Target tracking with phased array radar by using adaptive update rate

Thesis Type: Postgraduate

Institution Of The Thesis: Orta Doğu Teknik Üniversitesi, Faculty of Engineering, Department of Electrical and Electronics Engineering, Turkey

Approval Date: 2010




In radar target tracking problems, it may be required to use adaptive update rate in order to maintain the tracking accuracy while allowing the radar to use its resources economically at the same time. This is generally the case if the target trajectory has maneuvering segments and in such a case the use of adaptive update time interval algorithms for estimation of the target state may enhance the tracking accuracy. Conventionally, fixed track update time interval is used in radar target tracking due to the traditional nature of mechanically steerable radars. In this thesis, as an application to phased array radar, the adaptive update rate algorithm approach developed in literature for Alpha-Beta filter is extended to Kalman filter. A survey over relevant adaptive update rate algorithms used previously in literature on radar target tracking is presented including aspects related to the flexibility of these algorithms for the tracking filter. The investigation of the adaptive update rate algorithms is carried out for the Kalman filter for the single target tracking problem where the target has a 90° maneuvering segment in its trajectory. In this trajectory, the starting and final time instants of the single maneuver are specified clearly, which is important in the assessment of the algorithm performances. The effects of incorporating the variable update time interval into target tracking problem are presented and compared for several different test cases.