摘要
针对雷达的目标检测概率和跟踪精度随着目标距离的增大而降低的问题,提出了一种基于门限体积最小准则的认知雷达的波形选择方法。该方法在高斯噪声、线性运动目标跟踪方法的基础上,通过测量噪声与发射波形之间的关系,在经典卡尔曼滤波算法的框架中增加了波形选择模块,来实现对跟踪波形的调节。仿真结果表明,该方法能够明显地提高雷达的跟踪性能。
Aiming at the issue about the target detection probability and tracking accuracy of radar decrease with the increase of the target distance, a new selection method of cognitive radar waveforms based on the minimization of criterion gate volume is proposed in this paper. The waveform selection block is added in the classical Kalman filter to adjust the tracking waveforms through the relationship between the measurement noise and the transmitting waveforms on the basis of the Gauss noise and the tracking menthods of the linear motion targets. The simulation results show that this method can improve the tracking performance of radar apparently.
出处
《微型机与应用》
2015年第9期62-64,共3页
Microcomputer & Its Applications
关键词
认知雷达
卡尔曼滤波
门限体积最小准则
cognitive radar
Kalman filter
the minimization of criterion gate volume
