Matching area selection for arctic gravity matching navigation based on adaptive all-field extended extremum algorithm

IF 1.4 4区 管理学 Q3 ENGINEERING, ELECTRICAL & ELECTRONIC Iet Radar Sonar and Navigation Pub Date : 2024-04-15 DOI:10.1049/rsn2.12571
Menghan Xi, Lin Wu, Qianqian Li, Guocheng Mao, Pengfei Wu, Bing Ji, Lifeng Bao, Yong Wang
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Abstract

Suitable and effective matching area selection is crucial for gravity matching-aided navigation. In this paper, an all-field extended extremum algorithm based on an adaptive threshold (AT-AEE) is proposed for matching area selection in the Arctic Sea. The gradient data is obtained by using the convolution of gravity reference graph data and all-field extended extremum parameters. Then, the adaptive threshold method was employed to determine the optimal gradient threshold based on gravity anomaly data across various test areas. Data points with gradients exceeding the specified threshold are identified as local candidate points for matching areas. The test areas containing a certain proportion of local candidate points are designated as the suitable matching areas. Nine test areas in the Arctic Sea with different gravity change characteristics were chosen for simulation experiments to verify the performance of the proposed algorithm. Simulation experiments showed that superior navigation positioning results could be obtained in the matching areas selected by the AT-AEE algorithm. Compared to traditional algorithm, the matching areas derived from the AT-AEE algorithm performed with a better consistency in the gravity matching navigation results. In suitable matching areas with the proportion of local candidate points reaching 70%, the average positioning errors could be reduced to less than 1.5 n miles.

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基于自适应全场扩展极值算法的北极重力匹配导航的匹配区域选择
适当而有效的匹配区域选择对于重力匹配辅助导航至关重要。本文提出了一种基于自适应阈值的全场扩展极值算法(AT-AEE),用于北冰洋的匹配区域选择。梯度数据由重力参考图数据和全场扩展极值参数卷积得到。然后,采用自适应阈值法,根据各试验区的重力异常数据确定最佳梯度阈值。梯度超过指定阈值的数据点被确定为匹配区域的局部候选点。包含一定比例局部候选点的测试区域被指定为合适的匹配区域。为了验证所提算法的性能,我们在北冰洋选择了九个具有不同重力变化特征的测试区域进行模拟实验。仿真实验表明,AT-AEE 算法选择的匹配区域可以获得较好的导航定位效果。与传统算法相比,AT-AEE 算法得出的匹配区域在重力匹配导航结果上具有更好的一致性。在本地候选点比例达到 70% 的合适匹配区域内,平均定位误差可降低到 1.5 n 英里以下。
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来源期刊
Iet Radar Sonar and Navigation
Iet Radar Sonar and Navigation 工程技术-电信学
CiteScore
4.10
自引率
11.80%
发文量
137
审稿时长
3.4 months
期刊介绍: IET Radar, Sonar & Navigation covers the theory and practice of systems and signals for radar, sonar, radiolocation, navigation, and surveillance purposes, in aerospace and terrestrial applications. Examples include advances in waveform design, clutter and detection, electronic warfare, adaptive array and superresolution methods, tracking algorithms, synthetic aperture, and target recognition techniques.
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