Application of IMMF–IHHT algorithm to suppressing random interference of geomagnetic sensors

Abstract

Aiming at the problem that the geomagnetic sensor is vulnerable to external interference in the navigation process, this paper analyzes the frequency distribution range of geomagnetic signal and the noise characteristics in geomagnetic signal and proposes an improved morphological filtering and Hilbert–Huang transform (IMMF–IHHT) algorithm to extract and recognize the features of geomagnetic measurement signal. To avoid frequency aliasing and distortion caused by empirical mode decomposition, an improved morphological filtering algorithm based on mean constraint is used to preprocess the measured signal. The Hilbert spectrum of the decomposed signal is solved, the signal components are discriminated by the similarity criterion, and the signal components in line with the frequency range of the geomagnetic signal are extracted and processed to reconstruct the geomagnetic measurement signal. Simulation and experiments show that the signal-to-noise ratio and root-mean-square error of IMMF–IHHT combination algorithm are better than MF-HHT combination algorithm and IHHT algorithm. This algorithm has good signal feature extraction and recognition ability.

Improved ellipsoid fitting aided geomagnetic sensor calibration algorithm

“…The Earth's magnetic field is the inherent physical field of the Earth [1,2]. It has crucial applications in geomagnetic navigation [3,4], attitude calculation [5][6][7], magnetic anomaly signal detection [8,9], and so on.…”