| 基于进化策略改进的D-S证据识别算法 |
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| 引用本文： | 王小艺,侯朝桢,原菊梅,刘载文. 基于进化策略改进的D-S证据识别算法[J]. 光电子．激光, 2006, 17(8): 999-1003 |
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| 作者姓名： | 王小艺 侯朝桢 原菊梅 刘载文 |
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| 作者单位： | 北京理工大学自动控制系,北京,100081;北京工商大学信息工程学院,北京,100037;北京理工大学自动控制系,北京,100081;北京工商大学信息工程学院,北京,100037 |
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| 摘 要： | 提出了处理多传感器证据冲突的新方法，建立了获取传感器权重的优化模型，运用粒子群优化算法（PSO）求解传感器的权重分配，对Dempster—Shafter（D-S）证据理论进行改进。通过与其它改进算法的比较以及目标识别实例的仿真，验证了新方法的有效性和优越性。
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| 关 键 词： | Dempster-Shafter(D-S)证据理论 组合公式 目标识别 粒子群优化算法(PSO) |
| 文章编号： | 1005-0086（2006）08-0999-05 |
| 收稿时间： | 2005-10-23 |
| 修稿时间： | 2005-10-232006-03-04 |
Improved D-S Evidence Identification Algorithm Based on Evolutionar Strategies |
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| WANG Xiao-yi,HOU Chao-zhen,YUAN Ju-mei,LIU Zai-wen. Improved D-S Evidence Identification Algorithm Based on Evolutionar Strategies[J]. Journal of Optoelectronics·laser, 2006, 17(8): 999-1003 |
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| Authors: | WANG Xiao-yi HOU Chao-zhen YUAN Ju-mei LIU Zai-wen |
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| Affiliation: | 1. Department of Automatic Control, Beijing Institute of Technology, Beijing 100081, China; 2. College of Information and Engineering, Beijing Technology and Business University, Beijing 100037, China |
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| Abstract: | The new method to deal with the evidence conflict of multi-sensor has been presented,and An optimize model of obtaining sensor weights has been set up.We use the particle swarm optimizaiton(PSO) to compute sensor weights to modify Dempster-Shafter(D-S) evidence theory.Through compared with other improved methods and a simulation example of target identification,the results prove the validity and superiority of new method. |
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| Keywords: | Dempster-Shafter(D-S) evidence theory combination formula target identification particle swarm optimization(PSO) |
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