基于SDP优化测距的相对定位误差校正方法

邢佳艺; 邓锴; 王长红; 饶亮

doi:10.11993/j.issn.2096-3920.2025-0099

基于SDP优化测距的相对定位误差校正方法

doi: 10.11993/j.issn.2096-3920.2025-0099

邢佳艺^{1, 2,},
邓锴^{1, 3, ,},
王长红^{1, 3},
饶亮^{1, 3}

1.
中国科学院声学研究所, 北京, 100190
2.
中国科学院大学, 北京, 100049
3.
北京海洋声学装备工程技术研究中心, 北京, 100190

基金项目: 中国科学院前瞻战略科技专项资助(XDA0370402).

详细信息

作者简介:
邢佳艺(2000-), 女, 在读硕士, 主要研究方向为集群协同定位与相对定位误差校正

通讯作者:
邓　锴(1977-), 男, 博士, 研究员, 主要研究方向为声学测流测速技术及水下组合导航技术.

中图分类号: TJ630.1; U666.1
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- 文章访问数: 110
- HTML全文浏览量: 49
- PDF下载量: 24
- 被引次数: 0
出版历程
- 收稿日期: 2025-07-31
- 修回日期: 2025-09-02
- 录用日期: 2025-09-08
- 网络出版日期: 2025-12-03

Relative Localization Error Correction Method Based on SDP-Optimized Range Measurements

XING Jiayi^{1, 2
,},
DENG Kai^{1, 3
, ,},
WANG Changhong^{1, 3},
RAO Liang^{1, 3}

1.
Institute of Acoustics, Chinese Academy of Sciences, Beijing 100190, China
2.
University of Chinese Academy of Sciences, Beijing 100049, China
3.
Beijing Engineering Technology Research Center of Ocean Acoustics Equipment, Beijing 100190, China

摘要

摘要: 现有集群协同定位研究多聚焦于绝对位置估计, 对节点间相对位置关系的关注较少。为简化测距模型并更直观地评估算法性能, 文中假定集群内部节点保持相对静止, 提出了一种基于半正定规划(SDP)优化测距的惯导误差校正方法。该方法在测距时刻对原始测距数据进行全局SDP优化后校正惯性导航系统(INS)的定位误差, 并对INS存在的固有偏差进行误差补偿更新, 有效提升了集群内节点的相对定位精度。文中构建了集群协同定位模型, 推导节点位置的非线性最小二乘解算公式, 并开展惯导误差补偿机理分析。多次仿真结果表明: 与直接采用原始测距数据进行惯导校正的方法相比, 所提方法可使相对定位误差平均降低40%以上; 且随着测距更新间隔的增大, 其在惯导误差抑制方面的技术优势愈发显著。
- 半正定规划 /
- 相对定位 /
- 误差校正 /
- 惯性导航系统 /
- 协同定位
Abstract: Most of the existing research on cooperative localization focuses on absolute position estimation, with relatively little attention paid to the relative positioning among nodes in clusters. To simplify the ranging model and provide a more intuitive evaluation of algorithm performance, this paper assumed that nodes within the cluster remain relatively stationary, and it proposed an inertial navigation system(INS) error correction method based on semi-definite programming(SDP)-optimized ranging. At the time of ranging, global SDP optimization was performed on the original ranging data to correct the positioning error of the corrected INS, followed by error compensation updates for the inherent biases of the INS, which effectively enhanced the relative positioning accuracy among the nodes. The paper established a cooperative localization model for the cluster, derived a nonlinear least squares formulation for node positioning, and provided an analysis of INS error compensation. Multiple simulation results indicate that compared with the method of directly using the original ranging data to correct the INS, the proposed method can reduce the relative positioning error by more than 40% on average, and its advantage in suppressing INS errors becomes even more pronounced as the ranging update interval increases.
- semidefinite programming /
- relative localization /
- error correction /
- inertial navigation system /
- cooperative localization

HTML全文

图 1 AUV集群定位系统

Figure 1. AUV cluster positioning system

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图 2 惯导漂移及校正轨迹

Figure 2. INS drift and correction trajectory

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图 3 惯导系统误差校正对比曲线

Figure 3. Comparison curves of INS error correction

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图 4 测距误差优化对比曲线

Figure 4. Comparison curves of ranging error optimization

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图 5 集群阵型对比曲线

Figure 5. Comparison curves of cluster formation

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图 6 相对位置误差校正对比曲线

Figure 6. Comparison curves of relative position error correction

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图 7 不同测距间隔下相对位置误差曲线

Figure 7. Relative position error curves under different ranging intervals

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图 8 相对定位误差随时间变化曲线

Figure 8. Curves of relative positioning error with time

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