Tech titans like Uber, Amazon, and Google have all laid out ambitious plans for filling the skies with autonomous aircraft. Uber plans to launch an “on demand aviation” service called Uber Elevate through its flying car project. The European aerospace giant Airbus recently unveiled its secret flying-car project dubbed Vahana — a single-manned, autonomously piloted aircraft that can take off and land vertically. Amazon and Google plans to launch automated drone delivery fleets across urban areas that could eliminate the need for shipping via post or UPS.
UAVs have also become indispensable to modern militaries in providing intelligence, near-real time reconnaissance and surveillance to commanders, and offering warfighters greater battlespace awareness. They have proven effective in electronic combat support, battle damage assessment and even in national security operations like border surveillance, low intensity conflict and guerilla / terrorist warfare. In the future, UAVs will act as airborne data links, enemy radar jammers, chemical and biological weapons detectors, target acquisition systems, and finally precision air attack systems.
Unmanned Aerial Vehicles (UAVs) are growing at frentic pace driven by civil, consumer and military requirements. According to a 2014 Volpe report, the number of UASs operating in the U.S. National Airspace System (NAS) will exceed 250,000 by the year 2035. There are growing number of civil and commercial applications of UAVs, including humanitarian aid and disaster relief, infrastructure monitoring (such as oil pipelines), wildlife conservation and precision agriculture.
In order for a UAS to safely navigate in the already crowded aerial environment of the modern world, the U.S. Federal Aviation Administration (FAA) and other international organizations have mandated that unmanned aircraft must have an on-board Sense and Avoid (SAA).
The aims of Sense and Avoid technology, also referred to as ‘detect and avoid’, sense and avoid’ or ‘collision avoidance’ technology are the same; to detect aircraft & obstacles within the vicinity of the UAV and to execute manoeuvres to restore a safe situation if needed. In addition UASs must ensure that they can avoid the terrain and land without operator intervention, react to contingencies such as engine out and lost link scenarios, and Be reliable and cost-effective.
However, at present, UAVs cannot autonomously detect or avoid other UAVs, aircraft or obstacles such as buildings, and therefore present a severe concern for mid-air collisions. As a consequence, they cannot be flown out of line of sight or within close proximity to large gatherings of people, thus restricting their uses within the commercial sector.
Sense and Avoid technology
Sense and avoid is a sequence of functions which, using a combination of airborne and ground-based sensors, are able to perform manoeuvres to avoid collisions and serve as a UAV replacement for the tradition “see and avoid” capability for manned aircraft.
The Sense and avoid technology is of two types, one is for drones called manual sense and avoid which relays information to the UAV pilot and the second is the development of completely autonomous sense and avoid technology which removes the need for a pilot altogether.
Sense and Avoid Technologies
The cooperative technologies depend on cooperation from other aircrafts to know their distance, velocity and altitude and avoid collisions, while noncooperative technologies use active and passive sensors to determine these parameters on their own.
Cooperative technologies are widely used in manned aircraft and have a reliable track record in regards to reducing the number of midair collisions. One of the most desirable options is constructed using T-CAS or ADS-B transponders. Traffic Collision Avoidance Systems (T-CAS) or Automatic Dependent Surveillance-Broadcast (ADS-B) transmit information on an aircraft’s altitude, velocity and distance to other aircraft within a certain range. Whilst far more accurate than radar, systems such as T-CAS and ADS-B will only constitute an effective sense and avoid system once all aircraft are equipped with them.
As a consequence, until T-CAS and ADS-B become mandatory for all aircraft researchers are looking toward other options for sense and avoid. In addition, cooperative technologies provide no SAA capabilities against collisions with ground-based obstacles such as terrain features, towers, or power lines.
Volpe’s Ground-Based Sense and Avoid (GBSAA) capability
The ground-based sense and avoid (GBSAA) capability uses existing air traffic data from multiple sources to provide UAS operators with a real-time display of aircraft in the surrounding airspace. GBSAA alerts operators to potential conflicts with neighboring aircraft and recommends avoidance maneuvers for UAS in the event that a conflict does occur.
The primary component of GBSAA is a modified FAA terminal automation system that ingests and displays surrounding aircraft to a UAS operator. GBSAA leverages existing NAS radar equipment and infrastructure to locate these surrounding aircraft, and also has the ability to track “non-cooperative aircraft,” or aircraft lacking electronic means of broadcasting their position or speed.
Volpe has worked with industry collaborators from the MITRE Corporation, MIT Lincoln Laboratory, and Raytheon to develop and deploy a low-cost automated solution that enables UAS operators to “sense and avoid” other aircraft. The Air Force uses GBSAA for its UAS missions at Cannon AFB to ensure separation and conflict avoidance in relation to civilian air traffic.
Noncooperative technologies benefit from the fact that they can be used to detect ground-based obstacles as well as those that are airborne.
Active systems transmit a signal to detect obstacles in the flight path. Some examples of these active systems are radar and LiDAR. Motion-detection, EO, and IR systems are all examples of passive systems.
Sensor have their advantages and disadvantages, airborne radar, for example, measures the range to a target whereas electro-optical sensors do not, which are forming a key element of sense and avoid research. Sense and avoid systems use algorithms that combine data from the varying sensors and convert said data into a situational awareness picture. Systems such as these enable the pilot to alter the flight path of the UAV if a possible collision is detected, however also integrate a safety feature which enables the UAV to move itself if the pilot fails to react quickly enough.
Miniaturized phased array radar
Researchers at the University of Denver’s Unmanned Systems Research Institute have developed a phased-array radar system that only weighs 12 ounces. The radar-based system has advantages over transponder or camera systems because it works in poor visibility – at night or in bad weather. That technology is currently in the testing phase.
Echodyne’s flat panel radar hopes to power the next generation of autonomous aviation
Echodyne Corp has carried out the successful test of airborne Detect and Avoid (DAA) radar on a small Unmanned Aerial Vehicle (sUAV). Echodyne’s radar was mounted on a small commercial drone which flew multiple missions below 400’ over a period of several days. The drone was of a size, payload, and range well suited for package delivery, infrastructure inspection, and agricultural monitoring.
Echodyne’s detect and avoid technology enables a drone to “see” moving and stationary obstacles using “radar vision” as the drone flies through the airspace beyond line of sight of its operator. Echodyne’s radar is based on patented Metamaterial Electronically Scanning Array (MESA) technology which enables the radar to deliver high-performance electronic scanning in a smaller, lighter and less expensive form factor than has been previously thought possible.
“It’s great to see our technology performing in real-world field tests exactly as designed,” said Echodyne founder and CEO Eben Frankenberg. Tests like this show that advanced radar can be deployed directly on small commercial UAVs to ensure safe beyond line of sight drone operations. Unlike other sensor technologies such as cameras and LIDARs, radar provides accurate tracking of obstacles at long range across a broad field of view in all types of weather.”
Doppler radar for small UAVs
Ashok Gorwara and others have proposed Doppler radar for small UAVs. “Doppler radar is proposed for use in this sense and avoid system because in contrast to optical or infrared (IR) systems Doppler can work in more harsh conditions such as at dusk, and in rain and snow. And in contrast to ultrasound based systems, Doppler can better sense small sized obstacles such as wires and it can provide a sensing range from a few inches to several miles. An SAA systems comprised of Doppler radar modules and an array of directional antennas that are distributed around the perimeter of the drone can cover the entire sky.”
These modules are designed so that they can provide the direction to the obstacle and simultaneously generate an alarm signal if the obstacle enters within the SAA’s adjustable “Protection Border”. The alarm signal alerts the drone’s autopilot to automatically initiate an avoidance maneuver,” explain the researchers.
The primary function of LiDAR sensors is to measure the distance between itself and objects in its field of view. It does so by calculating the time taken by a pulse of light to travel to an object and back to the sensor, based on the speed of light constant.
LeddarTech – Leddar just announced its modular Vu8. The specs make it ideal for autonomous drone use. The Vu8 is a compact solid-state LiDAR sensor that detects targets at a range of up to 705 feet (or 215 meters) and weighs 75 grams. The Vu8 is an active sensor that “could be” used for collision avoidance, navigation, and as an altimeter for drones. According to LeddarTech, the Vu8 LiDAR is “immune to ambient light” and was designed to provide “highly accurate multi-target detection over eight independent segments.”
“Leddar solid-state LiDAR technology, with its narrow or wide field-of-view, rich data acquisition, and multi-segment/multi-object detection capability, might be the best all-around sensing solution to provide efficient and reliable spatial awareness for a new generation of UAV,” says LeddarTech.
An emerging technology uses biotechnology with the eyes of flying insects as a model for sensing. This technology is referred to as neuromorphic motion detection, and attempts to copy the optical flow that is used by flying insects. Optical flow in insect eyes detects relative motion of contrasts through multiple eye sensors called lenslets.
Further projects are also looking to combine sense and avoid with ground-based radar and terrain avoidance capability to enable UAVs to avoid a broader range of obstacles. Currently in use, and of particular value to UAS (especially for ground-based objects) due to their small size, is the synthetic aperture radar (SAR).
NASA New SAA Technology for Unmanned Aircraft
NASA has developed technology that may enable unmanned aircraft to fly safely in the national airspace along with piloted aircraft through its program called Unmanned Aircraft Systems in the National Air Space or UAS in the NAS. The patent-pending integrated communications and control system is capable of collision warnings as well as real-time traffic and weather updates.
NASA recently tested on remotely piloted Ikhana aircraft its prototype Detect-and-Avoid (DAA) system working in concert with airborne and ground-based computers. Ikhana made 11 flights involving more than 200 scripted encounters with approaching aircraft. Depending on the specific scenario, either Ikhana detected one or more approaching aircraft and sent an alert to its remote pilot to take action, or Ikhana itself took action on its own by flying a programmed maneuver to avoid a collision – an aviation first.
General Atomics Aeronautical Systems, Inc. has developed one of the three primary DAA sensors flown on Ikhana, in this case a prototype radar system. It also contributed Ikhana system and self-separation and collision avoidance alerting logic software. The other two sensors included an Automatic Dependent Surveillance – Broadcast (ADS-B) from BAE Systems, and a second generation Traffic alert and Collision Avoidance System (TCAS) from Honeywell International, Inc.
Vigilant Aerospace Systems intends to commercialize the technology as part of its new FlightHorizon product suite and equip manned and unmanned aircraft with the hardware and software that provides synthetic cockpit views and detect-and-avoid commands to improve flight safety for all kinds of aircraft.
“One of major advantages of this system is that it uses existing FAA infrastructure to help keep drones away from other aircraft,” said Kraettli L. Epperson, CEO of Vigilant Aerospace Systems. “It also gives nearby aircraft the ability to be aware of the drone and improves situational awareness for the drone operator.”
DARPA’s ALIAS program
DARPA’s Aircrew Labor In-Cockpit Automation System (ALIAS) program recently conducted the first successful flight tests of a shoebox-sized, plug-and-play system designed to enable manned and unmanned aircraft to automatically detect nearby aircraft and avoid potential mid-air collisions. An unmanned air vehicle (UAV) repeatedly used the technology demonstration system to detect and track in real time a Cessna 172G aircraft approaching from various vertical and horizontal distances.
The integrated sense-and-avoid (SAA) system includes a single optical camera that provides imagery for detection and tracking. The system also incorporates passive ranging features that assess the likelihood of an incoming aircraft intersecting the flight path of its host aircraft, and collision-avoidance capabilities to determine the best way to steer the host aircraft out of harm’s way.
The work is part of a DARPA effort to create a low-cost, easily installed system to detect oncoming or crossing aircraft and determine the best avoidance strategy compliant with standard rules that set minimum vertical and lateral distances between aircraft during flight.
This follow-on research would shrink the system size; further test the ranging and collision-avoidance features; mature additional capabilities of the system such as detecting aircraft below the horizon and in poor light conditions; and improve calculations for optimal aircraft trajectories to avert impending collision.
The system could ultimately serve as a line of defense in future layered air-traffic management systems that could include Automatic Dependent Surveillance-Broadcast (ADS-B) transponders and ground-based radar systems that are part of the federal NextGen effort. There is particular potential applicability for unmanned air systems or aircraft with reduced crew sizes.
The ALIAS program envisions a tailorable, drop-in, removable kit that would enable high levels of automation in existing aircraft and facilitate reduced need for onboard crew. The program intends to leverage the considerable advances that have been made in aircraft automation systems over the past 50 years, as well as the advances that have been made in remotely piloted aircraft technologies, to help shift and refocus pilot workloads, augment mission performance and improve aircraft safety.
As an automation system, ALIAS aims to support execution of an entire mission from takeoff to landing, even in the face of contingency events such as aircraft system failures. ALIAS system attributes, such as persistent-state monitoring and rapid recall of flight procedures, would further enhance flight safety. Easy-to-use touch and voice interfaces would facilitate supervisor-ALIAS interaction. ALIAS would also provide a platform for integrating additional automation or autonomy capabilities tailored for specific missions.
Navy Choses RDRTec to develop common Sense and Avoid
Naval Air Warfare Center Aircraft Division-Lakehurst in Lakehurst, N.J., has awarded a $3 million contract to RDRTec for developing common Radar Autonomous Collisions Avoidance System (RACAS) Sense and Avoid (SAA) technology that fulfills both the Fire Scout and Triton unmanned aerial vehicles (UAVs).
The Fire Scout is an unmanned autonomous helicopter designed to provide reconnaissance, situational awareness, aerial fire support, and precision targeting support for ground, air, and sea forces. The Triton is a maritime version of the Northrop Grumman RQ-4C Global Hawk long-range high-altitude reconnaissance UAV adapted for maritime patrol in a support role to the Navy P-8 Poseidon manned maritime patrol jet.
In a separate Navy project, RDRTec experts developed radar sense-and-avoid technologies for the Fire Scout UAV using advanced AESA technology and proprietary signal processing to provide actionable collision warning information with lead times longer than 30 seconds involving non-cooperative aircraft moving as fast as 400 knots.
RDRTec Inc. is developing adaptive multi-channel phased array manifold radar technology that reconfigures by radar mode for optimum performance. Company experts are focusing on multi-mode X or C-band radars with phased arrays that support modes with high and low bandwidth requirements. High bandwidth modes include synthetic aperture radar (SAR), inverse synthetic aperture radar (ISAR), and high range resolution (HRR). Relatively low bandwidth modes include ground moving target indicator (GMTI), maritime moving target indicator (MMTI), air-to-air (AA) and sense and avoid (SAA) modes
USAF desires Remotely Piloted Aircraft (RPA) Sense and Avoid (SAA)
The Air Force has released a request for information notice requesting sense and avoid technologies for large RPAs – Predators and Global Hawks – though the notice said that sense and avoid technologies for smaller RPA such as the hand-launched Wasp and Raven are also encouraged.
As weapon systems have become increasingly complex, so have the environments in which they are expected to operate. Remotely Piloted Aircraft (RPA) Sense and Avoid (SAA) capabilities enable RPAs to maintain safe separation to include avoiding collisions as well as safely integrate with other airspace users across the full range of operations in global airspace environments. The global airspace includes operations in National Airspace (NAS), International Civil Aviation Organization (ICAO)/international airspace to include Due Regard, and Military Airspace (MAS).
Federal Aviation Rule (FAR) 91-113 requires the pilot to “see and avoid” other traffic. Because RPAs have no onboard pilot, RPA require a SAA capability which enables the RPA to operate safely in airspace with other users. The SAA capability must be able to provide safe-separation to include avoiding collisions.
The solution responses are expected to include, but not limited to, descriptions for the following attributes:
- Strategies for airworthiness certification (e.g. MIL-HNBK-516 C, or most current) and operational approval of the proposed solution
- Information Assurance and Cyber Security implementation
- Solution characteristics of Open Systems / Open Architectures which are highly desirable for a SAA solution
- Strategies for adherence / certification to quality management practices (e.g. SAE AS9100C, “Quality Management Systems: Requirements for Aviation”)
- Strategies for reliability and maintainability
- Strategies for system security and survivability
- Strategies for addressing Critical Program Information (CPI)
Challenges in Autonomous Sense and Avoid
The principle challenge in achieving autonomous sense and avoid technology is that it must be as effective as a human pilot. However developing a system that is able to replicate the human decision making process is incredibly difficult, and thus serves as the greatest stumbling block to the development of the technology. As a consequence the transition from pilot action for emergency manoeuvres to autonomous algorithms may be some way off for the industry.
There are many challenges: Making sense and avoid technology small enough and light enough to suit the capabilities of UAVs is proving particularly difficult. The size of UAVs, particularly with the increase of micro and nano UAVs, means that they do not have sufficient payload capabilities to utilize traditional methods such as radar for the detection of other aircraft. As a consequence, size and weight are becoming serious stumbling blocks to the successful development of sense and avoid.
Speed adds a further complication: detecting other aircraft which are travelling at a relatively slow speed is a challenge within itself. However identifying aircraft travelling at faster speeds requires a much quicker reaction time from sense and avoid technology in order to avoid collisions, thus creating an even greater hurdle to implementing the technology.
Further complexities are imposed by the power consumption and battery life of UAVs, the need for the technology to operate in different conditions, such as variable weather, and generating a sense and avoid system which operates on the same right-of-way rules as civil aircraft and commercial flights.
LeddarTech says: Available drones sensing solutions for position and range measurements as well as for collision avoidance are still far from perfect: GPSs and barometers aren’t full-proof—even outdoors—and can’t be relied upon when navigating indoors. Ultrasonic altimeters have very limited range. Optical flow sensors require good lighting and textured surfaces, and camera vision are still a work in progress and tend to be processing-intensive.
Sense and Avoid for autonomous UAVs and Swarms
The future autonomous systems will have ability to perform with a higher level of autonomy. Instead of just being able to execute a set of pre-programmed functions, they will be better able to react to their environment and perform more situational-dependent tasks as well as synchronized and integrated functions with other autonomous systems.
UAV Swarms is another emerging technology that could prove revolutionary for Military Strategies. These swarms can find, fix, and communicate precise target location of ground, sea, and air targets; they can serve as weapons platforms to attack air defense systems from multiple axes; or they can pass missile targeting data to any platform carrying a counter air missile. Sense and avoid challenges are even more complicated for autonomous systems and swarms.
While working sense and avoid technology still appears part of the distant future, the main consensus emerging from those researching the technology, including the ASTRAEA and MIDCAS Projects, is that the basic technology is there, it just needs to be monitored and developed.
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