A Class of Distributed Variable Structure Multiple Model Algorithm Based on Posterior Information of Information Matrix

Abstract

Abstract:The tracking of maneuvering targets in radar networking scenarios is studied in this paper. For the interacting multiple model algorithm and the expected-mode augmentation algorithm, the fixed base model set leads to a mismatch between the model set and the target motion mode, which causes the reduction on tracking accuracy. An adaptive grid-expected-mode augmentation variable structure multiple model algorithm is proposed. The adaptive grid algorithm based on the turning model is extended to the two-dimensional pattern space to realize the self-adaptation of the model set. Furthermore, combining with the unscented information filtering, and by interacting the measurement information of neighboring radars and iterating information matrix with consistency strategy, a distributed target tracking algorithm based on the posterior information of the information matrix is proposed. For the problem of filtering divergence while target is leaving radar surveillance area, a k-coverage algorithm based on particle swarm optimization is applied to plan the radar motion trajectory for achieving filtering convergence.

Key words:radar network system, variable structure multiple model, consistency filtering, information matrix, particle swarm optimization

CLC Number:

TP273

HUANG Yinghao1,2 (黄颖浩), WU Yi3 (吴怡), YAO Lixiu2 (姚莉秀), CAI Yunze1,2∗ (蔡云泽). A Class of Distributed Variable Structure Multiple Model Algorithm Based on Posterior Information of Information Matrix[J]. J Shanghai Jiaotong Univ Sci, 2022, 27(5): 671-679.

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