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.

Novel algorithm for geomagnetic navigation

To solve the highly nonlinear and non-Gaussian recursive state estimation problem in geomagnetic navigation, the unscented particle filter （UPF） was introduced to navigation system. The simulation indicates that geomagnetic navigation using UPF could complete the position estimation with large initial horizontal position errors. However, this navigation system could only provide the position information. To provide all the kinematics states estimation of aircraft, a novel autonomous navigation algorithm, named unscented particle and Kalman hybrid navigation algorithm （UPKHNA）, was proposed for geomagnetic navigation, The UPKHNA used the output of UPF and barometric altimeter as position measurement, and employed the Kahnan filter to estimate the kinematics states of aircraft. The simulation shows that geomagnetic navigation using UPKHNA could provide all the kinematics states estimation of aircraft continuously, and the horizontal positioning performance is better than that only using the UPF.

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.

Comparison of geomagnetic aided navigation algorithms for hypersonic vehicles

In this paper,we simulate,verify,and compare the performance of three classical geomagnetic matching aided navigation algorithms to assess their applicability to hypersonic vehicle navigation.Firstly,we introduce the various sources of the geomagnetic field.Secondly,we describe the principles and processes of the geomagnetic contour matching(MAGCOM)algorithm,iterative closest contour point(ICCP)algorithm,and Sandia inertial magnetic aided navigation(SIMAN)algorithm.Thirdly,we discuss the principles of inertial/geomagnetic integrated navigation,and propose the state and observation equations of integrated navigation.Finally,we perform a simulation of inertial/geomagnetic integrated navigation on the hypersonic boost-glide vehicle trajectory.The simulation results indicate that the real-time performance of the SIMAN algorithm can be optimized such that the matching accuracy is higher than that of the other two algorithms.At the same time,the SIMAN algorithm can achieve better stability,and though the amount of measurement noise can be larger,it can still achieve good positioning accuracy.

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.