Radar Target Data Association with Amplitude and Tracking Information
Hao Tong, Tian Liu, Shenghua Zhou, Xiaojun Peng · 2021 CIE International Conference on Radar (Radar) · 2021
In the radar data association problem, amplitude and state information of target returns are widely used in tracking algorithms, and typically many methods combine them. However, except from uniting them, constructing the correlation model among different instants returns is rarely considered. It is known that there is numerous information in radar target returns, but it is complicated to make comprehensive consideration. In this paper, we not only approximate the joint distribution of squared amplitudes based on the Copula function but unite the state information of target returns. Regarding squared amplitudes as statistics to derive the conditional probability density function (PDF), combine with state information to predict the scope of latter instant statistics, which can be used to improve certain anti-interference performance in the target-detection-during-tracking problem. Furthermore, this algorithm will consider about kinematic state and give the most reasonable measurement the highest possibility among the numerous ones radar receiving. And numerical results will be utilized to verify the effectiveness of the proposed method.