基于相关性分析的水下定位异常数据校正及丢失数据修补方法

超短基线是实现水下拖体设备精确导航定位的必备设备,是目前我国在国际海底区域进行资源深入调查研究的重要装备。受水声信号传播损失、多径效应和其它设备噪声等因素的影响,超短基线水下定位数据存在诸多异常点,已严重影响水下定位数据的可信度和使用。针对该问题,本文提出并实现了一种基于相关性分析的剔除随机异常点和回归填充改正算法,并采用国际海底区域实测水下定位数据对算法可靠性进行了验证,同时采用模拟仿真方法对小时间尺度的定位数据进行了预测对比,取得较好效果。结果表明,该算法快捷、有效,有望在后续国际海底区域调查中推广应用,为国际海底资源调查水下装备的准确定位提供直接服务。

Anomaly data reconciliation and missing-data repair methods of underwater positioning based on correlation analysis

Ultra-short baseline is the necessary device to achieve the accurate positioning of towing equipment, and it is also the important equipment to do the deep-sea resource research in the international seabed area at the present. Because of the influences of acoustic signal propagation loss,multipath effect and other equipment noise, underwater positioning data has many outliers, which has seriously affected the credibility and the use of positioning data.To solve this problem, we propose and implement a correction algorithm based on correlation analysis to reject outliers and random regression which fill and correct positioning data. We use positioning data measured from the international seabed area to validate the reliability of the algorithm.At the same time, we use simulation comparison method for small scale and short time positioning data forecast, and therefore a good result has been achieved. The experimental results show that the algorithm is fast and effective. It is expected to be applied to the international seabed area survey, and can provides direct service to the international seabed resources investigation for accurate positioning equipment.