Adaptive waveform optimization algorithm based on UWB MIMO radar

C. Ji, Yaoliang Song, Qiang Du
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Abstract

For the issue of deterioration in detection performance caused by dynamically changing environment in UWB MIMO radar, we propose a novel adaptive waveform design which is aimed to improve the ability of discriminating target and clutter from the radar scene. Firstly, we consider using a Dirichlet process mixture model (DPMM)-based clustering approach to discriminate individual extended targets. Then we apply the minimization mutual-information (MI) strategy between individual targets echoes to select the best waveform from an ensemble of UWB waveforms for transmission. With this approach, the radar system constantly learns about its surroundings and adopts its operational mode accordingly based upon the MI minimization criterion. Finally, simulation results demonstrate that the optimal design method brings an improvement in the target detection ability and target discrimination capability.
基于UWB MIMO雷达的自适应波形优化算法
针对超宽带MIMO雷达中环境动态变化导致探测性能下降的问题,提出了一种新的自适应波形设计,旨在提高雷达场景中目标和杂波的区分能力。首先,我们考虑使用基于Dirichlet过程混合模型(DPMM)的聚类方法来区分单个扩展目标。然后应用目标回波间互信息最小化策略从一组超宽带波形中选择最佳波形进行传输。通过这种方法,雷达系统不断了解周围环境,并根据MI最小化准则采取相应的工作模式。仿真结果表明,该优化设计方法提高了目标检测能力和目标识别能力。
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