Aerospace and Electronic Systems Magazine September 2016 - 14

Prototype Sense and Avoid System Onboard a ScanEagle Unmanned Aircraft
reduction in power consumption while also reducing the overall
cost of the SAA system. Our flight tests also demonstrated that the
migration of the SAA system to the ScanEagle and the significant
SWaP reduction did not affect the system's main capability of detecting collision threats.
The ability to trade-off the FOV, detection range, SWaP requirements, and system costs will allow the tailoring of the SAA
system for each unmanned aircraft and each operating environment. This flexibility allows the technology to be used on a wide
variety of aircraft platforms-including manned aircraft.

FUTURE
SAA SYSTEM IMPROVEMENTS
There are a number of options to improve the capabilities of the
SAA system. Testing additional scenario geometries in a wider
variety of environmental conditions would help to further mature
the SAA system. One immediate and relatively easy option is to
collect more no-target data to extend the false alarm performance
of the system.
Technology improvements during the SAA system's development have meant that more processing power is now available. Instead of an SBC with 16 cores a new low-power 192 core SBC is now
available as a low-cost COTS solution. Whilst good detection performance was achieved with the current system, more processing power
would enable a higher frame rate and the processing of more of the
available FOV. Increasing the FOV would allow the SAA system to
provide greater SAA protection from a wider range of azimuths.
The FT&E campaign deliberately concentrated on the "sense"
component of SAA. One manual avoidance manoeuvre was demonstrated. The nature of the avoidance manoeuvre was determined
by the remote pilot in real-time. Automated manoeuvres have been
left for future work, although they have previously been tested on
the Cessna-based system [14].

SAA - AN ENABLER OF AUTONOMY
Looking towards the future, an SAA system is an important step
towards a fully autonomous unmanned aircraft [36]. The ultimate
aim is an aircraft that can autonomously sense and avoid aircraft
and other obstacles within the operating environment. Our prototype SAA system performed all the data processing onboard the
ScanEagle in real-time. Onboard processing provides another step
towards autonomy, where all the processing and decision making
is made independently of any command and control communication links.

CERTIFICATION OF SAA
At the time of writing, the civil airworthiness certification of SAA
systems is an ongoing issue for the UAS community. The Radio
Technical Commission for Aeronautics (RTCA) has recently released Phase I Minimum Operational Performance Standards
(MOPS) for Detect and Avoid (DAA) systems [37]. Compliance
with the standards is recommended as one means of assuring that
14

the SAA system will perform its intended functions satisfactorily
under all conditions normally encountered in routine aeronautical
operations. The initial MOPS, however, are aimed at UAS that are
equipped to operate into Class A or restricted airspace under instrument flight rules (IFR) and have a take-off weight greater than 25
kg.
When suitable MOPS are available for small UAS then the
challenge and expense of compliance will be brought into focus.
The current SAA system, for example, is composed of a number of
COTS systems. The suitability of these COTS systems will need to
be assessed during the SAA compliance testing process. The frequent release of new COTS systems, with improved capabilities,
may challenge the compliance process.

CONCLUSIONS
This article described the development of a prototype SAA system, which was successfully flight tested and evaluated onboard
a ScanEagle unmanned aircraft. Unmanned versus manned flight
tests, in nonsegregated civilian airspace, were used to demonstrate
a world first: the real-time detection of a collision threat from a
small UAS.
Two lenses were tested during the FT&E campaign. This enabled the trade-off between FOV, detection range, and hardware
performance to be explored. The average detection ranges from the
campaign were close to the empirical predictions. This close correspondence validated the use of empirical models for SAA system
design and performance prediction.
The ScanEagle's SAA system demonstrated a capability to detect aircraft at ranges that were similar to a pilot's ability to see
other aircraft. One flight test confirmed that the detection ranges
provide sufficient time for the remote pilot to make a decision and
execute a successful collision-avoidance manoeuvre.
The real-time and post flight-test evaluation results emphasised the importance of quantifying the SAA system's performance
in terms of the detection range and the associated false alarm rate.
Post flight-test analysis also demonstrated that changing the structuring element of the SAA system's morphological filter led to significantly improved aircraft detection results.
The research presented in this article has demonstrated that real-time SAA is possible from onboard a small unmanned aircraft,
which is an important milestone for the integration of small UAS
into the NAS and their subsequent use for commercial and civilian
applications.

ACKNOWLEDGMENTS
The research presented in this article forms part of Project ResQu
led by the ARCAA, QUT. The authors gratefully acknowledge the
support of the project partners: QUT; Commonwealth Scientific and
Industrial Research Organisation (CSIRO); Queensland State Government Department of Science, Information Technology, Innovation and the Arts; The Boeing Company, and Insitu Pacific Limited.
We also acknowledge the assistance of Dr. Luis Mejias. Mr. Duncan Greer and Mr. Dirk Lessner operated the Cessna 172. Mr. Nigel
Meadows and the Insitu Pacific team operated the ScanEagle.

IEEE A&E SYSTEMS MAGAZINE

SEPTEMBER 2016

Table of Contents for the Digital Edition of Aerospace and Electronic Systems Magazine September 2016