and the accuracy is not as good as outside. It is also not feasible to get continuous position updates for use in tracking, fitness, or navigation systems.
Wi-Fi positioning has improved the availability of fixes indoors and also the time to get a fix. However, today AP positioning is based on surveys that have been done using GPS vehicles outside, so the determined positions tend also to be outside, even when the mobile device is indoors.
To reliably deliver indoor positioning, the positioning system must be able to:
◾ Determine position quickly — within a few seconds.
◾ Determine position accurately — within 5–10 meters, circular error probable (CEP) 50 percent.
◾ Determine position updates at 1 Hz.
◾ Preserve battery life.
Cameras have very different uses than handsets. Typically, a camera is off until the user is ready to take a picture or video. When a picture is taken, theposition can be recorded and used to geotag the image with the location, date, and time. For this use case, the positioning system needs to be able to determine position indoors quickly and with low power, but continuous updates at 1 Hz are not needed.
Fitness products use location for recording distance traveled, speed, elevation, calorie counting, and showing a track of running or cycling workouts. Users value good accuracy and a fast startup time when they are about to begin a workout. The positioning system needs to be able to determine position continuously, but not necessarily show the position updates in real time.
Battery life for a typical assest-tracking device is extremely important, as is the ability to locate the asset in any environment. Continuous position updates are not needed. A typical feature of asset-tracking systems is the ability to set a geofence boundary, used for generating alerts. The positioning system needs to determine position periodically and compare with the geofence. If the position is outside the geofence, an alert is sent to the user.
GNSS Positioning
Positioning algorithms on the SiRFstarV Quad-GNSS combine range measurements from all-in-view GPS, GLONASS, QZSS, and SBAS satellites. The chip is hardware-ready to enable Galileo and Compass measurements with a future software update. Immunity to interference, cross-correlation, and multipath impairments are provided to achieve very high sensitivity, which is critical for indoor positioning. Nevertheless, the utility of reception sensitivities below –165 dBm has been found to have limited value for all but static cases, due to the very long integration times required to make reliable measurements. Increasing the number of independent range measurements helps improve indoor positioning, and using multiple constellations is a key enabler to provide them.
The improvement in indoor positioning by using multiple constellations is similar to the improvement in urban canyon positioning, since the impairments are similar.
One significant difference is that multipath delays for indoor environments are typically much shorter, and conventional mitigation methods cannot be applied without a very wide RF bandwidth. The shorter delays therefore produce lower signal levels due to phase cancellations and pseudorange bias errors, which are recognized as multipath errors and reduced as part of the chip’s measurement processing. While the advantage of augmenting GPS measurements with GLONASS is typically 20 to 40 percent improvement in position accuracy in urban canyon environments, it shrinks to only 7 to 15 percent indoors. Even with GLONASS measurements, the position is frequently shown outside of the building.
Figure 1 shows the results of an indoor walk test with a SiRFstarV receiver using GPS and GLONASS. The test was done on multiple floors of a three-story commercial building. Table 1 shows a summary of the performance metrics as determined by stopping at benchmark locations during the test. Fixes are available nearly 97 percent of the time. The addition of GLONASS tracking increased the average number of satellite measurements from 7.3 to 9.9 and improved the horizontal and vertical accuracy by about 7 to 15 percent. The horizontal accuracy is about 11.5 meters, 50 percent CEP. However, more than half the fixes are shown outside of the building.
Table 1. Impact of GLONASS on indoor positioning.
This test had high availability, but many environments cannot provide GNSS signals with sufficient energy to obtain position fixes. While the use of multiple constellations improves the accuracy and availability of the GNSS fixes, additional position sources are needed to achieve suitable availability and accuracy for continuous indoor positioning.
MEMS Pedestrian Dead Reckoning
Pedestrian dead-reckoning (PDR) logic is realized using integration of MEMS sensors with the SiRFstarV GNSS receiver, which has a dedicated I2C port designed to interface with MEMS sensors. A data-acquisition task collects sensor data and performs low-level error checking, timing synchronization, and buffering of the data from various sensors. This data is sent periodically to the process where a sensor data handler prepares it for further processing.
Acceleration data is processed by the context (or user mode) detection algorithm to determine the dynamic state of the user (or receiver) in order to select appropriate position-determination algorithms and associated motion parameters used by these algorithms. The PDR algorithm is employed when the user mode is classified as walking, fast-walking, jogging, stationary, climbing/descending stairs, elevator, and escalator.
The generalized navigation equation can be written as
(1)
where vne is ground velocity in navigation frame, Cnb is direction cosine matrix relating body reference frame to navigation frame, f b is specific force, ωnenis turn rate of Earth, ωnenis body rate, andgnlis local gravity vector expressed in navigation frame. This equation (in navigation frame) relates the ground speed of an object to measured specific force and measured body rate. The generalized navigation equation, when integrated twice, transforms from the acceleration of the platform into position represented in North and East reference frame, results in Equation 2,
(2)
where, s(t) is displacement and ψ(t) is heading. In the case of pedestrian motion, velocity and heading can be assumed to be constant during the interval when a step is taken. With this assumption, the integral form of Equation 2 can be rewritten as a difference equation with piece-wise linear approximation.
(3)
This equation describes a method of dead reckoning (DR) that is based on step counting rather than integration of acceleration and angular rate. This PDR process consists of three important components: the previously known absolute position of the user at time t-1 (Et-1, Nt-1), the stride length or distance traveled by the user since time t-1 (), and the user’s heading (ψ) since time t-1. The coordinates (Et, Nt) of a new position with respect to a previously known position (Et-1, Nt-1) can be computed as shown in Equation 3. The position initialization of the PDR process can be accomplished using any or a combination of absolute positioning technologies such as GNSS, Wi-Fi, or GSM.
Performance of PDR algorithms is dependent on obtaining calibrated MEMS inertial sensor data continuously. Calibration of sensors is accomplished through collecting and processing sensor data for user motion of device in Earth’s gravity and magnetic field. Accelerometer and gyroscope calibration logic utilize the knowledge of device stationary condition. Magnetic sensor calibration logic requires that various axes of sensor are exposed to Earth’s magnetic field vector at the user location. With the given time and location estimate, the Earth’s magnetic field parameters are computed using the World Magnetic Model. Normal use of a mobile device would result in rotations in various Euler planes thereby applying Earth’s magnetic field to various axes of magnetic sensor. Earth’s magnetic field parameters are also used to detect occurrences of magnetic disturbances. Magnetic sensor measurements are de-weighted for the PDR process during such magnetic disturbances.
The essential logic components that affect the performance of PDR positioning system are: calibration of sensors, step detection, determination of walking direction, positioning fusion logic, and orientation of phone while walking. Typical phone users will have the phone in a pocket, in a belt clip, in a purse or bag, in their hands looking at it, or up to their ear in a conversation. The PDR algorithms need to be able to perform robustly in any of these orientations.
With PDR, an absolute position can be propagated as a user moves on foot. Due to the error growth characteristics of typical MEMS devices used in consumerelectronics, the estimated path deviates from the actual path as a function of distance traveled. The error growth is typically on the order of 10 percent of distance traveled, especially in the presence of magnetic disturbances. This level of error growth makes MEMS PDR unsuitable as the sole positioning solution when indoors. Periodic absolute positioning updates are required to correct the path and to allow additional calibration.
Wi-Fi Positioning
Opportunistic positioning using observed Wi-Fi signals is a well established method of absolute positioning in GNSS-denied environments. Off-the-shelf Wi-Fi access point hardware is not well suited to positioning using timing observations, therefore the chip under discussion uses observed signal strengths together with the broadcast unique identifiers (BSSIDs) as the basis for the Wi-Fi positioning sub-system. Signal strength information is by its nature asymmetric. A strong observation of a Wi-Fi AP indicates that one is near it, but it is not safe to infer from a weak observation that you are far away. This is because weak observations may be due to, for example, occlusion, fading, or antenna orientation. This means that the performance of Wi-Fi positioning varies considerably with location and time, especially in areas with many pedestrians.
There are several limitations to Wi-Fi positioning. The first is that since it is opportunistic, there is no guarantee of performance. Fortunately, AP density is typically highest in the areas where Wi-Fi positioning is most needed, namely, deep indoors and in dense urban areas. Secondly, there is no guarantee that APs will remain in the same locations. APs may be attached to mobile devices, or AP equipment may simply be moved. This leads to a requirement for the database of AP locations to be dynamically monitored and continuously improved. Lastly, the location of the APs is not known a priori, and hence there needs to be some independent means of locating the APs in order for them to be used for positioning. The CSR server implementation uses the other technologies present, namely GNSS and MEMS, to generate this information. This avoids the need to manually survey areas where Wi-Fi positioning coverage is required.
The chip supports Wi-Fi receive (sniffing) and positioning via scanning of the ISM band to detect any broadcast 802.11b Barker codes on any of the 14 channels. This process takes approximately 100 milliseconds/channel, producing a scan time of 300 milliseconds for the three primary channels, or a scan time of 1.4 seconds for a systematic scan of the entire band.
The usual configuration is for the SiRFstarV chip to be connected to the CSR Positioning Center (CPC) server via software running on a host processor in the device. On request, the CPC can then provide the device with all the APs known to be in the vicinity of the user. This data is sent as a sequence of spatially contiguous sets of APs in a tiled structure. The benefit of serving tiles to the user, rather than user’s position or only the APs instantaneously detected, is that the client device can subsequently operate independently with only occasional server contact. In fact, since the chip supports on-board storage of the AP tile information, it can also operate for extended periods without waking up the host, a feature useful for low-power geo-fencing and other location functions.
Another important aspect of the CPC is that is supports crowd-sourced learning of Wi-Fi APs. Client SiRFusion devices submit anonymous sets of Wi-Fi signal strength data and associated BSSIDs, together with contemporaneous GNSS and relative information from the MEMS devices. By collating all the information available in an area across users, the system is able to calculate the most likely locations for Wi-Fi APs and hence generate tiles available to provide to all users. Unlike crowd-sourced systems based on GNSS alone, CSR also uses relative data from MEMS PDR to extend the coverage area of the crowd-sourcing indoors. This produces better Wi-Fi positioning performance indoors.
Sensor Fusion
The GNSS, Wi-Fi, and MEMS PDR solutions offer varying levels of accuracy, coverage, and reliability. CSR has developed SiRFusion, a Kalman filter-based fusion engine in the SiRFstarV device, to combine all these location inputs. Sensor fusion is a critical component and does the job of fusing the multiple sources of position information to provide a single best estimate of position and confidence to the user. It takes as input absolute positions from GNSS and Wi-Fi and also any relative information derived from the MEMS PDR sub-system. Figure 2 illustrates the major components of SiRFusion.
Figure 2. Major components of SiRFusion.
To determine how to weight and smooth the different inputs, it is crucial that the individual input technologies provide reliable estimates of their confidence and correlation. As an example, we mentioned earlier that the quality of Wi-Fi positioning is variable and is best when strong APs are seen. A high quality Wi-Fi position, signified by a high confidence value, will cause the fusion filter to be strongly biased towards this positioning source. When the Wi-Fi position quality subsequently deteriorates, this is reflected in a lower position confidence, and hence the fusion filter down-weights Wi-Fi influence. In turn, this allows dominance of the MEMS PDR input until another sufficiently high-quality absolute position allows the filter to correct. The net effect of this behavior is that the MEMS bridges the position output smoothly between high-quality absolute position fixes and to a first approximation, any low-grade information is ignored. Another benefit is that individual Wi-Fi positions can be jumpy, because on an individual scan there is considerable variation in the audible APs and their signal strengths. Sensor fusion with MEMS PDR helps to smooth this out, providing a continuous trajectory and a more satisfying user experience.
Another job of the fusion engine is to transition smoothly from indoors where Wi-Fi and MEMS PDR dominate, to outdoors where GNSS dominates. This happens automatically in the fusion filter with the GNSS becoming increasingly dominant outdoors as GNSS confidence improves. Conversely, the Wi-Fi position accuracy will typically decrease outdoors and the dominant technology will therefore gradually dominate the solution. When technologies are not being used they can be switched off or placed in a maintenance mode to reduce unnecessary power consumption.
Performance Results
CSR has developed a demo platform with SiRFstarV and SiRFusion in a modified HTC Google Nexus One handset with Android. Figure 3 shows a modulewith the receiver and MEMS devices; the module is mounted inside the HTC phone shown in Figure 4. The data log includes PDR output, Wi-Fi positioning, GNSS positioning, and the combined sensor-fusion solution.
Figure 3. Module with MEMS devices.Figure 4. HTC Google Nexus test phone.
A series of tests were carried out in Tokyo Station in Tokyo, Japan. The tests shown here were all done on the B1F level in the shopping area adjacent to the station. This area is two levels below the tracks and is below ground. There are no windows, and there was no GNSS reception. The environment also has lots of magnetic anomalies due to tracks, trains, elevators, escalators, and many people in motion, which affects Wi-Fi signals. Each plot shows an indoor map superimposed on the Google Earth image of the area. The narrow aisles in the map are about 5 meters wide. The map is used for presenting results only; it was not used to do map-aiding or map-matching.
AP harvesting and learning was done in this area before the tests were conducted. In each test, the phone is turned on, and SiRFusion uses Wi-Fi measurements and data from the AP database to determine the initial position without any assistance from GNSS. In each case, the initial position was determined within 1–3 seconds.
In Figure 5, the route walked is shown by the straight green line, with the start point in the lower left corner. Wi-Fi positioning is shown in red, the yellow isthe MEMS PDR solution, and the blue shows the SiRFusion solution, which in this case is combining Wi-Fi and PDR. The Wi-Fi position is not available every second and at times has discontinuities of several meters. This is due to the signal variability as discussed previously. The PDR solution shows a gradual drift that is more than 25 meters off track in places. This is not an issue for SiRFusion, as only the relative positioning is used from the PDR output. The SiRFusion solution shows a smooth continuous output that has a maximum cross-track error of about 7 meters. Note that the error of the SiRFusion solution does not follow the PDR solution. The absolute positioning provided by the Wi-Fi fixes keeps the solution on track.
Figure 5. Tokyo Station test showing Wi-Fi (red squares), PDR (light green squares), and SiRFusion output (blue); straight green line shows true path followed.
Figure 6 introduces a test with several turns in the corridors. The path walked is marked by the red flags, and took just under six minutes. The fusion solution is shown in blue. The start point was in the lower left. The fusion solution was able to detect each of the turns made while walking. The shape of the path clearly follows the marked path walked. The largest deviation from the path was ~7 meters. Typically, the solution was within 5 meters of the path walked.
Figure 6. Tokyo Station test showing turns; red flgas mark actual path, blue is SiRFusion output.
Figure 7 shows another path through the corridors, this time just over seven minutes in duration. Again, the fusion solution shows each turn correctly and in this case, the maximum cross-track error is about 5 meters. Figure 8 shows the same path, but with the output from three separate walks shown in green. A cold start was done before each walk. The results agree closely, showing high repeatability between test runs.
Figure 7. Tokyo Station test showing turns; legend as per Figure 6.Figure 8. Tokyo Station test repeatability; light green shows three successive SiRFusion test runs.
To obtain a quantitative measure of the performance accuracy, the locations of several points in the Valley Fair Mall in Santa Clara, California, were determined. During several independent test runs in the mall, the tester went to each designated test point and indicated a marker in the log. The measured positions were compared with the determined positions to generate the performance statistics shown in Table 2. The cross-track error was 3.2 meters 50 percent CEP and 13.1 meters 95 percent CEP. These levels agree with the estimated results determined from the maps in the Tokyo tests.
Table 2. Accuracy test, Santa Clara Mall.
These tests show excellent results in availability, accuracy, stability, and repeatability. The availability is near 100 percent, with the only missing fixes being the first couple of seconds on startup. The position accuracy is sufficient to guide a user to the correct storefront, terminal, or track in a complicated indoor environment. The smooth continuous output can be used for voice guidance applications.
Applications
Continuous indoor positioning enables important consumer and commercial applications including indoor search, navigation, social networking, andadvertising on mobile devices, indoor geotagging on camera devices, indoor workout monitoring on fitness devices, and asset tracking.
Mobile Devices. Search, mapping, and navigation are popular uses for smartphones, tablets, and other mobile devices. These services are even more powerful when taken indoors in shopping centers, airports, train stations, and other public places. In a large shopping area, a consumer can search for the nearest store with items of interest and get walking directions to that store. He or she may receive a coupon or ad relevant to the store or item that they searched for. Business owners are interested in targeted mobile ads to help connect with interested shoppers.
Camera Devices. Location capability is emerging on camera devices for geotagging the location where a photo was taken so that it can be embedded with other meta-data in the image file. Geotagged photos can be easily shown on maps, sorted by location, and shared with others. Indoor positioning enables geotags to work inside as well as outside, completing the coverage availability.
Fitness Devices. Fitness watches and other workout tracking products use location to measure distance traveled, calories burned, steps taken, and plot workout tracks on maps. With indoor positioning, indoor workouts can also be included in consumers’ data analysis as they track a wider variety of workout types.
Machine-to-Machine and Asset Tracking. The benefits of indoor location extend the asset-tracking model from fleets of trucks and automobiles to include all types of valuable assets, from children to pets to merchandise and even data. It is valuable to provide an individual with their own location, but it is even more valuable to provide the location of objects that are somewhere else in an M2M application. The low-power, ubiquitous location capability of SiRFstarV and SiRFusion allows very small tags with months of battery life to be attached to virtually any object and in combination with an appropriate communication link (cellular, Wi-Fi or BLE) report that position to the CPC. From there, a cloud-based location service to carriers, retailers, malls, government agencies and others can add location to their product mix. This service can even be extended to provide data security so that sensitive corporate information could only be accessed by devices within an authorized area, and not in a public place such as an airport. By making ubiquitous location information available on almost any imaginable platform, the use cases are nearly limitless.
Conclusion
Sensor fusion algorithms have been developed and refined to address the problem of determining position indoors. Performance testing shows that the position availability approaches 100 percent, and accuracy exceeds 10 meters, 50 percent CEP. The fusion technology is suitable for integrating in a wide range of consumer and commercial devices. The solution uses existing wireless infrastructure and can be deployed around the world with no new equipment to install or surveying to perform. The self-learning capability adapts to changes in the signal environment.
Acknowledgments
Seiji Ishikawa and Shinya Ohno of CSR performed the testing in Tokyo Station and were instrumental in preparation and analysis.
ST Microelectronics provides the MEMS sensors used in much of CSR SiRFusion testing.
J. Blake Bullock was senior product manager responsible for CSR’s next generation of GNSS solutions. He has now transferred to Samsung System LSI Business and is responsible for GNSS and indoor positioning solutions. He holds a M.Sc. degree in geomatics engineering from the University of Calgary, an MBA from Arizona State University, and several patents in LBS and navigation.
Mahesh Chowdhary is senior director MEMS technology at CSR where he works on the integration of GPS, MEMS sensors, and wireless technologies. As founder and CTO of Acculeon, he pioneered the use of GPS and MEMS sensors in vehicle safety applications. He received his Ph.D. in Applied Science from The College of William and Mary, Williamsburg, Virginia.
Dimitri Rubin is senior director at CSR and is responsible for the development of the SiRFusion system. He has worked in the wireless communication field for 24 years.
Don Leimer is managing the GNSS Advanced Development group at CSR. Mr. Leimer has led and contributed to numerous commercial and military GNSS developments including GPS Phase I.
Greg Turetzky is senior director for location and technology strategy in CTO office at CSR. He has an M.S. in computer science from Johns Hopkins and holds a number of patents in GPS.
Murray Jarvis is a consultant research and development engineer at CSR. He holds a Ph.D. in physics and has worked on a variety of positioning technologies including GNSS, cellular and Wi-Fi.
The U.S. Air Force is investing to improve the Global Positioning System (GPS) used worldwide for military and civilian purposes.
Between Sept. 28 and Oct. 1, the Air Force announced four new GPS contracts.
Three were in the $30 million range, including contracts to Rockwell Collins and L-3 Communications to test and engineer new GPS technology, while Raytheon was awarded just under $30 million to develop receiver cards for GPS systems. Honeywell International also received a $14 million contract for engineering services related to GPS.
Maintained by the Air Force, the GPS is used in everything from civilian car navigation to targeting for military weapon systems. The only competition for the American GPS is the Russian GLONASS system, although the European Union is currently developing its own system, nicknamed Galileo.
The contracts were announced days before the Oct. 4 launch that put the first new GPS satellite of 2012 into orbit. That satellite, a Boeing-designed GPS IFF, improves on navigational accuracy, provides a more secure military signal and has a longer design life than older satellite models. It should deploy fully in about three months.
Butler National Corporation, which specializes in the aerospace sector of structural modification, maintenance, repair, and overhaul, announces issuance of the Supplemental Type Certificate (STC) for installation of the new Garmin GTN series of navigators that provide GPS, navigation, and communications. The installation is for GTN 750 navigators in the Learjet Models 35/35A/36/36A with the FC-200 autopilot and the Learjet Model 24.
The Garmin GTN series features intuitive touchscreen controls and a large-screen display that give Learjet pilots unprecedented access to high-resolution mapping, graphical flight planning, and geo-referenced charting, among many other features. The installation also features new GPS roll-steering that allows seamless navigation operations with turn anticipation and waypoint sequencing interfaced to the autopilot.
“This approval offers a significant and economical avionics upgrade for the Lear 30 series airplanes,” said Clark Stewart, president and CEO of Butler. “The STC for the new Garmin GTN series allows us to tap into a sizeable upgrade market for retrofit of flight management systems. The Garmin GTN upgrade provides significant functionality upgrades, including WAAS GPS approaches and roll-steering interface to the autopilot.”
“We have designed the installation to provide cost-effective options to meet the various Learjet operator requirements. We will be offering the GTN Learjet installations through our avionics facility Kings Avionics starting under $100,000,” commented Craig Stewart, Aerospace division president.
Butler National Corporation operates in the Aerospace and Services business segments. The Aerospace segment focuses on the manufacturing of support systems for commercial and military aircraft including the Butler National TSD for the Boeing 737 and 747 Classic aircraft, switching equipment for Boeing McDonnell Douglas Aircraft, weapon control systems for Boeing Helicopter, and performance enhancement structural modifications for Learjet, Cessna, Dassault, and Beechcraft business aircraft.
