Passive Collision Detection for UAV Sense and Avoid Systems

The Department of Defense (DoD) has invested heavily and successfully in Unmanned Aerial Systems (UAS) technology. Currently, UAS face limitations on their utilization in civil airspace because they do not have the capability to sense and avoid (SAA) other air traffic. Ability to detect collisions with low False Alarm and False Negative Rates are crucial for SAA. Moreover, in several situations use of only passive sensors is necessary. To address this problem, UtopiaCompression in collaboration with the University of California, Los Angeles proposes to develop a Collision Detection system based on passive Electro-optical or Infra-red sensors. We show that it is possible to extract sufficient information from the images to completely observe the states of an approaching obstacle. We then propose Collision Detection methodologies based on statistical decision theory to decide whether or not a collision is going to occur. The desired False Alarm and False Negative Rates are input parameters to the algorithm.