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An Aeromagnetic Compensation Strategy for Large UAVs.
Ye, Liwei; Yu, Zhentao; Zhang, Yaxun; Chi, Cheng; Cheng, Pu; Chen, Jie.
Afiliación
  • Ye L; Qingdao Innovation and Development Center, Harbin Engineering University, Qingdao 266500, China.
  • Yu Z; Institute of Remote Sensing, Navy Submarine Academy, Qingdao 266000, China.
  • Zhang Y; Qingdao Innovation and Development Center, Harbin Engineering University, Qingdao 266500, China.
  • Chi C; Institute of Remote Sensing, Navy Submarine Academy, Qingdao 266000, China.
  • Cheng P; Institute of Remote Sensing, Navy Submarine Academy, Qingdao 266000, China.
  • Chen J; Institute of Remote Sensing, Navy Submarine Academy, Qingdao 266000, China.
Sensors (Basel) ; 24(12)2024 Jun 10.
Article en En | MEDLINE | ID: mdl-38931558
ABSTRACT
Aeromagnetic surveys are widely used in geological exploration, mineral resource assessment, environmental monitoring, military reconnaissance, and other areas. It is necessary to perform magnetic compensation for interference in these fields. In recent years, large unmanned aerial vehicles (UAVs) have been more suitable for magnetic detection missions because of the greater loads they can carry. This article proposes some methods for the magnetic compensation of large multiload UAVs. Because of the interference of the large platform and instrument noise, the standard deviations (stds) of the compensation data used in this paper are larger. At the beginning of this article, using the traditional T-L model, we avoid the shortcomings of the anti-magnetic interference ability of triaxial magnetic gate magnetometers. The direction cosine information is obtained by using an inertial navigation system, the global positioning system, and a triaxial magnetic gate magnetometer. Then, we increase the amplitude of the maneuvers in the compensation process; this reduces the multicollinearity problems in the compensation matrix to a certain extent, but it also results in greater magnetic field interference. Lastly, we employ the method of Lasso regularization Newton iteration (LRNM). Compared to the traditional methods of least squares (LS) and singular value decomposition (SVD), LRNM provides improvements of 34% and 27%, respectively. In summary, this series of schemes can be used to perform effective compensation for large multi-load UAVs and improve the actual use of large UAVs, making them more accurate in the measurement of aeromagnetic survey data.
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Idioma: En Revista: Sensors (Basel) Año: 2024 Tipo del documento: Article País de afiliación: China

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Idioma: En Revista: Sensors (Basel) Año: 2024 Tipo del documento: Article País de afiliación: China