基于相似性传播的天波雷达多路径量测聚类

The multi-layer structure of the ionosphere can support several signal propagation paths between the sky-wave Over-The-Horizon Radar (OTHR) and targets, often giving rise to multipath measurements for a single target. The problem of multipath measurements clustering for OTHR is considered, which needs to solve the problems of multipath measurements recognition and measurements clustering at the same time. OTHR measurements model assumes that a target can generate at most one measurement through an ionospheric propagation path, and multipath clustering constraints need to be considered. In this paper, affinity propagation clustering is extended to multipath constraint model, and a new multipath constraint affinity propagation clustering algorithm is proposed. The algorithm transforms the clustering problem into an inference problem by constructing the probabilistic graphical model of multipath measurements clustering, and uses the max-sum belief propagation to approximate the maximum a posteriori probability of the clustering matrix. The advantages of the algorithm include that it identifies automatically the number of clusters, and the computational complexity scales quadratically in the number of measurements and the number of propagation paths. Simulation results show that, the proposed method can outperform multiple hypothesis multipath clustering algorithm.