针对脉冲多普勒(PD)雷达在跟踪低信噪比目标时,检测概率的降低会导致数据更新率降低,从而难以保证目标跟踪的稳定性的问题,文中提出了一种新的目标跟踪检测模型与算法来提高跟踪目标的测量更新概率。该方法通过利用目标跟踪过程中滤波预测信息提供的检测先验信息,设置一种最佳门限进行目标信号的检测,其中先验信息主要是目标在各个检测单元的预测存在概率。仿真结果表明,该方法有效提高了跟踪过程中雷达对低信噪比目标的检测概率,并且对跟踪精度有一定的改善。

When pulse Doppler (PD) radar tracks the target with low SNR, the decrease of detection probability will lead to the decrease of data update rate, so it is difficult to ensure the stability of target tracking. Therefore, this paper proposes a new target tracking detection model and algorithm to improve the measurement update probability of tracking target. In this method, an optimal threshold is set to detect the target signal by using the detection prior information provided by the filtering and prediction information in the process of target tracking. The prior information is mainly the prediction probability of the target in each detection unit. The simulation results show that this method can effectively improve the detection probability of radar for low SNR targets in the tracking process, and improve the tracking accuracy to a certain extent.

TN957