电讯技术2025，Vol.65Issue(2)：313-321,9.DOI:10.20079/j.issn.1001-893x.230927002
基于拉普拉斯混合模型的航迹抗差关联方法
An Anti-bias Track Association Algorithm Based on Laplace Mixture Model
摘要
Abstract
In order to solve the robustness issue of track association in complex environments with system errors and incomplete consistency with reported targets in networked radar system,according to the non-rigid point set registration theory,an association method which combines the neighborhood structural information of the track and the Laplace Mixture Model(LMM)is proposed.The trajectories of non-cooperative detection targets,deemed as outliers,are initially modeled by a more robust LMM.Then,a local similarity measurement is defined to calculate the similarity of track neighborhood structures to determine the weights of Laplace components,and the closed-form solution of the LMM is obtained through the Expectation-Maximization(EM)algorithm.Finally,a classical assignment method is employed to make track association decisions based on the posterior probability matrix obtained from the expectation step.Simulation results demonstrate that the proposed algorithm achieves high association accuracy and robustness when confronted with various complex environments,such as different system errors,detection probabilities,and target distribution densities.关键词
组网雷达系统/航迹关联/拉普拉斯混合模型/局部相似性测度/EM算法Key words
networked radar system/track association/Laplace mixture model/local similarity measurement/EM algorithm分类
信息技术与安全科学引用本文复制引用
韦春玲,吴孙勇,刘锦新,余润华..基于拉普拉斯混合模型的航迹抗差关联方法[J].电讯技术,2025,65(2):313-321,9.基金项目
国家自然科学基金资助项目(62371149,62263007) （62371149,62263007）
广西科技重大专项(AA20302001) （AA20302001）
广西无线宽带通信与信号处理重点实验室基金(GXKL06190117) （GXKL06190117）
认知无线电与信息处理教育部重点实验室基金(CRKL180106,CRKL220107,CRKL210101) （CRKL180106,CRKL220107,CRKL210101）
桂林电子科技大学校级研究生创新项目(2023YCXS108) （2023YCXS108）
