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Alternative TitleSGPDA-STF and Its Application of Underwater Multiple Targets Bearings-Only Tracking
刘开周; 梅登峰; 王艳艳
Source Publication机械设计与制造
Contribution Rank1
Funding Organization国家自然科学基金(61273334); 辽宁省自然科学基金(2011010025-401)
Keyword广义概率数据关联 强跟踪 纯方位跟踪 多目标跟踪 杂波
Other AbstractFor a range of issues,including large amount of calculation and low robustness to model variation,existing in the generalized probability data association (GPDA)algorithm,a simplified generalized probability data association(SGPDA) algorithm is proposed,and then SGPDA is combined with strong tracking filter (STF)algorithm to form a novel algorithm named strong tracking filter based on simplified generalized probability data association (SGPDA-STF). SGPDA greatly reduce calculation without decreasing accuracy. The robustness of STF is strengthened by adjusting the gain matrix. SGPDASTF algorithm combines strong robustness of STF and low calculation cost of SGPDA. The simulation of single observer multiple targets bearings-only tracking in cluttered underwater environment is conducted,and the results show the superiority of SGPDA-STF over the traditional GPDA-EKF algorithm in robustness and calculation cost.
Document Type期刊论文
Corresponding Author刘开周
Recommended Citation
GB/T 7714
刘开周,梅登峰,王艳艳. SGPDA-STF及其在水下多目标纯方位跟踪中的应用[J]. 机械设计与制造,2014(12):220-223.
APA 刘开周,梅登峰,&王艳艳.(2014).SGPDA-STF及其在水下多目标纯方位跟踪中的应用.机械设计与制造(12),220-223.
MLA 刘开周,et al."SGPDA-STF及其在水下多目标纯方位跟踪中的应用".机械设计与制造 .12(2014):220-223.
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