Joint tracking and classification on aerodynamic model and RCS by ground-based passive radar
Long Xu, Kun Zhan, Hong Xu Jiang, Liang Bai, Mengjie Wu · 2014
For the ground-based passive radar to monitor low altitude threat targets, the radio frequency modulation (FM) signals transmitted by the broadcast stations is exploited, and an effective joint tracking and classification (JTC) algorithm based on aerodynamic model and radar cross section (RCS) is presented. The aerodynamic equations are used as motion model, and target classification is made possible by the inclusion of RCS in the measurement vector. Thus, tracking and classification are closely coupled, giving full play to the advantages of joint tracking and classification. Our algorithm is implemented by interacting multiple model regularized particle filter (IMMRPF) and simulations show the superiority of our algorithm.