Development of Sense and Avoid system based on multi sensor integration for unmanned vehicle system

[摘要] Unmanned Aerial Vehicles (UAV) have a great potential to replace manned aircraft in many tasks or missions. However, in order to allow these UAVs to execute their mission appropriately and especially to deploy them in national or civil airspace, UAVs must have a proper and reliable collision avoidance system. This avoidance system is known as a Sense and avoidance (SAA) system. The purpose of the system is to detect any obstacles either in static or moving condition and respond with proper avoidance maneuvers in order to maintain minimum separation distances. Therefore the research project deals with the development of a unique SAA system which is based on multisensory integration. In particular, it focuses on sensors, processing logic and hardware required on the UAVs to acquire situational awareness. Dissimilar kind of sensors which is optical and laser type is proposed to be employed, so that weaknesses from each individual sensor can be tolerated. Proper logics or algorithm related to the fusion of output from each sensor will also be studied.The combination of Extended KalmanFilter (EKF) and Differential Evolution(DE) method is used for the purpose of development of detection and tracking system which considered to be the main challenges in SAA system development. Subsequently, once the algorithms are put together, including maneuvers avoidance technique algorithm, the developed SAA system will be experimentally tested in order to validate and evaluate the overall capability of the system.

[发布机构] Department of Mechanical Engineering, Kulliyyah of Engineering, International Islamic University, Malaysia, P.O.Box 10, Kuala Lumpur; 50728, Malaysia^1;Faculty of Mechanical and Manufacturing Engineering, Universiti Tun Hussein Onn Malaysia, Malaysia^2

[效力级别] 无线电电子学 [学科分类] 航空航天科学

[关键词] Collision avoidance systems;Detection and tracking;Differential Evolution;Multi-sensor integrations;Multisensory integration;Sense and avoid systems;Situational awareness;Unmanned vehicle systems