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首页> 外文期刊>International Journal of Sensors, Wireless Communication and Control >A Method of Multi-sensor and Multi-target Tracking and Fusion Based on Double-threshold Technique
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A Method of Multi-sensor and Multi-target Tracking and Fusion Based on Double-threshold Technique

机译：基于双阈值技术的多传感器多目标跟踪融合方法

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摘要

The data fusion can come down to a process that combines the state vectors from different sources to obtain a more accurate result. Compare to the achieved results that depend on single source, the method has gained an improved performance and reduced the computational complexity and bandwidth of transmission as well. This paper makes use of Probabilistic Data Association (PDA) algorithm and Joint Probabilistic Data Association (JPDA) algorithm to track the Multi-target for each local sensor in a clutter environment. Furthermore, a method based on statistical double-threshold association algorithm and covariance-weighted fusion algorithm is proposed in this paper. Meanwhile, the simulation result shows that the performance has been improved significantly in multi-sensor and multi-target tracking progress with the proposed method in the paper.
机译：数据融合可以归结为一个将来自不同来源的状态向量进行组合以获得更准确结果的过程。与依赖单一来源的结果相比，该方法具有改进的性能，并且还降低了传输的计算复杂度和带宽。本文利用概率数据关联（PDA）算法和联合概率数据关联（JPDA）算法来跟踪杂乱环境中每个本地传感器的多目标。此外，提出了一种基于统计双阈值关联算法和协方差加权融合算法的方法。同时，仿真结果表明，本文提出的方法在多传感器，多目标跟踪中的性能得到了显着提高。

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