使用Mahalanobis距离对DVL辅助SINS的异常抗性初始调整
Yidong Shen1, Li Luo1, Guoqing Wang2
1School of Electronic Information and Electrical Engineering, Chengdu University, Chengdu 610106, China.
Sensors (Basel, Switzerland)
|December 31, 2025
概括
本研究介绍了多普勒速度日志 (DVL) 辅助的带式惯性导航系统 (SINS) 的强大的初始对齐方法. 新方法通过抑制异常值和复杂水下环境中的干扰来提高准确性.
科学领域:
- 导航系统工程 导航系统工程
- 机器人技术和自主系统
- 信号处理 信号处理
背景情况:
- 在多普勒速度日志 (DVL) 的帮助下,紧式惯性导航系统 (SINS) 对于水下导航至关重要.
- 由于复杂的水下环境和测量异常值,SINS/DVL系统的初始调整方法的性能显著降低.
- 现有的方法与DVL测量的可靠性扎,这些测量被异常污染了.
研究的目的:
- 为 SINS/DVL 综合导航系统提出一种异常抗异常的初始对齐方法.
- 在存在测量异常值和干扰的情况下,提高初始对齐的稳定性和准确性.
- 提高SINS/DVL系统在具有挑战性的水下环境中的整体性能.
主要方法:
- 开发一个改进的Mahalanobis距离标准,用于异常残留载体检测.
- 在观察矩阵中引入适应权重因子以抑制异常干扰.
- 将这些技术集成到SINS/DVL系统的初始对齐算法中.
主要成果:
- 与现有方法相比,当异常值存在时,拟议的方法显示出更高的对齐准确性.
- 在初始对齐过程中,可以有效地抑制异常干扰.
- 模拟和实验结果验证了新方法的增强性能和稳定性.
结论:
- 拟议的耐异常值初始调整方法在不利条件下显著提高了SINS/DVL系统的准确性.
- 这种方法更适合于复杂的水下环境中的实际应用,其中DVL数据可能不可靠.
- 干扰抑制技术提高了集成导航系统的可靠性.
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