Multi-radar Signal Level Fusion Detection Algorithm based on Fast Time Accumulation - Xuan, Fang; Lin, Zhou (2020 IEEE International Conference on Information Technology,Big Data and Artificial Intelligence (ICIBA), 2020)
Aiming at the problem of multi-radar joint detection, the performance of non-coherent accumulation detection algorithm under fast time sampling is analyzed. In order to improve the detection performance, two fast time phase-coherent accumulation detection algorithms are designed based on Generalized Likelihood Ratio Test (GLRT): 1. Fusion detection algorithm based on rapid phase-coherent accumulation in a single station;2. Detection algorithm based on overall signal fusion. From the perspective of theory and simulation, the performance of the two improved methods for detecting low-speed or stationary targets is better than that of the non-coherent accumulation detection method. Method 1 is suitable for distributed networking, while method 2 is suitable for centralized networking. The improved algorithm can extract target Doppler features while fusion detection, and provide information for target recognition and motion analysis.