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中文核心期刊

利用水平精度因子的长基线水声定位选元方法

Element selection method based on horizontal dilution of precision for long baseline underwater acoustic localization

  • 摘要: 针对长基线水声定位场景, 提出了一种基于水平精度因子的选元方法。该方法可避免时延估计误差较大的阵元参与定位解算, 且可根据目标定位结果及时调整选元策略。首先选择水平精度因子最小的阵元组合对目标位置进行解算, 然后利用卡尔曼滤波器预测目标位置, 当卡尔曼滤波器的预测值与解算值相差较大时, 选择水平精度因子次小的阵元组合重新解算, 重复此过程直至解算值与预测值的差小于一定范围时, 得到最优的阵元组合和目标定位结果。湖上实测数据处理结果表明, 分别采用交汇解算和高斯迭代解算方法, 所提选元方法的定位误差相比于固定选元方法分别减小了51.0%和22.2%, 有效提升了长基线水声定位精度。

     

    Abstract: For long baseline underwater acoustic localization scenarios, a method based on the horizontal dilution of precision (HDOP) is proposed for selecting array elements. This method avoids the participation of array elements with large time-delay estimation errors in the solving process of localization, and adjusts the selection strategy timely based on the localization results. First, the combination of array elements with the smallest HDOP are selected to calculate the target location, and then the Kalman filter is used to predict the target location. If the prediction value of the Kalman filter differs significantly from the calculated value, the combination of array elements with the second-smallest HDOP is selected to resolve the problem. This process is repeated until the difference between the calculated value and the predicted value is less than a certain threshold. The optimal combination of array elements and the target localization results are then obtained. The processing results of the data measured on the lake show that using the intersection and Gaussian iteration solution reduce the localization error of the proposed method by 51.0% and 22.2% respectively, compared to the fixed element selection method. This method effectively improves the accuracy of long-baseline underwater acoustic localization.

     

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