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A Novel Refined Track Initiation Algorithm for group targets Based on group Model

Chinese Journal of Electronics 2014年第4期23卷 851-856页

作者： GAO Fei REN He WANG Jun Amir Hussain Tariq S. Durrani School of Electronic and Information Engineering Beihang University School of Natural Sciences University of Stirling Department of Electronic & Electrical Engineering University of Strathclyde

Traditional refined track initiation methods for group targets have mistakes or loss of tracks when tracking irregular motions, for the reason that they rely on a stable relative position of group members. To solve the problem, a group dynamic model was introduced for proposing a new initiation algorithm and its whole framework. We made a self-adaptive improvement of the group separation on various group radii. After the pre-association of these groups, a state equation derived from the model was used for predictions of group members. Then a relational matrix was defined for refined data associations. Finally tracks were validated by logic-based method. Particular scenarios and Monte Carlo simulations showed that,compared with algorithms based on relative position, this algorithm has better performance on the adaptability to changes of a group structure and the correctness of initiation.

关键词： group targets Track initiation group model State equation Data association

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group tracking algorithm for split maneuvering based on complex domain topological descriptions

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Chinese Journal of Aeronautics 2018年第1期31卷 126-136页

作者： Cong WANG Chen GUO Yu LIU You HE Institute of Information Fusion Naval Aeronautical and Astronautical University Yantai 264001 China

A group tracking algorithm for split maneuvering based on complex domain topological descriptions is proposed for the tracking of members in a maneuvering group. According to the split characteristics of a group target, split models of group targets are established based on a sliding window feedback mechanism to determine the occurrence and classification of split maneuvering, which makes the tracked objects focus by group members effectively. The track of an outlier single target is reconstructed by the sequential least square method. At the same time, the relationship between the group members is expressed by the complex domain topological description method, which solves the problem of point-track association between the members. The Singer method is then used to update the tracks. Compared with classical multi-target tracking algorithms based on Multiple Hypothesis Tracking （MHT） and the Different Structure Joint Probabilistic Data Association （DS-JPDA） algorithm, the proposed algorithm has better tracking accuracy and stability, is robust against environmental clutter and has stable time-consumption under both classical radar conditions and partly resolvable conditions.

关键词： Complex domain group targets Joint probabitistic data association Multiple hypothesis tracking Sliding window feedback Tracking

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