脉间参差间隔波形的无模糊多普勒谱估计

    Ambiguity-Free Doppler Spectrum Estimation for Inter-Pulse Staggered Waveforms

    • 摘要: 针对机载低重频(pulse repetition frequency, PRF)的脉冲多普勒(pulse-Doppler, PD)雷达,提出一种基于脉间参差间隔波形的单相干处理间隔(coherent processing interval, CPI)解多普勒模糊方法,以缩短固定空域的探测时间。首先,建立脉间参差间隔波形的慢时间回波模型,并分析广义相关滤波器条件下的杂波泄漏机理。随后,给出基于最小方差无失真响应(minimum variance distortionless response, MVDR)准则的自适应多普勒处理方法;针对机载场景中协方差矩阵估计样本受限的问题,进一步提出一种迭代自适应处理方法,以减弱对大量同质训练样本的依赖。最后,为降低计算复杂度,利用杂波先验分布信息构造低维多普勒子空间,实现降维处理。仿真结果表明,所提方法能够有效抑制折叠杂波泄漏,并提高强杂波背景下的无模糊多普勒谱估计性能。

       

      Abstract: For an airborne low-pulse repetition frequency (PRF) pulse-Doppler (PD) radar, a single-coherent-processing-interval (CPI) Doppler ambiguity resolution method based on inter-pulse staggered waveforms is proposed to shorten the dwell time required for a fixed surveillance sector. First, a slow-time echo model for the inter-pulse staggered waveform is established, and the mechanism of clutter leakage under generalized correlation filtering is analyzed. Then, an adaptive Doppler processing method based on the minimum variance distortionless response (MVDR) criterion is presented. To address the problem of limited training samples for covariance matrix estimation in airborne scenarios, an iterative adaptive processing method is further proposed to reduce the dependence on a large number of homogeneous training samples. Finally, to reduce the computational complexity, a low-dimensional Doppler subspace is constructed by exploiting prior clutter distribution information, and a reduced-dimension processing scheme is developed. Simulation results show that the proposed method can effectively suppress folded clutter leakage and improve the performance of ambiguity-free Doppler spectrum estimation in strong clutter backgrounds.

       

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