In this paper, a geomagnetic matching navigation method that utilizes the geomagnetic vector is developed, which can greatly improve the matching probability and positioning precision, even when the geomagnetic entropy information in the matching region is small or the geomagnetic contour line’s variety is obscure. The vector iterative closest contour point (VICCP) algorithm that is proposed here has better adaptability with the positioning error characteristics of the inertial navigation system (INS), where the rigid transformation in ordinary ICCP is replaced with affine transformation. In a subsequent step, a geomagnetic vector information fusion algorithm based on Bayesian statistical analysis is introduced into VICCP to improve matching performance further. Simulations based on the actual geomagnetic reference map have been performed for the validation of the proposed algorithm.

In this study, Loran-C signals were collected throughout the day, and the characteristics of the received signals at different propagation distances were analyzed. Because the signal amplitude is small and difficult to recognize at a long distance and there is mutual interference between stations, a linear average method is used to process the received signal. At locations closer to the receiver, clear observations of the time delay and amplitude variation in the one-hop sky wave can be made by using the ground wave as a reference, which can be applied to studying the characteristics and parameter inversion of the lower ionosphere. When the distance is further, the significant enhancement of the sky-wave signal during the night may lead to decreased accuracy in timing and positioning. When the distance is much larger than the propagation range of the ground wave, only the sky-wave signal can be received, and the signal is more stable than when the distance is closer. During the night, multiple amplitude-comparable multi-path signals may appear in the sky wave, making the identification of the one-hop sky wave more difficult.

The complex frequency shifted (CFS) perfectly matched layer (PML) has been proven to be more efficient in attenuating evanescent waves and reducing late-time reflections than the original PML. In this letter, the piecewise linear recursive convolution (PLRC) method is combined with the bilinear transform (BT) to implement the CFS-PML for unmagnetized plasma simulation. Compared to the original bilinear transform implementation, the computational cost of the PLRC CFS-PML is greatly reduced with the same absorbing performance.

Purpose: This study aims to find a novel solution to the calibration of three-axis magnetometers to suppress errors of sensors. The nature of the calibration process is parameter estimation and hence the purpose of the paper is to calculate the error parameters and eliminate sensor errors and obtain the true value of the pure magnetic field. Design/methodology/approach: The paper puts forward a calibration method using an alternative iteration looping optimization (AILO) to estimate the parameters. The proposed method divided the parameters to be estimated into two parts: a portion less than one and the other greater than one. Parameters with different orders of magnitude are calculated respectively, which let one part to be a known quantity and the other part is derived by the known quantity; the derived quantity is used to calculate the known quantity again, and looping iteration multiple times until the iteration termination condition is satisfied. Findings: The simulation and experimental results indicate that the calibration accuracy is improved at least by two orders by the proposed method compared to the two-step method and the linear decreasing weight particle swarm optimization (LDW-PSO) algorithm which proves the validity of the proposed method. Practical implications: The proposed method can improve the calibration accuracy of total magnetic field, which provides a reference to the calibration of three-axis magnetometers. Originality/value: A calibration method based on the AILO is proposed in this paper, which is used to improve the calibration accuracy of the three-axis magnetometer.