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Article

Robust Adaptive Multiple Backtracking VBKF for In-Motion Alignment of Low-Cost SINS/GNSS

1
School of Automation, Jiangsu University of Science and Technology, Zhenjiang 212100, China
2
Ocean College, Zhejiang University, Zhoushan 316021, China
3
Shanghai Astronomical Observatory, Chinese Academy of Sciences, Shanghai 200030, China
4
School of Surveying and Land Information Engineering, Henan Polytechnic University, Jiaozuo 454003, China
5
School of Resources and Environmental Science and Engineering, Hubei University of Science and Technology, Xianning 437100, China
6
Research Center of Beidou + Industrial Development of Key Research Institute of Humanities and Social Sciences of Hubei Province, Hubei University of Science and Technology, Xianning 437100, China
7
School of Civil and Environmental Engineering, University of New South Wales, Sydney, NSW 2052, Australia
*
Author to whom correspondence should be addressed.
Remote Sens. 2025, 17(15), 2680; https://doi.org/10.3390/rs17152680 (registering DOI)
Submission received: 6 June 2025 / Revised: 28 July 2025 / Accepted: 31 July 2025 / Published: 2 August 2025
(This article belongs to the Section Urban Remote Sensing)

Abstract

The low-cost Strapdown Inertial Navigation System (SINS)/Global Navigation Satellite System (GNSS) is widely used in autonomous vehicles for positioning and navigation. Initial alignment is a critical stage for SINS operations, and the alignment time and accuracy directly affect the SINS navigation performance. To address the issue that low-cost SINS/GNSS cannot effectively achieve rapid and high-accuracy alignment in complex environments that contain noise and external interference, an adaptive multiple backtracking robust alignment method is proposed. The sliding window that constructs observation and reference vectors is established, which effectively avoids the accumulation of sensor errors during the full integration process. A new observation vector based on the magnitude matching is then constructed to effectively reduce the effect of outliers on the alignment process. An adaptive multiple backtracking method is designed in which the window size can be dynamically adjusted based on the innovation gradient; thus, the alignment time can be significantly shortened. Furthermore, the modified variational Bayesian Kalman filter (VBKF) that accurately adjusts the measurement noise covariance matrix is proposed, and the Expectation–Maximization (EM) algorithm is employed to refine the prior parameter of the predicted error covariance matrix. Simulation and experimental results demonstrate that the proposed method significantly reduces alignment time and improves alignment accuracy. Taking heading error as the critical evaluation indicator, the proposed method achieves rapid alignment within 120 s and maintains a stable error below 1.2° after 80 s, yielding an improvement of over 63% compared to the backtracking-based Kalman filter (BKF) method and over 57% compared to the fuzzy adaptive KF (FAKF) method.
Keywords: low-cost Strapdown Inertial Navigation System; in-motion alignment; adaptive multiple backtracking; Expectation–Maximization; robust filter low-cost Strapdown Inertial Navigation System; in-motion alignment; adaptive multiple backtracking; Expectation–Maximization; robust filter

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MDPI and ACS Style

Lyu, W.; Wang, Y.; Jin, S.; Huang, H.; Tian, X.; Wang, J. Robust Adaptive Multiple Backtracking VBKF for In-Motion Alignment of Low-Cost SINS/GNSS. Remote Sens. 2025, 17, 2680. https://doi.org/10.3390/rs17152680

AMA Style

Lyu W, Wang Y, Jin S, Huang H, Tian X, Wang J. Robust Adaptive Multiple Backtracking VBKF for In-Motion Alignment of Low-Cost SINS/GNSS. Remote Sensing. 2025; 17(15):2680. https://doi.org/10.3390/rs17152680

Chicago/Turabian Style

Lyu, Weiwei, Yingli Wang, Shuanggen Jin, Haocai Huang, Xiaojuan Tian, and Jinling Wang. 2025. "Robust Adaptive Multiple Backtracking VBKF for In-Motion Alignment of Low-Cost SINS/GNSS" Remote Sensing 17, no. 15: 2680. https://doi.org/10.3390/rs17152680

APA Style

Lyu, W., Wang, Y., Jin, S., Huang, H., Tian, X., & Wang, J. (2025). Robust Adaptive Multiple Backtracking VBKF for In-Motion Alignment of Low-Cost SINS/GNSS. Remote Sensing, 17(15), 2680. https://doi.org/10.3390/rs17152680

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