电光与控制, 2019, 26 (5): 39, 网络出版: 2019-06-10
基于跟踪质量熵的分布式组网雷达航迹融合算法
A Track Fusion Algorithm of Distributed Netted Radar Based on Track Quality Entropy
分布式多传感器融合 航迹融合 质量熵 灰度关联 反馈信息 distributed multi-sensor fusion track fusion quality entropy gray correlation feedback information
摘要
针对分布式多传感器融合系统中, 传统的航迹融合算法未充分考虑不同传感器探测跟踪性能不同带来的航迹质量的不确定度差异, 导致融合后的航迹质量下降的问题, 提出了一种基于跟踪质量熵的航迹融合算法。首先, 构建融合中心所有局部航迹的跟踪质量熵模型, 根据熵大小排序并划分不确定度等级; 然后, 选择质量熵排序队列的航迹作为参考数列, 利用灰度理论对不同局部节点的来自同一目标源的航迹进行聚类; 最后, 将聚类后的航迹, 根据不确定等级进行分群融合, 并把不确定等级较低的航迹融合后的状态反馈至各局部节点进行局部融合。该方法提高了局部节点的跟踪质量, 增强了航迹融合的正确性, 仿真验证了该方法的可行性和有效性。
Abstract
In distributed multi-sensor fusion system, the uncertainty of target tracking quality due to different detection performance of the sensors has not been fully considered by the traditional track fusion algorithms, which may result in degraded track quality after fusion.A method of track fusion algorithm based on track quality entropy is proposed here.Firstly, the quality entropy models of all the local tracks of the fusion center are constructed, sorted according to value of the entropy, and divided into different uncertainty levels.Secondly, a sort queue of track quality entropy is choosed as the reference queue, and the gray theory is used to cluster the tracks of different local nodes from the same target source.Lastly, the clustered tracks are grouped according to quality uncertainty level, and the track state with low uncertainty level will be fed back to local nodes for local fusion.This method can improve the quality of local node tracking, and enhance the correctness of track fusion.Simulation verifies the feasibility and effectiveness of the method.
陈帅, 张世仓, 王凯. 基于跟踪质量熵的分布式组网雷达航迹融合算法[J]. 电光与控制, 2019, 26(5): 39. CHEN Shuai, ZHANG Shi-cang, WANG Kai. A Track Fusion Algorithm of Distributed Netted Radar Based on Track Quality Entropy[J]. Electronics Optics & Control, 2019, 26(5): 39.