An adaptive anti-disturbance navigation method for polarized skylight-based autonomous integrated navigation system. (October 2022)

• Record Type: Journal Article
• Authors: Dou, Qingfeng; Du, Tao; Qiu, Zhenbing; Wang, Shanpeng; Yang, Jian
• Is Part Of: Measurement. Volume 202(2022)
• Publication Date: 2022-10
• Subjects: Polarization navigation -- Anti-disturbance navigation method -- Degree of polarization -- Autonomous navigation; Weights and measures -- Periodicals; Measurement -- Periodicals; Measurement; Weights and measures; Periodicals; 530.8
• DOI: 10.1016/j.measurement.2022.111847
• Languages: English
• ISSNs: 0263-2241

Abstract

Abstract: In satellite-denied confrontation or unstructured environments, the navigation performance of the GPS will be severely restricted or even deceived. The SINS/polarization navigation system (PNS)/odometer (OD) integration is not only free from electromagnetic interference, but also has complementary navigation performance, which can meet the needs of autonomous navigation without GPS. However, PNS is limited to the disturbances from the environment, such as shelter, cloud, or large maneuvers. The effect of multiple scattering from real weather conditions and computation methods on the navigation model is considered in this article. It is modeled as an angle of polarization error. The error is estimated in real time to improve the accuracy of PNS navigation model. Aiming at the outliers in polarization measurement caused by shelter, cloud or large maneuvers, an adaptive anti-disturbance navigation method is designed. In particular, this method introduces the degree of polarization to design an adaptive factor to adjust the filter gain. Then, the innovation is utilized to estimate the measurement noise matrix in the presence of outliers. Several simulation experiments and outdoor tests were performed to verify the effectiveness of the proposed method. The experimental results show that the proposed method has better heading estimation than existing methods under large maneuvers.