Research On Algorithm Of Geomagnetic Navigation System

The geomagnetic navigation system is a completely autonomously navigationmethod with strong hidden ability. And it is not affected by terrain, weather,position and so on. So it can work in all regions and all seasons with very importantmilitary value. This article will study four problems. They are the established of themodel of IGRF, the demarcated of the geomagnetic sensor, the matching algorithmwith geomagnetic and integrated navigation system filtering. The details are asfollows.1. the model of IGRF is analyzed, and the source and factors of geomagneticfield are introduced. It is prepared for the observational equation modeling. To solveproblem of the geomagnetic sensor, whose three axes are not completelyperpendicular to one another, and the electrical characteristics are not completelysymmertry, the method of ademarcating and the experimental program is provided.2. Two commonly used algorithms which are the MAGCOM and the ICCPalgorithm are analyzed and simulated. From the simulation, it is easily to seethat,the MAGCOM algorithm is easy and its computing speed is very fast. But itsaccuracy is very low, and its heading error can not be corrected, As for ICCPalgorithm, its heading error can be corrected and its accuracy is high. but the initialerror is limited, it can not be too large.Or it will cause the match failed and fallinginto local optimum.The two methods related above are constrainted by the trajectoryshape and have bad real-time performance. So the intersected contour lines ofgeomagnetic field and gravitational field is given and simulated. The result provesits advantages to the common methods.3. The integrated navigation system filtering is studied. First, the state equationof INS system is given, and combined with the above model, the state space modelof integrated navigation system is established. Then the method of UPF is provided.Together with EKF, they are simulated and compared, from the result, it can be seen that:the latter(EKF) run simple and fast, it is limited by Gaussian noise with rightaccuracy; However, the former has good accuracy and wide application range, butits speed is poor, and is not limited by Gaussian noise. In a word, it is not fit to thehigh real-time requestion.