理论模型分析卡尔曼滤波在航空全张量磁力梯度测量中的应用效果

doi:10.11720/wtyht.2021.1307

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Abstract

The aero full tensor magnetic gradient data contain complex motion noise, which is distributed from low frequency to high frequency in the spectrum, and is mainly white noise. So, how to effectively suppress the motion noise is a great challenge. The traditional digital filtering can only filter the noise with the specified frequency band, but it can not effectively separate the noise mixed in the full tensor magnetic gradient useful signal. In view of the fact that Kalman filter is a fast, efficient and real-time optimization estimation method, the authors applied it to the aero magnetic full tensor gradient data processing, and built the state equation and observation equation reasonably. Model test proves that the method is effective and can be applied to real-time processing of aeromagnetic full tensor gradient data.

Key words： full tensor magnetic gradient Kalman filter white noise data processing

Received: 16 June 2020 Published: 29 April 2021

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	Articles by authors
	Qing-Kui MENG
	Jian-Xin ZHOU
	Qing SHU
	Wei GAO
	Guang-Jing XU
	Chen-Yang WANG

Cite this article:

Qing-Kui MENG,Jian-Xin ZHOU,Qing SHU, et al. Application effect of Kalman filter in airborne full tensor magnetic gradient measurement based on theoretical model[J]. Geophysical and Geochemical Exploration, 2021, 45(2): 473-479.

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https://www.wutanyuhuatan.com/EN/10.11720/wtyht.2021.1307 OR https://www.wutanyuhuatan.com/EN/Y2021/V45/I2/473

Full tensor magnetic gradient of sphere model

Full tensor magnetic gradient of noisy sphere model

Filtered full tensor magnetic gradient of sphere model

Comparison of B_xx ,B_yyand B_zz with before and after filtering(profile Y=500 m)

Comparison of B_xy ,B_xz and B_yzwith before and after filtering (profile Y=500 m)

Full area noise-reduction factor and mean square error

Quantitative statistics of Kalman filtering results of typical profile (Y=500 m)

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