相关杂波背景下的认知雷达跟踪波形设计

Adaptive Waveform Design for Cognitive Radar Tracking in the Presence of Signal-dependent Clutter

针对在相关杂波背景下,如何通过发射波形的优化以提高雷达对运动扩展目标的跟踪精度问题,文中建立了跟踪模型,然后通过卡尔曼滤波实现了对目标的跟踪和预测,进而基于最小化滤波误差建立了波形优化模型,最后对问题模型进行了分析求解。结果表明:白噪声背景中,伪随机信号相对于其它波形在跟踪性能上具有明显的优势。计算机仿真结果验证了理论的正确性。

In view of how to improve tracking performance by waveform optimization in signal-dependent clutter background, he tracking model was established. The target impulse response was forecasted and filtered by Kalman filter and the optimization goal was designed based on the minimum filtering error. Finally, this problem was analyzed and solved and the results show that in the white noise background, the pseudorandom waveform is proved to be the optimum waveform. Computer simulation results verify the correctness of the theory.