基于证据理论的敌我识别目标关联方法OA

To address the problem of association between IFF targets and radar targets in scenarios dense target scenarios,an association method based on evidence theory is proposed.A positional correlation model is established.Evidence and its basic probability assignment(BPA)are generated based on the azimuth and range measurement capabilities of the radar and IFF interrogator,as well as data from multiple measurements.Evidence derived from multiple measurements of the same target is combined using the Dempster rule to construct a combined evidence set.The association of all targets is completed sequentially based on a maximum value search within the combined evidence set.The simulation results demonstrate that,the proposed method achieves higher association accuracy than the nearest neighbor(NN)method at equivalent time complexity.Furthermore,compared to the Kuhn-Munkres(KM)algorithm,the proposed method achieves higher accuracy in most dense target scenarios with lower time complexity.