摘要
针对分布式被动传感器网的特点,提出了一种异步采样条件下机动目标跟踪方法。该方法采用交互式多模型概率数据互联滤波器跟踪机动目标。为启动滤波器,采用最大似然法估计目标初始状态;为适应异步观测条件,提出了马尔可夫转移概率计算方法。仿真实验表明,在分布式被动传感器网中采用该算法能有效进行机动目标跟踪。
Aiming at the nature of the distributed passive sensor network, a method for maneuvering target tracking under asynchronous sampling condition is proposed, which tracks maneuvering target using the interacting multiple model probabilistic data association filter (IMMPDAF). To startup IMMPDAF, the batch maximum likelihood (ML) method is introduced to estimate the initial target state. To adapt to asynchronous sampling condition, the computing method for the Markov transition probabilities is put forward. Simulation results show ML-IMMPDAF is effective in a distributed passive sensor network.
出处
《系统仿真学报》
EI
CAS
CSCD
北大核心
2005年第6期1441-1444,共4页
Journal of System Simulation
基金
深圳市科技局基金(200335)