UAS Collision Warning and Passive Sensor Fusion Algorithms for Multiple Acoustic Transient Emitter Localization

This dissertation considers two important topics in the area of estimation, target tracking and sensor fusion. The first topic is closest point of approach (CPA) prediction for unmanned aircraft systems (UAS) collision warning and the second topic is passive sensor fusion for multiple acoustic transient emitter localization. To operate within a controlled airspace, UAS must have the capability to sense and avoid collisions with non-cooperative aircraft. This dissertation presents an inexpensive system design and develops an algorithm for estimating the CPA between the ownship and the intruder and a collision warning scheme using only bistatic range and range rate measurements from a multistatic radar. Since it is vital for soldiers to be able to accurately localize sources of hostile fire in the battlefield for situational awareness and threat assessment, this dissertation develops both centralized and distributed passive sensor fusion algorithms to accurately estimate the number of acoustic transient emitters and their locations using bearing and time of arrival measurements