Bio-inspired geomagnetic navigation method for autonomous underwater vehicle

This paper presents a bio-inspired geomagnetic navigation method for autonomous underwater vehicle(AUV) without using any a priori geomagnetic information. Firstly, the multi-objective search problem is raised. Secondly, the geomagnetic navigation model is established by constructing a cost function. Then, by taking into consideration the biological magneto-taxis movement behavior for the geomagnetic environment stimulus, the multiobjective evolutionary search algorithm is derived to describe the search process. Finally, compared to the state-of-the-art, the proposed method presents better robustness. The simulation results demonstrate the reliability and feasibility of the proposed method.

Direction navigability analysis of geomagnetic field based on Gabor filter

Direction navigability analysis is a supplement to the navigability analysis theory, in which extraction of the direction suitable-matching features(DSMFs) determines the evaluation performance. A method based on the Gabor filter is proposed to estimate the direction navigability of the geomagnetic field. First,the DSMFs are extracted based on the Gabor filter’s responses.Second, in the view of pattern recognition, the classification accuracy in fault diagnosis is introduced as the objective function of the hybrid particle swarm optimization(HPSO) algorithm to optimize the Gabor filter’s parameters. With its guidance, the DSMFs are extracted. Finally, a direction navigability analysis model is established with the support vector machine(SVM), and the performances of the models under different objective functions are discussed. Simulation results show the parameters of the Gabor filter have a significant influence on the DSMFs, which, in turn, affects the analysis results of direction navigability. Moreover, the risk of misclassification can be effectively reduced by using the analysis model with optimal Gabor filter parameters. The proposed method is not restricted in geomagnetic navigation, and it also can be used in other fields such as terrain matching and gravity navigation.

Calibration and compensation methods of installation error of electronic compass

Installation error angle is one of the factors that affect the accuracy of electronic compass used for geomagnetic navigation.To solve this problem,the calibration and compensation methods for installation error angle are studied.By analyzing the generation mechanism of installation error angle of electronic compass,an installation error model is established,compensation formulae are derived,and calibration scheme is proposed.To verify the correctness of the calibration and compensation methods,the verification experiment is conducted by computer simulation.The simulation results show that the proposed calibration and compensation methods are effective and practical.

Multi-geomagnetic-component assisted localization algorithm for hypersonic vehicles

Owing to the lack of information about geomagnetic anomaly fields,conventional geomagnetic matching algorithms in near space are prone to divergence.Therefore,geomagnetic matching navigation algorithms for hypersonic vehicles are also prone to divergence or mismatch.To address this problem,we propose a multi-geomagnetic-component assisted localization(MCAL)algorithm to improve positioning accuracy using only the information of the main geomagnetic field.First,the main components of the geomagnetic field and a mathematical representation of the Earth’s geomagnetic field(World Magnetic Model 2015)are introduced.The mathematical relationships between the geomagnetic components are given,and the source of geomagnetic matching error is explained.We then propose the MCAL algorithm.The algorithm uses the intersections of the isopleths of the geomagnetic components and a decision method to estimate the real position of a carrier with high positioning accuracy.Finally,inertial/geomagnetic integrated navigation is simulated for hypersonic boost-glide vehicles.The simulation results demonstrate that the proposed algorithm can provide higher positioning accuracy than conventional geomagnetic matching algorithms.When the random error range is±30 nT,the average absolute latitude error and longitude error of the MCAL algorithm are 151 m and 511 m lower,respectively,than those of the Sandia inertial magnetic aided navigation(SIMAN)algorithm.