In this letter, an ultrawideband (UWB) multiple-input-multiple-output (MIMO) antenna using a novel fence-type decoupling structure, which has high isolation in the UWB, is presented. The MIMO design consists of two half-cutting UWB antenna units that have good low-frequency impedance-matching performance because of the use of a rectangular slot on the radiation patch. Meanwhile, the isolation in the operating band is enhanced by introducing the fence-type decoupling structure at the ground of the antenna. Furthermore, the L-shaped parasitic branches are designed to heighten the impedance bandwidth and isolation in the low-frequency band, i.e., 3-3.4 GHz. The simulation and experiments show that the antenna has low mutual coupling (S21 <; -25 dB) and a low envelope correlation coefficient (ECC <; 0.004) in the UWB.

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.

We previously used back propagation neural network (BPNN) with the meteorological factors of the receiver point to establish a model for predicting propagation delay of Loran-C signal over a short distance. Nevertheless, for a long propagation path, it is not proper to use only the meteorological factors of the receiver point. In this letter, a propagation delay prediction model that considers multiweather and multipoint was established by using a more suitable generalized regression neural network (GRNN) over a long distance. We first compared three meteorological factors of six points on the propagation path, and found that they have obvious differences. Then, a propagation delay prediction model based on three meteorological factors of the six points is established with GRNN. Finally, the further comparison shows that on the one hand, GRNN is more suitable to establish the prediction model of propagation delay than BPNN; on the other hand, more points on the propagation path are considered, and the prediction accuracy of the model is higher.

A small ultrawideband (UWB) slot antenna is proposed using a stepped impedance resonator feeding line, aiming at improving band-edge selectivity. The proposed antenna mainly comprises a feeding line with low-pass characteristics at the top of the dielectric substrate and two slots at the bottom. The stepped impedance resonator is used to improve the upper band-edge selectivity, and the narrow slot near the stepped slot improves the lower band-edge selectivity. The frequency selection range, the frequency selective characteristic, and the reflected zeros of the antenna upper band-edge are analyzed and studied. The measured results show that the antenna covers the frequency range of UWB systems from 3.1 to 11 GHz (114%) with the reflection coefficient less than -10 dB. Compared with the traditional UWB antenna, the proposed compact antenna has advantages in size and band-edge selectivity and is more suitable for UWB applications. The ratio of the -3 dB bandwidth to the -10 dB bandwidth is 1.038, which is very close to 1.

A stochastic finite-difference time domain (S-FDTD) combined with the piecewise linear recursive convolution method is applied to model wave propagation in unmagnetized plasma with random plasma frequency. The stretched-coordinate perfectly matched layer implementation of the S-FDTD method is also presented. The accuracy and efficiency of the proposed algorithm are validated by numerical examples.