针对自适应高斯模型及算法在水下目标跟踪时对机动频率依赖性较强的缺陷，提出一种基于机动检测的改进算法。利用目标在转向机动时航向角发生持续性变化的特性，构造统计量对目标的机动点和非机动点进行估计，进而自适应调节模型的机动频率，实现对水下目标的精确跟踪。仿真结果表明，基于航向变化率的机动检测算法对不同速度、不同机动强度的水下目标均具备良好的检测效果，基于机动检测的改进模型及算法对非机动目标和转向机动目标均具备良好的跟踪性能。
Aiming at the defect that the adaptive Gaussian model and algorithm have strong dependence on maneuver frequency when tracking underwater targets, an improved algorithm based on maneuver detection is proposed. Utilizing the characteristics of the continuous change of the heading angle of the target when turning and maneuvering, construct statistics to estimate the maneuvering and non-maneuvering points of the target, and then adaptively adjust the maneuvering frequency of the model to achieve accurate tracking of the underwater target. The simulation results show that the maneuver detection algorithm based on the heading change rate has a good detection effect on underwater targets with different speeds and different maneuvering intensities, the improved model and algorithm based on maneuver detection have good detection results for both non-maneuverable targets and steering maneuvering targets.
2022,44(6): 114-120 收稿日期：2021-08-09
DOI：10.3404/j.issn.1672-7649.2022.06.023
分类号：TN929.3
作者简介：梅鹏(1996-)，男，硕士研究生，研究方向为水下目标跟踪机动检测
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