针对水下多目标跟踪过程中存在多种干扰因素，如噪声污染、杂波环境、量测数据处理等，本文将概率假设密度滤波应用到水下目标跟踪领域。首先，在单目标匀速运动场景下，提出一种二维搜索法，探究目标估计的均方根误差随2个被动声呐距离和目标初始链距取值变化的规律，为后续目标跟踪中参数选取提供参考。接着，对于多目标编队航行和航迹交叉的运动场景，分别探究目标间距和量测噪声对目标跟踪性能的影响。仿真结果表明，二维搜索法能够有效指导算法参数选取，并且所提算法具有目标数和目标状态估计精度良好的优点。
For the many kinds of interference factors in underwater multi-targets tracking, such as noise pollution, clutter environment and measurement data processing, this paper proposes to apply probability hypothesis density filter to underwater target tracking. Firstly, when single-target move with a constant velocity, a two-dimensional search method is proposed to study the regulation that the root mean square error of the target estimation with the variation of two passive sonar spacing and the target initial distance. The regulation provides reference for parameter selection in the following target tracking. Then, for the multi-target formation navigation and cross-track motion scenarios, the effects of target spacing and measurement noise on target tracking are investigated respectively. The simulation show that the two-dimensional search method can effectively guide the selection of algorithm parameters, and the proposed algorithm has the advantages of accurate target number and target state estimation.
2019,41(7): 55-59 收稿日期：2018-03-05
DOI：10.3404/j.issn.1672-7649.2019.07.011
分类号：TP391.9
作者简介：王芳(1993-),女,硕士研究生,研究方向为水下目标跟踪
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