2020
DOI: 10.1177/0954410020951022
|View full text |Cite
|
Sign up to set email alerts
|

Geomagnetic signal de-noising method based on improved empirical mode decomposition and morphological filtering

Abstract: To solve the problem that geomagnetic signals are susceptible to random noise and instantaneous pulse interference in geomagnetic navigation, a geomagnetic signal de-noising method based on improved empirical mode decomposition (IEMD) and morphological filtering (MF) is proposed. The instantaneous pulse interference is eliminated by designing different structural elements according to the characteristics of the pulse signal. The signal after filtering the instantaneous pulse interference is decomposed by EMD, … Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1
1

Citation Types

0
2
0

Year Published

2022
2022
2023
2023

Publication Types

Select...
3

Relationship

1
2

Authors

Journals

citations
Cited by 3 publications
(2 citation statements)
references
References 42 publications
0
2
0
Order By: Relevance
“…Secondly, considering that the total geomagnetic features of the matching areas are very similar, the ICCP algorithm is prone to the problem of low matching accuracy or mismatch. And the terrain has only elevation information, while the geomagnetic field has abundant information features, such as vector features, three axes and seven components [15,16]. The objective function is improved by using the geomagnetic three-dimensional features, which is defined as the matching index.…”
Section: Vector Improved Algorithm For Iccp Matchingmentioning
confidence: 99%
“…Secondly, considering that the total geomagnetic features of the matching areas are very similar, the ICCP algorithm is prone to the problem of low matching accuracy or mismatch. And the terrain has only elevation information, while the geomagnetic field has abundant information features, such as vector features, three axes and seven components [15,16]. The objective function is improved by using the geomagnetic three-dimensional features, which is defined as the matching index.…”
Section: Vector Improved Algorithm For Iccp Matchingmentioning
confidence: 99%
“…Based on Li Ji's research method, Diao Yun-yun [15] introduced autocorrelation function to verify that the highorder components above order 6 contain effective geomagnetic signal cutoff frequency, identify the effective geomagnetic signal in the medium and high-frequency components of IMF and calculate the root-mean-square error (RMSE) between the final result and the fast Fourier transform result, proving the superiority of morphological filtering and HHT combined filtering. Zhai [16] adopted the improved empirical mode decomposition for geomagnetic measurement signals, designed normalized least mean square (NLMS) filter and morphological filter to remove the noise in the mixed intrinsic mode function (IMF), adaptively adjusted the filtering parameters according to the noise level of different IMF components, reconstructed the IMF and residual after noise reduction and obtained the filtered signal. Zhou [17] used the combined filtering algorithm of adaptive median filter and HHT algorithm for magnetic sensor signal processing and proposed a similarity criterion based on IMF processing.…”
Section: Introductionmentioning
confidence: 99%