基于伪线性卡尔曼滤波的两站红外无源定位及跟踪技术

Pseudo-linear Kalman filter based passive location and tracking techniques by two infrared stations

建立了目标的两站红外搜索与跟踪系统的伪线性观测模型,基于该模型提出了运动目标的伪线性卡尔曼滤波算法.该算法利用伪线性方程组获得滤波器的初值,从而提高了滤波器的跟踪精度和速度.分别采用伪线性卡尔曼滤波器与推广卡尔曼滤波器对目标进行定位及跟踪的仿真结果表明:在跟踪初始阶段,伪线性卡尔曼滤波的跟踪精度明显优于推广卡尔曼滤波.在近距离范围,不论目标是匀速还是机动运动,两者的跟踪精度都非常高.在远距离范围,当目标机动时,伪线性卡尔曼滤波的跟踪精度明显优于推广卡尔曼滤波;当目标匀速运动时,推广卡尔曼滤波的跟踪精度略优于伪线性卡尔曼滤波.从整个仿真过程可以看出,目标的运动形式对推广卡尔曼滤波性能的影响是非常明显的,而对伪线性卡尔曼滤波性能的影响则很小.

A PLKF (pseudo-linear Kalman filter) is presented for tracking a moving target using two stations of IRST systems. The initial value of the filter is attained from the pseudo-linear equations, which improves the tracking accuracy and speed of the filter. Results of the simulation of tracking a maneuvering target by PLKF and EKF (extended Kalman filter) illustrate that at the beginning of tracking, the tracking accuracy of PLKF is better than that of EKF; in the near range of the tracking, both the tracking accuracy of PLKF and EKF are better whether the target is maneuvering or not; in the far range of the tracking, the tracking accuracy of PLKF is better than that of EKF when the target maneuvers, but is somewhat worse when the target moves at a constant velocity. From the view of global range, the influence of the moving state of the target is very strong on the tracking accuracy of the EKF and is weak on that of PLKF.