雷达学报Issue(1)：86-96,11.DOI:10.3724/SP.J.1300.2013.20079
基于贝叶斯框架的空间群目标跟踪技术
Tracking of Group Space Objects within Bayesian Framework
摘要
Abstract
It is imperative to efficiently track and catalogue the extensive dense group of space objects for space surveillance. As the main instrument for Low Earth Orbit (LEO) space surveillance, ground-based radar systems are usually limited by their resolving power while tracking small, but very dense clusters of space debris. Thus, the information obtained regarding target detection and observation will be seriously compromised, making the traditional tracking method inefficient. Therefore, we conceived the concept of group tracking. The overall motional tendency of a group’s objects is particularly focused, while individual objects are in effect simultaneously tracked. The tracking procedure is based on the Bayesian framework. According to the restriction among the group center and observations of multi-targets, the reconstruction of the number of targets and estimation of individual trajectories can be greatly improved with respect to the accuracy and robustness in the case of high miss alarm. The Markov Chain Monte Carlo Particle (MCMC-Particle) algorithm is utilized to solve the Bayesian integral problem. Finally, the simulation of the tracking of group space objects is carried out to validate the efficiency of the proposed method.关键词
空间监测/群目标/空间目标/轨道跟踪/贝叶斯框架Key words
Space surveillance/Group objects/Space object/Orbit tracking/Bayesian framework分类
信息技术与安全科学引用本文复制引用
黄剑,胡卫东..基于贝叶斯框架的空间群目标跟踪技术[J].雷达学报,2013,(1):86-96,11.基金项目
国家高技术研究发展计划项目(863计划)资助课题 （863计划）
