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中文核心期刊

无源声呐水下多目标融合跟踪方法

Underwater multitarget fusion tracking method for passive sonar

  • 摘要: 针对海洋环境噪声导致弱目标在不同子频带检测结果差异较大, 致使以全频带探测结果为输入的跟踪算法出现性能退化的问题, 提出一种子带融合跟踪方法。该方法利用改进的高斯混合概率假设密度滤波器对各频率子带输出的方位估计结果进行跟踪, 并采用广义协方差交集准则对子带跟踪结果进行融合, 以获得综合各子带信息的跟踪结果。仿真结果表明, 所提方法可以提高弱目标在各子带信噪比不均衡情况下的跟踪能力, 且运算时间与对比方法较为接近。海试数据处理结果进一步验证了所提方法的有效性。

     

    Abstract: The marine environmental noise will cause the detection results of weak targets significantly different in subdbands and lead to the performance degradation problem of tracking algorithms based on fullband detection results. To address this issue, a subband fusion tracking method is proposed. A modified Gaussian mixture probability hypothesis density (GM-PHD) filter is introduced to obtain direction of arrival (DOA) tracking results for different subbands. In addition, the subband tracking results are fused by the generalized covariance intersection (GCI) technique to obtain the tracking results with integrated subband information. Simulation results illustrate that the proposed method can improve the tracking ability of weak targets with different signal-to-noise ratios in each subband, and the computation time is relatively close to the comparison methods. The sea trial data processing results further demonstrate the effectiveness of the proposed method.

     

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