摘要
针对无源协同定位系统中低可观测目标的航迹初始及维持问题,提出一种基于遗传算法的极大似然概率多假设的多基站无源协同定位方法。首先,建立多基站无源协同定位系统数学模型。其次,提出基于极大似然概率多假设的无源协同定位航迹初始算法,并首次利用遗传算法解决极大似然概率多假设中的优化求解问题,以提高目标检测跟踪性能。最后,通过滑窗法实现航迹维持。仿真结果表明,所提方法能够有效解决多基站无源协同定位系统中低可观测目标的航迹初始及维持问题。
In order to track very low observable likelihood targets with a multistatic passive coherent location proposed.system,a The genetic algorithm consist maximum three probabilistic multi-hypothesis method target is contributions of aspects.First,the mathematical model for detection and tracking is established.Second,a maximum likelihood probabilistic multi-hypothesis method hence is the presented estimation Simulation for track initialization,and the genetic algorithm is used for in optimization a and performance.results Last,the the track maintenance the is achieved sliding window manner.show effectiveness of proposed algorithm.
出处
《火力与指挥控制》
CSCD
北大核心
2017年第7期29-32,38,共5页
Fire Control & Command Control
基金
国家自然科学基金资助项目(61573123)
关键词
无源协同定位
低可观测目标
航迹初始
极大似然概率多假设
遗传算法
multistatic passive coherent location
low observable targets
track initialization
maximum likelihood probabilistic multi-hypothesis
genetic algorithm
