基于位置和速度的点状运动目标Bayes跟踪

Bayes Tracking for Moving Point Target Based on Position and Velocity

采用结合概率数据关联的卡尔曼滤波方法,研究一种基于位置、速度信息的微弱点动目标Bayes跟踪技术。其关键是在跟踪区域检测时,检测器以Basyes模式进行工作,检测门限随目标先验概率比变化。提出一种新的门限计算方法。与基于恒虚警概率准则的跟踪技术相比,跟踪过程中检测到的虚警目标明显减少,仿真结果验证了该算法的实时性与精确性。

This paper studies the Bayes weak point moving target tracking technology by using probabilistic data associated with the Kalman filter method, which is based on position, velocity information. The key is in the region of tracking, detector works in Basyes mode, detection threshold changes with goal＇s priori probability change. A new threshold calculation is proposed. Based on CFAR（CFAR probability） guidelines tracking technologies, the process of detection to track the number of false alarm target is decreased. Simulation results show that it is a real-time and accurate algorithm.