基于动态规划的多站雷达协同探测信号级融合算法

Multiple Radar Cooperative Detection Signal Level Fusion Algorithm Based on Dynamic Programming

多站雷达协同探测系统具有抗摧毁、抗干扰、探测性能改善空间大等优势,因此近年来成为国际雷达界的前沿研究热点。目前,许多学者的研究主要集中在数据级多站雷达信息融合,该算法可以有效提高跟踪的稳定性,但是并不能有效地提升雷达的探测距离。针对以上缺点,本文将多站雷达多普勒滤波后的数据作为动态规划的数据输入,然后采用动态规划算法对该数据进行非相参融合,这样可以大大提高信噪比,实现对低可观测目标的有效检测,最后对算法性能进行了理论分析。仿真表明了该算法的可行性和稳健性。

Multiple radar signal level fusion detection has great advantages on the resistance to destruction and interference and the great improvement of the detection performance,so it receives much attention in international radar research field.Recently,the research of many researchers focuses on the multiple radar data level fusion,which can improve the tracking stability,but it can't effectively improve the radar detection distance.Based on the above-mentioned shortcomings,the multiple radar data after the Doppler filtering are used as the data input.And then the Dynamic Programming(DP)algorithm is performed to the data to realize signal level non-coherent fusion,which can obviously improve the signal-to-noise ratio and detect the low observable targets.Finally,the performance of the algorithm is analyzed theoretically.The simulation shows the feasibility and stability of this algorithm in improving the detection performance of weak targets.