| 引用本文: | 敬忠良,张国伟,周宏仁.基于随机神经网络的数据关联组合优化研究[J].控制理论与应用,1994,11(3):257~263.[点击复制] |
| JING Zhongliang, ZHANG Guowei and ZHOU Hongren.Investigation on Combinatorial Optimization of Data Association Based on Stochastic Neural Network[J].Control Theory and Technology,1994,11(3):257~263.[点击复制] |
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| 基于随机神经网络的数据关联组合优化研究 |
| Investigation on Combinatorial Optimization of Data Association Based on Stochastic Neural Network |
| 摘要点击 757 全文点击 385 投稿时间：1993-06-02 |
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| DOI编号 |
| 1994,11(3):257-263 |
| 中文关键词 神经网络 模拟退火 数据关联 多目标跟踪 组合优化 |
| 英文关键词 neural network simulated annealing data association multi-target tracking combinatorial optimization |
| 基金项目 |
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| 中文摘要 |
| 本文研究密集多回波环境下的机动多目标数据关联问题。通过对联合概率数据关联（JPDA）方法性能特征的分析，将其归结为一类约束组合优化问题，进而应用随机神经网络Boltzmann机的组合优化求解策略，结合改进的模拟增益退火方法，提出了一种新颖有效的机动多目标快速随机神经网络数据关联组合优化算法（FSNJPDA），克服了传统JPDA存在出现的计算组合爆炸现象。仿真结果表明，该方法不仅收敛速度快，而且计算量小，关联效果好，回波愈密集，其优越性能愈为突出。 |
| 英文摘要 |
| In this paper, the properties of the joint probabilistic data association（JPDA）are analyzed, and the data association of multi-maneuvering targets is reduced to be a sort of constraint combinatorial optimization problem. Based on Boltzmann machine and simulated gain annealing, a new algorithm called fast stochastic neural joint probabilistic data association （FSNJPDA）is presented. The simulations show that the computation combinatorial explosion of the JPDA has been solved, and the FSNJPDA is effective and reliable. |