基于波形设计的弹载雷达回波目标识别优化

The Anti-Jamming Waveform Optimization Algorithm for the Missile-Borne Radar Under Clutter Using Mutual Information Criterion

弹载雷达回波目标识别是导弹制导的关键环节,接收机通过提取回波中目标信息并将其反馈给自动驾驶系统以导引弹体飞向目标。针对复杂电磁环境中弹载雷达回波掺杂杂波和干扰导致回波中目标信息难以提取,造成导弹制导性能降低的问题,基于发射波形设计提出了一种噪声、杂波和干扰影响下的弹载雷达回波目标识别优化方法,通过拉格朗日乘子法设计最大化互信息量时的最优发射波形表达式,利用泰勒级数将表达式化简为杂波和干扰因式的形式,同时实现信息数据快速处理。实验结果表明,波形优化算法能够针对目标频率响应、杂波和干扰的相对强度合理分配发射信号的频域能量,以补偿干扰、杂波影响带来的互信息量损耗,并缩短信息处理时间。

Target recognition of missile- borne radar echo is a key part of the missile＇s guiding system. The receivers fetch information of target from radar echo to guide the missile to target by autopilot. To solve the problem that the target information of missile- borne radar echo become difficult to fetch and the guiding performance reduces when the echo is mixed with clutter and jamming in the complex electromagnetic environment,an optimized target recognition algorithm in noise,clutter and jamming based on waveform design is proposed. This algorithm maximizes the mutual information between the target ensemble and the echo signal using Lagrangian multiplier method and then is simplified by Taylor series to make the signal easier to analyze and process. Simulation results show that this algorithm could redistribute the energy of the signal on the frequency to compensate the mutual information loss caused by clutter and jamming and shorten the signal processing time.