Segment recognition of the maneuvering target track is the basis for judging the intention of target's behavior. However, existing track segmentation algorithms have a weak ability to detect changes of pattern, and are thus difficult to meet the requirement of fast and refined track segmentation for maneuvering targets. To this end, our paper proposes a two-layer refined track segmentation framework. The pre-segmentation layer is used to detect the pattern switching during the movement of the target, so as to determine the pre-segment area with obvious pattern changes and obtain the pre-segment points of the area with obvious target pattern changes. Then, iterative backtracking optimization is used to segment the track of the non-pre-segmented area with small differences, so as to obtain more refined segmentation points. The framework has the ability to process the track from coarse to fine segmentation, and can realize the recognition of refined segment of the maneuvering target track. Finally, the simulation results of two typical target maneuvering scenarios are given to demonstrate the effectiveness of our proposed method, which can not only reduce the time of iterative optimization, but also improve segmentation accuracy.
QIAO Dianfeng
,
LIANG Yan
,
ZHANG Huixia
,
ZHAO Pengjiao
. Automatic backtracking-based refined segment recognition of maneuvering target track[J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2021
, 42(4)
: 524744
-524744
.
DOI: 10.7527/S1000-6893.2020.24744
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