| 基于幅值信息的联合概率数据关联粒子滤波算法 |
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| 引用本文： | 章飞,周杏鹏,陈小惠.基于幅值信息的联合概率数据关联粒子滤波算法[J].系统工程与电子技术,2011,33(2):453-457. |
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| 作者姓名： | 章飞 周杏鹏 陈小惠 |
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| 作者单位： | 1. 东南大学复杂工程系统测量与控制教育部重点实验室， 江苏 南京 210096；
2. 江苏科技大学电子信息学院， 江苏 镇江 212003；
3. 南京邮电大学自动化学院, 江苏 南京 210046 |
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| 摘 要： | 针对非线性非高斯环境下多目标被动跟踪的低可观测问题，将粒子滤波、联合概率数据关联和量测的幅值信息相结合，提出了一种基于幅值信息的联合概率数据关联粒子滤波算法。将联合概率数据关联算法中的关联似然与幅值似然比相结合，利用粒子滤波算法进行跟踪滤波，用幅值量测来改善低可观测条件下的目标跟踪性能。仿真结果表明，该算法提高了数据关联的可靠性和目标跟踪的精度。
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| 关 键 词： | 粒子滤波 幅值信息 联合概率数据关联 低可观测 被动跟踪 |
Joint probabilistic data association particle filter algorithm based on amplitude information title |
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| ZHANG Fei,ZHOU Xing-peng,CHEN Xiao-hui.Joint probabilistic data association particle filter algorithm based on amplitude information title[J].System Engineering and Electronics,2011,33(2):453-457. |
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| Authors: | ZHANG Fei ZHOU Xing-peng CHEN Xiao-hui |
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| Institution: | 1. Key Lab of Measurement and Control of CSE of Ministry of Education, Southeast University, Nanjing 210096, China;
2. School of Electronics and Information, Jiangsu University of Science and Technology, Zhenjiang 212003, China;
3. School of Automation, Nanjing University of Posts and Telecommunications, Nanjing 210046, China |
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| Abstract: | For the low observable problems of multiple target passive tracking in nonlinear and non-Gaussian environment,combining with particle filter(PF),joint probabilistic data association(JPDA) and amplitude information of measurements,a joint probabilistic data association particle filter algorithm based on amplitude information is proposed.In this algorithm,the association likelihood of JPDA is combined with the likelihood ratio of amplitude,the particle filter algorithm is used to track targets,and the amplitu... |
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| Keywords: | particle filter amplitude information joint probabilistic data association low observable passive tracking |
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