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在非高斯背景和没有辅助数据的条件下,研究了高分辨率雷达分布式目标的自适应检测问题。首先采用有序检测理论和协方差矩阵的迭代估计方法粗略估计散射点集合,进一步利用迭代估计方法获得协方差矩阵的近似最大似然估计,提出了无需辅助数据的自适应检测器(ADWSD)。ADWSD在非高斯背景下具有近似恒虚警率特性,且检测性能远好于修正的广义似然比检测器。仿真分析表明,随着杂波尖峰的增加,ADWSD的检测性能得到提高,且对不同的杂波相关性具有很好的鲁棒性。
Under non-Gaussian background and without auxiliary data, adaptive detection of distributed targets in high-resolution radar is studied. First, an iterative estimation method based on ordered detection theory and covariance matrix is used to roughly estimate the set of scattering points. The iterative estimation method is used to obtain the approximate maximum likelihood estimation of the covariance matrix. An adaptive detector without auxiliary data (ADWSD) is proposed. ADWSD has approximate constant false alarm rate in non-Gaussian background, and the detection performance is far better than the modified generalized likelihood ratio detector. The simulation results show that with the increase of clutter spikes, the detection performance of ADWSD is improved and it has good robustness to different clutter correlations.