Geomagnetic/Inertial Fusion Navigation Method Based on Magnetic Anomaly Gradient Measurement

Geomagnetic navigation is an autonomous navigation method that utilizes the natural magnetic field of the Earth. It has various advantages such as strong autonomy and good anti-interference performance, and can work normally in various environments to play its role. However, in the fields of low altitude navigation and underwater navigation, geomagnetic matching navigation requires the construction of geomagnetic maps based on a large amount of measurement data, and requires the motion platform equipped with this navigation method to have high computing power. The above issues bring inconvenience to the application of geomagnetic navigation. Inertial navigation method is a commonly used autonomous navigation method that has high accuracy in a short period of time. However, over time, its navigation results will have significant cumulative errors, which will affect the accuracy of navigation positioning. This article extracts differential information of magnetic anomaly fields from the total measurement information of the Earth's magnetic field through differential measurement information at different positions during platform movement, as the observation of the paper. Meanwhile, based on the magnetic dipole characteristics of the magnetic anomaly field, this article derives a magnetic anomaly gradient measurement matrix that can be applied to navigation system filters on the basis of the magnetic dipole model theory. By using the magnetic anomaly gradient information to correct the cumulative error of the inertial navigation system, a geomagnetic/inertial fusion navigation method is proposed. This method can reduce the requirement for high-precision prior geomagnetic maps in geomagnetic navigation, while also correcting navigation errors in inertial navigation. Comparing the navigation method proposed in this article with the pure inertial navigation method, it was found that the navigation position accuracy of this method has significantly improved under the same conditions. The research conducted in this article explores a new method for autonomous navigation of motion platforms.