【摘要】 针对群目标在目标密集和航迹交叉等复杂场景下传统分布式航迹关联算法航迹关联正确率偏低的问题,提出了一种基于拓扑特征及小波变换的分布式航迹关联算法。利用群目标航迹的时间累积信息,基于小波变换提取航迹运动趋势,在速度朝向相同时利用最优子模式分配(OSPA)距离衡量不同航迹目标拓扑特征间距离,从而实现分布式航迹关联。仿真结果表明,与基于拓扑特征航迹关联算法相比,该算法航迹正确率显著提高,算法性能得到了提升。更多还原

【Abstract】 Aimed at the group targets’ low track correlation accuracy rate problem of the traditional distributed track correlation algorithm in the complex scenarios with dense targets or track intersec-tions,a distributed track correlation algorithm based on the topology features and the wavelet trans-form is proposed. With the time accumulated information of the group target track,the track move-ment trend is extracted based on the wavelet transform. When the speed directions are the same,the optimal sub-pattern allocation(OSPA)distance is used to measure the distance between the reference topological features of the different track targets. Thus,the distributed track correlation is realized.The simulation results show that compared with the track-based correlation algorithm based on the spatial topologies,the track accuracy of the algorithm is significantly improved,and the performance of the algorithm is enhanced.更多还原