A number of Unmanned Aerial Vehicle (UAV) mission-and-safety critical tasks involve low-level flight activities beyond the relatively safe aerodrome perimeter. Low level and terrain-following operations are often challenged by a variety of natural and man-made obstacles. The significant number of obstacle strike accidents recorded is a major concern both for aircraft operators and for people on the ground [1, 2]. Reduced atmospheric visibility due to adverse weather conditions is frequently a contributing factor in such accidents, but the difficult identification of small-size obstacles such as wires has led to accidents and incidents even in clear sky conditions. Significant development activities are specifically addressing the integration of lidar obstacle warning, detection, and avoidance systems for granting separation maintenance and collision avoidance capabilities [3-9].
Table 1 compares a number of sensor technologies for Obstacle Warning System (OWS) applications in small-to-medium size UAVs. Unfortunately, state-of-the-art radar is not capable of detecting small natural and man-made obstacles such as trees, power line cables and poles. The outstanding angular resolution and accuracy characteristics of Light Detection and Ranging (LIDAR), as well as its good detection performance in a wide range of incidence angles and weather conditions provide an ideal
solution for obstacle detection and avoidance [2].
One of the key challenges encountered by the aviation community for integration of Unmanned Aircraft Systems (UAS) into non-segregated airspace is the provision of a certifiable Sense-and-Avoid (SAA) capability. SAA can be defined as the automatic detection of possible conflicts by the UAS and the resolution of any existing collision threats by accomplishing safe avoidance manoeuvres. The maturity of SAA techniques and enabling technologies is considered low when viewed in the perspective of civil airworthiness regulations for manned aircraft, raising concerns to certification authorities and airspace users [8]. With the growing adoption of UAS for several civil, commercial and scientific applications, there is a need to certify UAS according to established national and international standards [9]. Such SAA systems will provide UAS the capability to consistently and reliably perform equally or even to exceed the see-and-avoid performance of a human pilot in manned aircraft while allowing a seamless integration of unmanned aircraft in the Air Traffic Management (ATM) network. Research efforts are primarily concentrated on adopting LIDAR sensors for small-to-medium size UAV platforms as one of the most accurate non-cooperative SAA sensors. The LIDAR Obstacle Warning and Avoidance System (LOWAS) for UAS is a low-weight/volume navigation aid system specifically designed to detect potentially dangerous ground and aerial obstacles placed in or nearby the planned flight trajectory and to provide timely warnings to the crew in order to implement effective avoidance manoeuvres.
For the complete paper by Ramasamy et al CLCIK HERE.
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