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.
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]. Journal of Shanghai Jiaotong University(Science), 2022
, 27(5)
: 671
-679
.
DOI: 10.1007/s12204-022-2458-x
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