journal article·2022-08-01Open access

Characteristic analysis and blind area prediction of aeromagnetic scalar gradient detection method

Ming Chang, Lei Xu, Xin Pang, Jiawei Zhang, Houpu Li, Mingzhen Lin

AIP Advances· Volume 12· Issue 8

Abstract

To analyze the characteristics of the aeromagnetic scalar gradient detection method, a uniformly magnetized ellipsoid is used to simulate an unexploded ordnance, and a magnetic field detection model is established in the International Geomagnetic Reference Field based on rotation matrices. Furthermore, the spatial distribution of the target’s magnetic field is simulated. The results indicate that the scalar gradient detection curve is closely related to the unmanned aerial vehicle (UAV) heading, geomagnetic direction, and target attitude. According to the measured data, the aeromagnetic detection system exhibits differences in the detection of different headings, indicating that some “blind areas” exist in the scalar gradient magnetic detection method. The experimental measurement by a quadrotor UAV equipped with two optical pump magnetometers verifies that the scalar gradient detection method can effectively eliminate the geomagnetic field as well as the interferences of the UAV itself. Furthermore, the angular relationship between the target magnetic field contour distribution and the heading is found to be the main reason that the scalar gradient detection system enters the “blind detection area.” Therefore, a flight strategy of “positive direction + orthogonal grid” is proposed. This method effectively reduces the missed detection rate of scalar gradient detection and provides strategic guidance for the detection path of aeromagnetic scalar gradient system.
Source: crossref · Quality: baseline

Research context

OpenAlex topics: Geomagnetism and Paleomagnetism Studies · Inertial Sensor and Navigation · Geophysical and Geoelectrical Methods

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

College of Weapons Engineering, Naval University of Engineering 1 , Wuhan 430033, China

92859 Troops 2 , Tianjin 300061, China

Unit 92840 of the PLA 3 , Dalian 116000, China

College of Electrical Engineering, Naval University of Engineering 4 , Wuhan 430033, China

College of Political Theories, Naval University of Engineering 5 , Wuhan 430033, China

Funding

National Natural Science Foundation of China · National Science Fund for Distinguished Young Scholars

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