MMV模型下无源双基雷达低空目标微动特征提取

Micro-Doppler feature extraction of low-altitude targets based on MMV model under passive bistasic radar

基于频分复用模式下的正交频分复用信号外辐射源双基雷达模型,对带旋翼低空目标进行回波建模,得到目标微动参数与回波微多普勒参数间的关系.在此基础上,针对数据缺损条件下的低空目标回波,采用基于多重观测矢量(MMV)模型并结合稀疏重构方法,实现了目标微动特征参数的提取.仿真结果表明:针对低空微动目标,该方法提取参数的均方误差可达到10-3量级.相比于单重观测矢量模型,该方法能更加准确实现数据缺损条件下的微动参数提取,耗时随模型重数的增加而减少,可为实际环境下低空目标微多普勒特征提取提供参考和借鉴.

Based on the passive bistatic radar under orthogonal frequency division multiplexing signal in frequency division multiplexing mode,the echo of low-altitude target with rotors was modeled,and the relationship between target micro motion parameters and echo micro-Doppler curve features was obtained.On this basis,aiming at the echo of low altitude targets under the condition of data defect,the multiple measurement vector(MMV)model and sparse reconstruction method were used to extract the target micro motion features.The simulation results show that the mean square error of the parameters extracted by this method can reach 10-3 magnitude.Compared with the single measurement vector model,this method can more accurately extract the micro motion features under the condition of data defect,and the time cost decreases with the increase of the model weight,which provides a reference for the micro-Doppler feature extraction of low altitude targets in real circumstance.