无需辅助数据的分布式目标自适应检测器

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...

Distributed Target Detection Without Secondary Data

The high resolution radar target echoes can be referred to as a distributed target. In the non-Gaussian background, the adaptive detection of a distributed target is investigated without secondary data. Firstly, the set of target scatterers are estimated roughly by means of the order statistics detection theory and the recursive estimator of covariance matrix. Then, an approximately maximum likelihood estimate of the covariance matrix is acquired by the recursive estimator. Furthermore, an adaptive detector without secondary data(ADWSD)is derived for the distributed target. The proposed detector is almost of constant false alarm rate for a non-Gaussian clutter. In addition, the ADWSD performs much better than the existing detector of modified generalized likelihood ratio test. Finally, the simulation results show that, as the clutter spikiness increases, the detection performance of ADWSD is improved, especially for the low signal-to-clutter ratio scenarios; and it is also robust with respect to different correlations of clutter.