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由于现有的非均匀检测器(NHD)普遍存在运算量大、难以实时实现等问题,文中提出了一种基于幅相信息的和差波束非均匀检测器。该方法首先采用恒虚警技术(CFAR)检测出强目标和强杂波信号,然后剔除强目标并对强杂波信号进行加权处理,以改善距离样本的均匀性,最后利用常规自适应算法抑制杂波,完成对弱目标的检测。理论分析和对实测数据的处理表明,该检测器能有效地检测出动目标,提高输出信噪杂比,并具有运算量小,易于工程实现等优点。
Since existing non-uniform detectors (NHDs) generally have large computational complexity and are difficult to be implemented in real time, a nonuniformity and difference beam detector based on amplitude and phase information is proposed in this paper. Firstly, the CFAR method is used to detect strong targets and strong clutter signals, and then the strong targets are eliminated and the strong clutter signals are weighted to improve the uniformity of distance samples. Finally, the conventional adaptive algorithm is used to suppress Clutter, to complete the detection of weak targets. Theoretical analysis and processing of the measured data show that the detector can effectively detect the moving target, improve the output signal to noise ratio, and has the advantages of low computational complexity and easy engineering.