Magnetic surveys are conventionally performed by scanning a domain with a portable scalar magnetic sensor. Unfortunately, scalar magnetometers are expensive, power consuming, and bulky. In many applications, calibrated vector magnetometers can be used to perform magnetic surveys. In recent years, algorithms based on artificial intelligence (AI) achieve state-of-the-art results in many modern applications. In this paper, we investigate an AI algorithm for the classical scalar calibration of magnetometers. A simple, low-cost method for performing a magnetic survey is presented. The method utilizes a low-power consumption sensor with an AI calibration procedure that improves the common calibration methods and suggests an alternative to the conventional technology and algorithms. The setup of the survey system is optimized for quick deployment in situ right before performing the magnetic survey. We present a calibration method based on a procedure of rotating the sensor in the natural earth magnetic field for an optimal time period. This technique can deal with a constant field offset and non-orthogonality issues and does not require any external reference. The calibration is done by finding an estimator that yields the calibration parameters and produces the best geometric fit to the sensor readings. A comprehensive model considering the physical, algorithmic, and hardware properties of the magnetometer of the survey system is presented. The geometric ellipsoid fitting approach is parametrically tested. The calibration procedure reduced the root-mean-square noise from the order of 104 nT to less than 10 nT with variance lower than 1 nT in a complete 360° rotation in the natural earth magnetic field. In a realistic survey scheme, the obtained calibration noise is suited to the environmental survey clutter. Implementing this scheme with a modern low-power analog-to-digital convertor and micro-controller results in power consumption lower than 15 mW and calibration duration of few minutes.
Bibliographical notePublisher Copyright:
© 1965-2012 IEEE.
- Three axis
- artificial intelligence (AI)
- in situ