基于信息熵的分布式MIMO雷达回波相位补偿与相参积累方法

针对分布式多输入多输出(Multiple-input Multiple-output,MIMO)雷达回波信号相参积累问题,提出了一种利用信息熵作为优化准则的多节点回波相位补偿与相参积累方法。采用正交频分复用线性调频信号(Orthogonal Frequency Division Multiplexing Linear Frequency Modulated Signal,OFDM-LFM)作为发射波形,通过匹配滤波完成耦合回波分离和脉冲压缩,然后在频域进行频移操作消除步进频的相位影响,利用信息熵估计距离对齐后的多节点回波相位差,随后构建相应的相位补偿函数,进而完成各节点回波的相位差异补偿,最终得到分布式MIMO雷达多节点回波信号的相参积累结果。所提方法可同时处理多个节点回波,仿真实验验证了该方法的有效性。 

Entropy-based phase compensation and coherent integration method for distributed MIMO radar

The coherent accumulation problem of distributed multiple-input multiple-output (MIMO) radar was studied. We proposed a phase compensation and coherent accumulation algorithm of multi-node echoes, which used information entropy as an optimization criterion. Orthogonal frequency division multiplexing linear frequency modulated signal (OFDM-LFM) was used as emission waveforms. The signal separation of coupling echoes and pulse compression were completed by matched filtering. In order to eliminate the impact of step frequency, we took frequency shift operation in the frequency domain. Information entropy function of the range alignment echoes was used to estimate the phase parameters, then we constructed the phase compensated function to compensate the phase differences of multi-node echoes. Finally, We obtained the coherent accumulation result of distributed MIMO radar. The proposed method can deal with the echoes of multiple nodes at the same time, simulation results are proided to verity the validity of the proposed method.