| 基于JPDA-MPC的单站纯方位多目标跟踪 |
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| 引用本文： | 邵俊伟,单奇,吴超.基于JPDA-MPC的单站纯方位多目标跟踪[J].航天电子对抗,2014(2):51-53,64. |
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| 作者姓名： | 邵俊伟 单奇 吴超 |
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| 作者单位： | 中国电子科技集团公司第三十八研究所,安徽合肥230088 |
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| 摘 要： | 静止单站对多目标进行纯方位跟踪时,若在直角坐标系下建立跟踪模型并使用最近邻标准滤波器(NNSF)进行关联和滤波,结果通常不稳定且容易发散。针对此问题,提出将修正的极坐标系(MPC)下的扩展Kalman滤波算法及联合概率数据互联关联(JPDA)算法相结合。与NNSF-MPC算法的仿真对比试验表明,JPDA-MPC算法可以提高跟踪过程的稳定性,且具有更小的跟踪误差。
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| 关 键 词： | 纯方位跟踪 联合概率数据互联 修正的极坐标系 最近邻标准滤波器 |
Multiple bearing-only target tracking with a single station based on JPDA-MPC |
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| Shao Junwei,Shan Qi,Wu Chao.Multiple bearing-only target tracking with a single station based on JPDA-MPC[J].Aerospace Electronic Warfare,2014(2):51-53,64. |
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| Authors: | Shao Junwei Shan Qi Wu Chao |
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| Institution: | (No. 38 Research Institute of CETC, Hefei 230088, Anhui,China) |
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| Abstract: | When tracking multiple bearing-only targets with a single station, the results are usually unstable and tend to be divergent, if the tracking model is built in Cartesian coordinates and the NNSF algorithm is used for data association. For resolving this problem, the extended Kalman Filter in MPC and the JPDA algorithm are combined. Simulations show that, compared with the NNSF-MPC algorithm, the JPDA- MPC algorithm can improve the stability of tracking process and also has a smaller tracking error. |
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| Keywords: | bearing-only tracking JPDA MPC NNSF |
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