Multi-sensor distributed fusion based on CFSFDP clustering algorithm

Feng Yang, Miaozang Zhang, Jinming Cao, Yongting Wang
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Abstract

Multi-sensor and multi-target distributed fusion has a big computational burden. A multi-sensor distributed fusion algorithm based on clustering by fast search and find of density peaks (CFSFDP) is proposed. The local target tracks which come from the multi-sensor are divided into multiple categories. The obtained categories number is the target number. The corresponding cluster centers are the fusion states of the targets. The least square fitting algorithm is used to smooth the target's fusion result. The simulation results show that the proposed algorithm has a higher robustness, compared with traditional Covariance Intersection (CI) fusion and local tracks of single sensor.
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基于CFSFDP聚类算法的多传感器分布式融合
多传感器多目标分布式融合计算量大。提出了一种基于快速搜索和发现密度峰聚类的多传感器分布式融合算法。将来自多传感器的局部目标航迹划分为多个类别。得到的类别号即为目标号。相应的聚类中心为目标的融合状态。采用最小二乘拟合算法对目标的融合结果进行平滑处理。仿真结果表明,与传统的协方差交叉(CI)融合和单传感器局部轨迹相比,该算法具有更高的鲁棒性。
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