基于时序向量相似性的空间目标群匹配技术研究OA

This article analyzes the motion characteristics of low-orbit space target groups and proposes a space target group matc-hing algorithm based on time series vector similarity,which improves the recognition and management ability of low orbit satellite constellations.Firstly,this article introduces the dimensionality reduction method of time series vectors,which simplifies the high-dimensional observation time series vectors of the target group into spatial configuration sequences.Secondly,an algorithm based on Dynamic Time Warping(DTW)is proposed to identify the phase sequence similarity of observed data of target group.Finally,the matching ability of the algorithm is verified by the simulation and measured data of Starlink satellite target group.The results show that this algorithm can match the observed data of the space target group rapidly.During the simulation data matching process,the success rate of matching can reach 100%under the condition of 30%random missing targets within the group,and the average success rate of target recognition within the group exceeds 75%under low missing conditions(with a missing rate of less than 5%).The success rate of matching real observed data can also reach 100%.