摘要
为了提高转移概率自适应的并行交互模型算法(ATPM-PIMM)对机动目标的跟踪精度,提出一种改进的ATPMPIMM算法。该算法将基于非等维状态的混合估计方法引入ATPM-PIMM算法中,改善非等维状态交互带来的信息丢失问题,降低模型切换导致的峰值误差,满足对机动目标跟踪的需要。仿真结果表明,改进的ATPM-PIMM算法能有效地提高对机动目标的跟踪精度。
An improved ATPM-PIMM(parallel interacting multiple model based on adaptive transition probability matrix)algorithm is proposed to improve its tracking accuracy for maneuvering targets.In this algorithm,the mixing estimation method based on unequal dimension states is introduced into ATPM-PIMM algorithm to eliminate the information loss caused by unequal dimensional state interaction and reduce the peak error caused by model switching,so as to meet the needs of maneuvering target tracking.The simulation results show that the improved ATPM-PIMM algorithm can effectively improve the tracking accuracy for maneuvering targets.
作者
张成龙
索继东
麻智雄
ZHANG Chenglong;SUO Jidong;MA Zhixiong(School of Information Science and Technology,Dalian Maritime University,Dalian 116026,China)
出处
《现代电子技术》
2022年第5期14-18,共5页
Modern Electronics Technique
基金
福建海事局项目(2018Z0093)。
关键词
转移概率自适应
交互多模型
机动目标跟踪
混合估计
非等维状态
信息丢失
adaptive transition probability
IMM
maneuvering target tracking
mixing estimation
unequal dimension state
information loss
