基于线性约束最小方差原则的稳健快速自适应脉冲压缩方法

针对线性调频信号在距离单元内的回波采样点与目标点失配, 即采样失配的情况下, 自适应脉冲压缩性能下降的问题, 对快速自适应脉冲压缩(fast adaptive pulse compression, FAPC)方法进行改进, 提出一种基于线性约束最小方差(linearly constrained minimum variance, LCMV)原则的连续分块FAPC (contiguous block FAPC, CFAPC)方法。该方法将自适应波束形成方法类比到自适应脉冲压缩滤波方法中, 首先在最小方差无畸变响应(minimum variance distortionless response, MVDR)原则保持增益的前提下增加零点约束条件, 加宽零点凹口的宽度; 而后对分块的协方差矩阵设置置零条件, 抑制旁瓣能量, 实现在采样失配情况下保持稳健的目的。实验结果表明, 在脉内多普勒频移和采样失配同时存在的情况下, 所提方法可以更好地抑制目标的距离旁瓣, 具有较好的稳健性。

Robust fast adaptive pulse compression method based on linearly constrained minimum variance principle

The performance of adaptive pulse compression degrades when echo sampling point of the linear frequency modulation (LFM) signals mismatched with the target point in a range cell (namely sampling mismatch). In order to solve the problem, this paper improves the fast adaptive pulse compression (FAPC) method and proposes a new continuous block FAPC (CFAPC) method which is based on linearly constrained minimum variance (LCMV) principle.The method analogizes the adaptive beamforming method to the adaptive pulse compression filtering method, firstly utilizes minimum variance distortion response (MVDR) principle to keep the target's gain and sets the zeroing constraints to widen the width of the energy's notch; then applies another zeroing constraint to block covariance matrix to further suppress the energy of sidelobes and maintain the robustness when sampling mismatch happens. The experiments show that the proposed method can better suppress the range sidelobes of the target and it is more robust when theintra-pulse Doppler shift and sampling mismatch exist simultaneously.