A number of organizations are focusing on how inertial can help GNSS receivers to provide more stable, reliable position outputs when signals are hard to receive. Papers presented in September at the ION GNSS+ 2016 conference in Portland, Oregon, demonstrate that there is indeed a lot of focused effort in this area.
The conference showcased several integrated inertial GNSS solutions from a range of companies. For example, NovAtel is developing a novel way to make better use of lower precision MEMS inertial for certain land applications. Qualcomm is moving forward with a low-cost visual inertial to advance autonomous vehicle developments. And researchers in Germany from a university spin-off company are studying a multi-sensor solution.
Inertial integration aiding
Many people have heard about the NovAtel SPAN inertial/GNSS system. SPAN inertial-integration-aiding software has now been available integrated on NovAtel GNSS engines for a number of years. Combined with various external inertial packages providing real-time inertial aiding data, this system enables positioning outputs over a wider range of more difficult signal environments where GNSS alone might be too stressed to perform well.
According to the website, NovAtel currently offers SPAN with MEMS inertial products including various models from Honeywell, Litef, Analog Devices and Sensonor, along with a number of fiber-optic and high-precision tactical grade inertial measurement units (IMUs).
Recent SPAN development efforts have been focused on improving the performance of combined GNSS/SPAN/MEMS IMUs. The premise of the work is that in land-vehicle applications, a “land profile” can be applied that constrains velocity based on a range of acceptable vehicle dynamics. This includes applying limits to the cross track and vertical velocities of the vehicle.
In testing this land model, with equipment mounted in the NovAtel test van, three types on IMU were run through three different test scenarios. The IMUs were:
Epson G320 — Low power, small size MEMS IMU
Litef μIMU-IC — Larger tactical-grade performance IMU still based on MEMS sensors
Litef ISA-100C — Near-navigation-grade IMU using fiber optic gyros (FOG).
The three test scenarios involved environments with clear sky, partially obstructed sky view (downtown urban canyon) and a parking garage with no view of the sky and no satellite signal reception.
The Epson MEMS IMU appeared to be at a disadvantage from the beginning, given the higher performance units to which it was being compared. But NovAtel’s objective was to demonstrate that even this lower end device, when combined with GNSS, SPAN and the land profile, enables pretty good positioning results.
Test set-up.
Impact of SPAN land profile in GNSS denied testing.
The tests indicated that positioning with integrated higher performance units did not benefit to the same extent as when coupled with the low-end MEMS units in land-profile mode. Acceptable positioning was indeed possible with the Epson MEMS and when the constraints of land profile were able to limit position excursions when GNSS was lost, as in the parkade tests at Calgary airport shown in the figure above.
Ryan Dixon and Michael Bobye from NovAtel Inc. wrote this ION GNSS+ paper, “Performance Differentiation in a Tightly Coupled GNSS/INS Solution.” Ryan Dixon is the chief engineer of the NovAtel Synchronized Position Attitude Navigation (SPAN) GNSS/INS products, and Mike Bobye is a principal geomatics engineer at NovAtel Inc.
Visual inertial odometry
Qualcomm also presented some interesting results for the integration of visual inertial odometry (VIO) with GNSS. VIO measurements are constructed from a stream of camera frames combined with inertial measurements and can provide high-accuracy relative positioning. In experiments in a not-too-severe urban-canyon environment, this approach has been seen to reduce 95 percent horizontal error by two-thirds compared to GPS alone.
For applications such as autonomous vehicles and advanced driver assistance systems (ADAS), 50-meter errors, which can be typical for stand-alone GPS in urban canyons, just won’t cut the mustard. So Qualcomm has been looking for another source of aiding that would help reduce errors significantly.
The test set-up used a Sony Xperia Z3 phone as the source for the camera data and separate VIO processing, along with a single-frequency CSR SiRFstarIV GPS module on a custom hardware board for raw pseudorange and Doppler range-rate measurements. A high-precision NovAtel OEM6 GNSS/IMU SPAN-CPT module was used as ground-truth for position measurements.
Two scenarios were used to evaluate the proposed approach. The first scenario is an 870-meter drive in downtown Somerville, New Jersey, with a duration of 261 epochs. This represents a mild urban-canyon environment with loss of signal errors of a few tens of meters.
(Left) Part of the trajectory for the drive testing; (right) walkthrough building with no GPS coverage.
Results from the drive testing include several large GPS errors that the GPS+VIO solution is able to significantly reduce, while the walkthrough building tests appear to demonstrate a continuous GPS+VIO position solution.
“Robust Positioning from Visual-Inertial and GPS Measurements” was written by Urs Niesen, Venkatesan N. Ekambaram, Jubin Jose, Lionel Garin, and Xinzhou Wu, all of Qualcomm Research.
Multiple sensors
Finally, researchers at the Technical University of Munich (TUM) in Germany have focused on bringing outputs from as many sensors as economically feasible into an integrated GNSS solution. A precise model for multipath is included that applies amplitude, code delay, phase shift and Doppler shift for each reflected signal. The magnetometer measurements provide rough attitude information, which enables robust GNSS attitude ambiguity fixing.
The ANavS module integrates a multi-constellation u-blox GNSS receiver with a Sensonor 3D accelerometer/gyroscope/magnetometer, a Bosch barometer/thermometer and a built-in dual-band Taoglas GPS/GLONASS antenna. Real-time kinematic (RTK) positioning was tested by TUM students using the measurements from the multi-sensor module and a virtual reference station (VRS). A second multi-sensor module placed on the rear of the vehicle enabled attitude determination.
“Reliable RTK Positioning with Tight Coupling of 6 Low-Cost Sensors” was authored by Patrick Henkel, Technische Universität München, and Houcem Hentati, Advanced Navigation Solutions, Munich, Germany.
All of these options are providing GNSS with the support it needs in tight signal situations.
I didn’t get to this year’s IEEE/ION PLANS meeting in Savannah, Georgia, in April, but I did find a few papers that interested me. You might have read past articles of mine that looked at the challenges of indoor navigation. And, of course, unmanned vehicles technology also is one of my favorites.
So, I was pleased to find papers that addressed a few key issues for me:
An approach that employs cooperative smartphones to achieve about 3 meters indoor location.
Another look at the problems in using smartphone embedded GNSS for RTK positioning.
Relative positioning between UAVs using GNSS, radio and inertial, and also adding image processing in a GNSS denied environment.
Analysis of encounter-alerting issues for UAV detect and avoid systems.
Indoor navigation
Indoor navigation is an area which is seeing quite intense research, and several companies have now put initial products on the market. The general approach has been to use sensors within smartphones combined with radio-frequency (RF) signals which seem to be readily available in stores and malls which indoor location is finding commercial applications.
If a position can be generated by an internal GNSS receiver within the phone in an outdoor setting prior to entering a building, the trick is to carry that position forward as GNSS signals disappear when the user moves away from the entry area. Inertial sensors in the phone are usually not accurate enough to do this job on their own, so ranging using RF from Bluetooth and Wi-Fi transmitters/beacons may be integrated to provide a position solution. Magnetic sensors in the phone have also been used to detect fixed metal structures within a building and use this data to aid location determination.
The problem is that you need an up-to-date database of where the Wi-Fi and Bluetooth are located, and it has been taking a lot of work to map or “fingerprint” the interiors of buildings — and guess what, these “beacons” often are moved after a mall or store is mapped, so RF ranging can become quite inaccurate.
So, fearless investigators from the University of Buckingham and University of Northampton in the U.K. have come up with the concept of using ranging between cooperative smartphones to aid each other and achieve location accuracies of 5-10 meters.
While outdoors with good GNSS position, the inertial sensors in each phone are calibrated, each phone gets position using its internal GPS and a network is formed between the phones using their relative positions. Then when a phone goes inside the building, step counting is used to maintain relative positioning in the network. This can result in around 3 meters positioning for the interior phone.
Well, yes, not everyone has two other buddies waiting around so one guy can go in and find the classic comic store, but for applications such as firefighters, urgent/health care, and security/police, this approach might work well.
Cooperative smartphone location overview. (From “UNILS: Unconstrained Indoors Localization Scheme based on cooperative smartphones networking with onboard inertial, Bluetooth and GNSS devices,” H.S. Maghdid, A. Al-Sherbaz, N. Aljawad and I.A. Lami.)
Another paper looked hard at the options there might be to resolve problems with GPS performance which has previously precluded running RTK on smartphones. If we could achieve centimeter positioning on a mass-market basis, many current applications which are inhibited by cost, could become possible and revolutionize even the way we live. People have already used external solutions to solve some of the problems, but leading researchers at Texas U, with Broadcom and Radiosense support, may have come up with a self-contained solution.
It is known that there are issues with the capability of the GNSS chip and oscillator components in smartphones — the observables they produce are not currently of sufficient quality to sustain RTK performance. So these researchers worked with Broadcom, who supplied them with an Android smartphone, which provided access to raw code and carrier-phase outputs and was also able to process these measurements internally.
A smartphone’s Android software stack with the GNSS components and data flow highlighted. (From “On the Feasibility of cm-Accurate Positioning via a Smartphone’s Antenna and GNSS Chip,” T.E. Humphreys, M. Murrian, F. van Diggelen, S. Podshivalov, K.M. Pesyna, Jr.)
Carrier phase measurements in smartphones suffer from five anomalies not found in survey-grade GNSS receivers — but four of these can be fixed in post-processing. The remaining phase measurement error increases with time and precludes RTK centimeter-level positioning — it could be the result of round-off error due to processing limitations. Otherwise it seems possible that carrier-phase differential GNSS positioning might be achievable.
However, the researchers also studied antenna performance and found that its gain pattern was significantly affected by strong local multipath. The impact is that deep, unpredictable fading and large phase error will compromise centimeter-accurate positioning.
So we’re not quite there yet, but with a new smartphone version showing up almost every other year, it is always possible that researchers and manufacturers will eventually evolve designs in the right direction, and ultimately solve the problem.
Unmanned aerial vehicles
Meanwhile, researchers at West Virginia University have been investigating methods to maintain relative positioning between UAVs in flight. With drone “swarms” and cooperative drone missions becoming more common, if a simple method could be derived to maintain relative separation, these applications could become more prevalent, especially in a GPS denied environment.
So, with only noisy ranging radios between UAVs, and an onboard navigation system solution on each vehicle, the researchers set about developing an algorithm which can maintain relative position. The solution is complicated by the geometry between the UAVs, how often range measurements are made, and the noise in those measurements. To constrain these variables, the study was run assuming the UAVs travel at the same altitude.
The study concluded that— provided the UAVs travel in the same direction, parallel to each other — that their algorithm could find a solution all the time. The focus of the study appears to be on determining hearing and relative bearing between the vehicles and results were varied depending on the frequency of range measurements, the amount of noise and the geometry. So a few steps forward along the path towards making drones work together in a hostile environment where GPS is jammed. (See “Cooperative Relative Localization for Moving UAVs with Single Link Range Measurements,” J. Strader, Y.Gu, J.N. Gross, M. De Petrillo, J. Hardy.)
Another study on the same problem of maintaining relative position between drones was also undertaken by West Virginia University, Systems & Technology Research and the Air Force Research Laboratory. However, their solution didn’t only use ranging between vehicles. It took advantage of inertial measurements on each drone, computer vision calculations derived from downwards looking cameras on both UAVs, and finally magnetometer measurements were also added into a Kalman filter solution.
UAV platform payload diagram and assumptions. (From “Unmanned Aerial Vehicle Relative Navigation in GPS Denied Environments,” J. Hardy, J. Strader, J.N. Gross, Y. Gu, M. Keck, J. Douglas, C.N.Taylor.)
With several additional sensor measurements, the researchers were able to predict that relative positioning could be maintained in a GPS denied environment. They also considered ranging radio, magnetometer and vision update rates, and the performance/update rate of various quality inertial sensors. The principle objective is to enable accurate target hand-off between drones as one approaches the other. Overall, they found their model could support 10-meter-level position and 0.5 degree accuracy.
Finally, for safe operation of UAVs in the U.S. National Airspace System (NAS), minimum Detect and Avoid (DAA) standards for small to medium size UAVs are being developed for operations within drone-accessible airspace. DAA has to provide the “see and avoid” for unmanned aircraft systems (UAS) that pilots of manned aircraft use to avoid other aircraft. So surveillance sensor information needs to supply the UAV and the remote Pilot in Command (PIC) operator with the situational awareness needed to remain well clear of other aircraft.
Part of what DAA should provide are alerts working to universal standards for all UAS.
Zones used in alert evaluation. (From “Analysis of Alerting Performance for Detect and Avoid of Unmanned Aircraft Systems,” S. Smearcheck, S. Calhoun, W. Adams, J. Kresge, F. Kunzi.)
The research presented by CAL Analytics and General Atomics (with technical support and guidance by RTCA committee SC-228 and NASA) outlined the evaluation alerts generated when other aircraft are anticipated to penetrate into a well-clear volume around a UAV.
Alerts can be “missed,” “late” and “early” — all of which can impair DAA performance and safety and which need to characterized and mitigated. Sensors currently under consideration for use in DAA include Automatic Dependent Surveillance Broadcast (ADS-B), active surveillance transponder and airborne radar — this study looked at ADS-B and radar and the trade-off that they provide related to desirable and undesirable alerts.This analysis will likely feed into the development of UAS DAA alerting standards and requirements.
Typical DAA tracker approach. (From “Analysis of Alerting Performance for Detect and Avoid of Unmanned Aircraft Systems,” S. Smearcheck, S. Calhoun, W. Adams, J. Kresge, F. Kunzi.)
Radar surveillance errors were found to increase the probability of Missed, Late, Short, Early and Incorrect Alerts, all of which is bad news for radar. ADS-B surveillance errors increased the probability of Short, Early, and Incorrect Alerts. However, ADS-B did not lower performance as much as radar — better news for ADS-B. All levels of surveillance errors were seen to increase the amount of alerting jitter, with radar seeing the most significant undesirable effects.
Guardian UAS used in DAA tests.
Highly reliable, proven DAA systems are likely an essential part of the safety system for UAS if they are to become a regular part of operations in the NAS. General Atomics has tested a DAA system including GA’s Due Regard Radar (DRR) aboard a U.S. Customs and Border Protection (CBP) Guardian Unmanned Aircraft System (UAS), a maritime variant of the Predator B UAV. The DAA system also includes Honeywell’s Traffic Alert and Collision Avoidance System (TCAS) and Sensor Tracker, specifically designed for DAA.
Schiebel Camcopter S-100 demonstrating detect and avoid system.
And, also in December of last year, a Schiebel Camcopter S-100 flew demonstration flights with an NLR-developed AirScout Detect and Avoid System. Two helicopters flew “intruder” profiles against the UAV during the demonstration. The Camcopter S-100 flew several scenarios and “unexpectedly” encountered an intruder aircraft. The system determined in real time the corrective action to maintain separation from the intruder aircraft.
So, progress on indoor navigation, research towards running RTK on smartphones, relative positioning between UAVs, and advances in Detect and Avoid solutions for UAVs. Something of a mixed bag, but all promise further progress around different solutions for a number of market navigation segments.
GPS World held a webinar on new unmanned aircraft initiatives on May 21 led by a panel of experts. On hand were Don Mark of the law firm Fafinski, Mark and Johnson; James Spicer and Adrien Perkins, both students in aeronautics and astronautics at Stanford University; and Peter Cosyn site manager and director of research and development at Gatewing, a Trimble company. I also participated.
Alan Cameron, editor-in-chief and publisher of GPS World, hosted the event and introduced the participants. Around 300 people signed up to listen to the webinar and ask questions.
Don Mark provided a legal overview of the FAA’s regulations for UAS, FAA and U.S. Senate initiatives, James Spicer and Adrien Perkins reviewed the Jäger UAV jammer detection project, and Peter Cosyn provided an overview of the Gatewing/Trimble UX5 UAS solution. I provided insight into recent UAS industry.
Finally, the panel discussed a few of several written questions submitted by the webinar attendees. We promised to publish both these questions and our attempt at providing answers. Please bear in mind that this is new area of technology, applications and regulations governing operations — so we welcome clarifications and inputs as we may miss the mark occasionally!
Q&A for GPS World Webinar:
“New Frontiers in Unmanned Flight: Hey You, UAV!”
Is the FAA going to keep requiring a pilot’s license to operate a UAV?
The draft sUAS rulemaking proposed by the FAA does not require a pilot’s license. Instead, there’s a requirement to pass an aeronautical knowledge test, obtain an FAA UAS operator certificate and to pass an FAA knowledge test every 24 months. However, the Section 333 exemptions granted by FAA so far have all required that the operator have a private pilot’s license.
What are the effects (operational, legal) of GNSS receiver failures in UAV missions and what are some technical measures to avoid them?
Most UAS used within a critical or commercial operation not only carry GNSS, but also have some form of navigation back-up system — MEMS inertial being the most common — so navigation is still possible, albeit for a short time with any degree of accuracy. And in the event of a communications link failure, the norm is to have the UAV follow a pre-programmed “return-to-base” route, so the vehicle returns safely to a known location.
What is the development of UAVs in the healthcare industry?
There are a number of ongoing and proposed applications of drones that are health related. A prototype system in Delft, Netherlands, carries a defibrillator to be used to revive heart-attack victims. The concept is that a network of geographically distributed drones would be called from a cellphone, and the closest UAV would be dispatched and would be able to arrive much quicker than a conventional ambulance.
This drone is part of a prototype healthcare delivery system in Delft, designed to carry a defibrillator to heart attack victims and caregivers.
Other healthcare applications could include the rapid delivery of vaccines, medications and supplies delivered right to the source of an outbreak. This could more rapidly reduce the incidence of life-threatening communicable diseases. Communication equipment, mobile technology and portable shelters could be delivered in a rapid fashion to areas where critical infrastructure damage would prevent ground or typical air transport. Drones have also been used extensively in disaster relief efforts.
Also, in July, unmanned aerial vehicles will deliver medical supplies to a free health clinic in Wise, Virginia. The most urgent prescriptions will be provided by pharmacies located out of town. To get the medicine to the community as soon as possible, the pharmacies will deliver them to their local airport, where they will be collected by NASA’s fixed-winged aircraft and be flown to Lonesome Pine Airport. When the prescriptions arrive there, they will be loaded onto Flirtey drones and delivered to the Wise County Fairground. Flirtey drones are expected to deliver around 24 packages of prescription medication.
Please describe LiDAR systems available for UAVs.
There are many lightweight LIDAR systems on the market for UAV applications — some even come integrated within their own operational drone system. Coupling drone-mounted LiDAR systems with vision cameras, advanced computer processing and GPS, it has now become possible to create a remotely piloted flying LiDAR scanner.
Routescene’s LiDAR pod attached to the belly of a UAV.
Update us on legal matters within the European Union?
The EU has been very active in preparing for the commercial use of UAS, so drone use in the EU appears to be significantly higher than in North America because of the proactive effort of regulators to introduce drones into regular commercial applications. This Forbes article summarizes the approach being taken and the progress towards introducing regulations within the EU by the end of 2015.
You speak of “UAV navigation in environments where traditional GPS receivers may fail.” Are you considering indoors navigation or “just” urban environment?
It’s true that drones are being operated indoors — for instance, within restaurants. In these environments, all the typical indoor navigation techniques will be viable — RF/magnetic fingerprinting, Bluetooth beacons, Wi-Fi source databases, cellphone signals including small cells, and even optical sensors, all often combined with indoor maps.
Urban environments with a restricted view of the sky also continue to challenge GNSS only navigation, which has led to extensive use of integrated inertial/GNSS navigation sensors.
Modularity of UAVs? Different sensors for different types of applications using the same UAV?
A number of professional drone manufacturers offer UAS that could carry different payloads. However, most manufacturers seem to focus on particular applications (flying camera, LIDAR and/or video survey) and don’t carry an extensive range of optional third-party payload equipment.
What regulations are there for self-made UAS?
It’s hard to imagine that the regulations would be different for a commercially manufactured drone or a home-built UAS. Only time will tell as regulations are developed that include this category of UAS.
What background and abilities should a team possess if it wants to develop a UAV?
An engineering team that takes on developing a UAV needs to be aware of the basics of flight, navigation and control/communications — these are the principle elements of UAV operations.
Do you exploit software-defined radio techniques?
Software-defined radios may find their way into UAVs whenever weight/volume are an issue, but they potentially require higher computing capability, and maybe somewhat higher power to run co-processors. Weight and power consumption are at a premium on small UAVs, so any initiative that saves in these areas will no doubt be welcomed.
What are the emerging application areas for UAVs?
It would seem that the application areas for UAVs are virtually unlimited. High interest areas include agriculture, pipelines, buildings and transmission line inspection, aerial survey, filmmaking and newsgathering, wildlife and environmental monitoring, fishing and military reconnaissance/weapons delivery. But there are many, many applications, some of which might not fit into this summary of applications.
When will the UAV market move beyond focusing on the drone itself and get to the important topic of what sensor technology and back-office systems provide the best value to the user? The UAV is a commodity.
Good comment — the utility of the UAV comes from the payload it carries and the analysis of the data it collects and how it can be operated.
I’m curious if the UAV mission will be used in conjunction with autonomous agricultural tractors and construction machinery. I’m assuming an off-site tractor operator would benefit from the aerial data for their scope of work.
Absolutely — another possible UAV application.
Do you know when high-altitude long-endurance solar-powered UAVs will start being used?
The key application being pursued by Google using high-altitude, long-endurance, solar-powered drones is to provide Internet coverage in areas that currently have no ground infrastructure. A number of countries around the world would benefit from connection to the Internet using this approach. Unfortunately, the prototype aircraft built by Titan Aerospace recently crashed. But Google has vowed to continue with its efforts. Another development, called Project Loon, involves the use of high-altitude balloons and is already well underway.
I am currently enrolled in the UAV Pilots Certificate Training Program offered through the Unmanned Vehicle University. Is this certificate, which costs $3500, going to actually benefit me in my future commercial operations? Does the FAA recognize it as anything valid? So unless the certificate provides me some practical advantage, I’m not sure if it was legitimate or a scam. Any thoughts on this or experience with this “University”?
A recent Senate bill seeks to establish the six FAA test centers as the authorities for training UAS pilots. However, it would appear that currently no universal training course has yet been developed or approved for UAS pilot training — so it may be premature at this stage to engage with third parties for training until guidelines are published by the FAA.
What is the positional uncertainty associated with the locational measure of GPS systems on these UAVs? What will it be in five years?
Depending on the application, accuracies between 1 meter and a few centimeters are being achieved. For higher accuracy requirements such as precision surveying, post-processing of data collected during a survey can provide accuracies within a few millimeters.
In five years’ time there will be more satellites in more constellations, and it’s possible that accuracies could improve further. However, the most benefit will come from having more reliable signals, more often, thereby reducing re-test and operational costs.
What industry do you see being the fastest adopter of UAV technology in the USA?
The U.S. military is already leading in the number of applications, number of operational UAS and number of different types of vehicles. Commercial applications have increased substantially now that the FAA has authorized a large number of civilian operations in the last year or so. There are a number of film and TV applications for movie-making and newsgathering, and this appears to be a growing area for commercial UAS. Aerial survey is also growing in popularity, and there is a huge range of monitoring applications for building inspection, pipeline and transmission line inspection, and also for crop growth monitoring — which may turn out eventually to have the highest number of applications in the U.S.
How do you think the industry should protect UAVs from GPS spoofing and other forms of remote or internal component (example ICS or SCADA) attacks?
Solutions to mitigate GNSS spoofing and signal jamming are currently high on the list of most receiver manufacturers’ development agendas, with several options already having reached the market. Anti-jam antennas, improved signal rejection in RF front ends, and algorithms that claim to be able to deduce and overcome spoofing attacks — these are the leading solutions that have been fielded. But we have only just scraped the surface of deceptive techniques being used and the frequency with which they are being encountered, so we should continue to see the solutions evolving to counteract more sophisticated interference and spoofing capabilities over time.
Will the upcoming regulations only impact commercial users, or will they also directly affect non-commercial and/or recreational operators?
In the U.S., regulations governing the operation of recreational or hobby aircraft appear to be less stringent than, say, a drone operating commercially. As long as common sense rules are observed, hobby aircraft operators have been able to operate without the FAA looking over their shoulders — provided they stay below 400 feet in an open space away from sensitive areas such as schools or hospitals and don’t make an inordinate amount of noise, no one has yet proposed more restrictions for hobbyist model aircraft operators. The focus for the FAA is currently on bringing drones safely into the national airspace system for commercial operations, so regulations so far have been mostly formulated to enable this to happen.
Proposed legislation in the USA refers to one pilot per vehicle; no mention is made of swarming or control of multiple vehicles per pilot. Is it worth developing apps that use swarms of UAVs at the moment?
Certainly, it’s been difficult for the FAA to introduce regulations for UAS that are acceptable for most anticipated commercial operators, while still respecting and protecting current manned aircraft operations. So far, we’ve had case-by-case approval for specific operations, while regulations for small UAS (sUAS) have only just been circulated for comments — and a huge number of comments have been received. So regulations for “regular-sized” and operated drones and for larger vehicles have not yet seen the light of day. So, the more complex applications involving the operation of a swarm of UAS may not yet have been even considered by the FAA. It has taken years to get this far, and we still don’t have any published regulations for any class of UAS in commercial applications, so it’s doubtful that there is any work underway on regulations for swarming drones. So develop apps if you wish, but don’t expect much regulatory support for some time yet.
What assurance do we have that a UAV operator won’t deliver a weapon instead of an Amazon purchase?
The exemptions that have been published allow certain well-defined, specific commercial operations of UAS. The unmanned vehicle has to be registered to an individual and get a unique tail number. The operators have to be identified and must regularly demonstrate proficiency and adequate knowledge to become a recognized operator. So authorities get to inspect the UAV, know the owner and know the operator, and even get to review and approve the location of each UAS operation — not that that would prevent someone subsequently modifying the vehicle to carry ordinance, or knowingly attacking a target. It would, however, be pretty easy to track down the offender, but that doesn’t really prevent “weaponization” or delivery. But we are only at the small-vehicle-level currently, so its doubtful if major damage would be possible with small weapons, but an individual attack might still be lethal. Careful screening of individuals seems to be the route the regulators have taken to minimize this risk. This is still a difficult issue that is going to take some policing and close control.
Instead of an actual pilot’s license required for legal flight of a UAV, do you think an all-encompassing UAV pilot’s license will be required? I ask because I am a trained Trimble UX5 pilot, but I do not have my pilot’s license. I also build UAVs, and I am curious how I would get a UAV pilot’s license for a UAV I built? Unless they had an all-encompassing training course for pilot/flight safety.
The FAA proposed rulemaking for sUAS operations did not require operators to have a pilot’s license. Instead, UAS operators are required to undertake a specific recurrent training course for UAS operators, administered by FAA qualified trainers. Regulations relating to “home-built” UAS have yet to emerge, and may be some time away from publication.
It is said that mainland China has over 70% of the world UAV market? How did we fall so far behind?
Lack of regulations in the U.S. may have held back U.S. industry — see related comments by Amazon in testimony to the U.S. Congress.
But also the absence of restrictions in other countries may have helped overseas manufacturers get established and to gain initial market share. While the majority of done R&D was initially within the U.S., it’s clear that DJI and its Phantom line of drones have become very popular, very quickly. Strangely enough, the largest concentration of buyers and operators currently appears to be in the U.S.
Insurance against UAVs crashing and causing damage to humans: what progress has been made in this area?
Several insurance companies are now writing risk-coverage policies for UAS, including Global Aerospace, USAIG, Allianz and AIG.
We are operating a GNSS reference network in Greece, SmartNet-Greece (Leica Geosystems). Is there a tested NTRIP system on UAVs, to be connected and monitored to Ntrip caster? How could this augment real-time GNSS accuracy of UAVs?
Seems like you are trying to get RTCM corrections from a ground network to a flying UAV – correct? So do we need an Internet connection to get your ground network RTCM corrections onto the UAV? I’m not an expert on available mobile Internet hook-ups, but most smartphones have one, so it can’t be that hard to add this onto a UAV. Alternatively, wouldn’t it be easier to have the GNSS receiver on the UAV listen to a PPP broadcast from one of the several services providing these corrections? We could get down as far as 10 cm accuracy with one of these commercially available correction services.
Talk about the possibilities of precise positioning in UAVs, instead of mapping.
Precise real-time positioning on a UAV is a question of which GNSS receiver is onboard and which PPP or local RTK network transmissions are available in the area of UAV operations. Positioning accuracy is possible of a few centimeters down to a few millimeters post-processed.
Realistically, how close are we to being able to fly UAVs for commercial applications such as topographic surveys and earthworks applications such as mining sites?
As we heard during the webcast, obtaining an FAA section 333 exemption is quite possible for these applications, and some have already been granted. The FAA has been streamlining the process recently to reduce the time it takes to obtain these authorizations.
What is a practical ceiling for UAV flight?
The FAA has limited UAS operations to below 400 feet in the Section 333 exemptions that have been granted, while 500 feet is used as the maximum ceiling in the proposed draft sUAS regulations.
What is status of technology for “see and avoid” requirements for UAVs?
NASA, the Federal Aviation Administration (FAA), General Atomics Aeronautical Systems (GA-ASI) and Honeywell International Inc. have successfully demonstrated a UAS proof-of-concept sense-and-avoid (SAA) system. GA-ASI worked with NASA’s Armstrong Flight Research Center to integrate the new system aboard NASA’s Ikhana research aircraft, a civilian version of the company’s Predator B. The flight-test campaign in November and December 2014 evaluated the SAA system in a wide variety of collision-avoidance and self-separation encounters between two remotely piloted aircraft and various manned aircraft and included a sensor-fusion algorithm being developed by Honeywell.
NASA’s Ikhana Predator B drone.
An RTCA subcommittee is also working in parallel to develop the requirements for an SAA system, and these flight-test evaluations will contribute to those technical standards.
Other companies that are also thought to be active in SAA development include Rockwell/Collins, Sierra Nevada and Insitu/ Queensland University of Technology Australia.
So, a large number of questions on a pretty wide range of subjects — hopefully some of the answers we’ve provided will be of assistance — but please provide us with your comments if you have information to share.
Disclaimer: The statements, questions, views and opinions presented in this article are those of the author and webcast audience, and may not necessarily reflect the opinions of GPS World magazine, its owners or staff. Readers are also warned that the answers are provided on a best-effort basis and could be less than 100% correct.
