基于多层感知器的外辐射源雷达多帧联合检测

针对复杂杂波背景下“低慢小”目标检测问题，发展了一种基于多层感知器（multi-layer perceptron, MLP）的检测器. 该检测器联合多场距离多普勒（range-Doppler, RD）谱作为观测空间，在每一场RD谱上取沿距离维滑窗的n个（通常取n=3）单元构造观测向量. 为评估该检测器实际性能，开展了无人机探测实验. 无人机这类“低慢小”目标通常出现在RD谱上邻近零多普勒的区域，该区域的杂波会影响目标检测. 实验结果表明，所提MLP检测器既能在高斯杂波环境下很好地逼近最优似然比（likelihood ratio, LR）检测器，同时，在难以得到杂波分布模型解析表达式的情况下，检测性能优于统计模型失配的LR检测器.

Multi-frame joint detection for passive radar based on multi-layer perceptron

For the problem of target detection of the low-altitude, slow-speed and small target (Lss-target) under complex clutter, a multi-layer perceptron (MLP) detector is developed in this paper. The detector combines the multi-frame range-Doppler (RD) spectrum as the observation space, and takes n (usually n=3) units along the range dimensional sliding window on each RD spectrum to construct the observation vector. To evaluate the performance of the detector, an unmanned aerial vehicle (UAV) detection experiment is carried out. LSS-targets such as UAVs usually appear near the zero-doppler region on the RD spectrum, clutter on which has a great impact on target detection. Experimental results show that the proposed MLP detector can approximate the likelihood ratio (LR) detector well in the Gaussian clutter environment. Meanwhile, it has better detection performance than the mismatched LR detector when the analytical solution for clutter distribution model is difficult to be obtained.