High-precision geomagnetic directional technology based on sensor error correction and adaptive hybrid filter. (15th February 2023)

• Record Type: Journal Article
• Authors: Chen, Weiren; Zhang, Haifeng; Lyu, Wenshan; Zou, Fengqian; Sang, Shengtian; Jiang, Ming
• Is Part Of: Measurement. Volume 207(2023)
• Publication Date: 2023-02-15
• Subjects: Geomagnetic directional -- Error correction -- Adaptive hybrid filter -- Information entropy; Weights and measures -- Periodicals; Measurement -- Periodicals; Measurement; Weights and measures; Periodicals; 530.8
• DOI: 10.1016/j.measurement.2023.112439
• Languages: English
• ISSNs: 0263-2241

Abstract

Highlights: A unified error model of the geomagnetic measurement data was established. A two-stage Kalman filter method was proposed to perform data fusion. An adaptive attitude updating algorithm is proposed to eliminate data interference. The high-precision geomagnetic directional technology was achieved. Abstract: Low-cost magnetic and inertial sensors based on micro-electro-mechanical systems (MEMS) are extensively used for navigation systems. However, measurements of the magnetometer are very susceptible to different factors, resulting in low accuracy when used for attitude estimation. To solve these problems, a novel method is proposed for geomagnetic directional technology based on sensor error correction and adaptive hybrid filter. In the dynamic directional accuracy test with the turntable rotating speed of 40°/s, the maximum error and RMSE of the yaw angle is 1.00° and 0.63°, respectively. When magnetic interference exists, this algorithm dynamically adjusts the weighting of the magnetometer data by information entropy and RMSE. The experimental results show that the adaptive attitude updating algorithm can reduce the directional error by 90.61% in the environment of magnetic interference. It can meet the overall demand for high-precision attitude calculation of different carriers.