| 次优联合概率数据关联算法的研究 |
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| 引用本文： | 安振,姜秋喜,李业春.次优联合概率数据关联算法的研究[J].现代雷达,2011,33(4):41-44. |
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| 作者姓名： | 安振 姜秋喜 李业春 |
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| 作者单位： | 1. 解放军96125部队,沈阳,110032
2. 电子工程学院,合肥,230037 |
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| 摘 要： | 数据关联算法的研究是多目标跟踪中的核心问题,多目标跟踪的精度和计算过程的复杂度均取决于所采取的数据关联算法的优劣。文中对2种典型的次优联合概率数据关联算法进行了研究,结合仿真结果指出了上述2种次优算法间的本质差异,同时还提出了一种改进的次优联合概率数据关联算法。计算机仿真表明,改进的算法较原算法具有更好的跟踪性能。
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| 关 键 词： | 联合概率数据关联 次优 改进 跟踪性能 |
A Study on Suboptimal Joint Probability Data Association Algorithm |
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| AN Zhen,JIANG Qiu-xi,LI Ye-chun.A Study on Suboptimal Joint Probability Data Association Algorithm[J].Modern Radar,2011,33(4):41-44. |
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| Authors: | AN Zhen JIANG Qiu-xi LI Ye-chun |
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| Affiliation: | AN Zhen1,JIANG Qiu-xi2,LI Ye-chun2(1.Unit 96125 of PLA,Shenyang 110032,China)(2.Electronic Engineering Institute,Hefei 230037,China) |
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| Abstract: | A study on data association algorithm is a key problem in multiple objects tracking,the accuracy and complexity of multiple objects tracking are determined by the used data association algorithm.Two typical suboptimal joint probability data association(JPDA) algorithms are studied,and the essential difference between the algorithms is pointed by simulation results.Basing on those,an improving suboptimal JPDA algorithm is putting forward.The computer simulations show that the improving JPDA algorithm has a b... |
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| Keywords: | joint probability data association suboptimal improving tracking performance |
| 本文献已被 CNKI 万方数据 等数据库收录！ |
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