Ionospheric clutter is a major factor affecting the performance of high frequency surface wave radar (HFSWR). Previous studies have been mainly focused on the development of ionospheric clutter suppression methods involving delicate signal processing techniques or additional antennas. However, ionospheric clutter originates from the interaction between HF waves and the ionosphere, thus it contains the characteristics of the latter. Therefore, ionospheric clutter can be analyzed to obtain the parameters of the reflecting ionosphere, expanding the value of HFSWR. This paper presents the preliminary coordinated observation and analysis results of the characteristics of the ionosphere at mid-latitudes of China using both HFSWR and ionosonde. The results demonstrate the existence of an oblique skywave propagation path (0.5 jump, 1 jump, etc.) in addition to the vertical reflection path and ionosphere-ocean mixed path. HFSWR beams were also found split into an O-trace and an X-trace after entering the ionosphere. Furthermore, range-folded ionospheric echoes are related to the short-term thickening of the F2-layer, showing strong fluctuation in the range-Doppler (RD) spectrum of HFSWR. These observed characteristics of ionospheric echoes are useful for the development of an efficient ionospheric clutter suppression algorithm for HFSWR and further investigation of the ionospheric mechanisms at mid-latitudes.

More recently, due to the enormous potential of long short‐term memory (LSTM) neural network in various fields, some efficient training algorithms have been developed, including the extended Kalman filter (EKF)‐based training algorithm and particle filter (PF)‐based training algorithm. However, it should be noted that if the system is highly non‐linear, the linearisation employed in the EKF may cause instability. Moreover, the PF usually suffers from the particle degeneracy. Therefore, the PF‐based training algorithm may only find a poor local optimum. To solve these problems, an unscented Kalman filter (UKF)‐based training algorithm is proposed. The UKF employs a deterministic sampling method; hence, there is no linearisation in it and it does not have the degeneracy problem. Moreover, the computational complexity of the UKF is the same order as that of the EKF. To further reduce the computational complexity, the authors propose a minimum norm UKF (MN‐UKF) to obtain a good trade‐off between performance and complexity. To the best of the authors’ knowledge, this is the first reported solution to this problem. Simulations using both benchmark synthetic signal and real‐world signal illustrate the potential of the algorithms developed.

In HFSWR (high-frequency surface-wave radar) system, the detection performance is impacted seriously by ionospheric clutter. Frequency selection is an effective method to avoid the effect of ionospheric clutter. The key to the method is the stationarity of ionospheric clutter over a period of time. This paper mainly researches the stationary time statistical property of the ionospheric clutter. A large number of real data including ionospheric clutter in HFSWR are processed and analyzed. It shows that ionospheric clutter in HFSWR has the characteristics of approximate stationarity within a period of time.

High Frequency Surface Wave Radar (HFSWR), which is currently applied in over-the-horizon detection of targets and sea states remote sensing, can receive a huge mass of ionospheric echoes, making it possible for the ionospheric clutter suppression to become a hot spot in research area. In this paper, from another perspective, we take the ionospheric echoes as the signal source rather than clutters, which provides the possibility of extracting information regarding the ionosphere region and explores a new application field for HFSWR. Primarily, pretreatment of threshold segmentation as well as connected region generation is used in the Range-Doppler (R-D) Spectrum to extract the ionospheric echoes. Then, electron density and plasma frequency of field aligned irregularities (FAIs) caused by plasma instabilities in the F region are obtained by the coherent backscattered radar equation. The plasma drift velocity of FAIs can also be estimated from Doppler shift. Ultimately, the effectiveness of inversion is verified by comparing with IRI2012.

In this paper, we consider a diffusive predator‐prey system where the prey exhibits the herd behavior in terms of the square root of the prey population. The model is supposed to impose on homogeneous Neumann boundary conditions in the bounded spatial domain. By using the abstract Hopf bifurcation theory in infinite dimensional dynamical system, we are capable of proving the existence of both spatial homogeneous and nonhomogeneous periodic solutions driven by Hopf bifurcations bifurcating from the positive constant steady state solutions. Our results allow for the clearer understanding of the mechanism of the spatiotemporal pattern formations of the predator‐prey interactions in ecology.

A theoretical model of the sky-wave path propagation with frequency modulated continuous wave (FMCW) source for high frequency (HF) radar is proposed in this paper. Based on the modeling of pulsed source, the expression of the received electric field with an FMCW source is derived for the reflection case from the ionospheric irregularities. Subsequently, the ionospheric reflection coefficient with different phase power spectrums for vertical and oblique backscattering propagation paths is incorporated into the ionospheric clutter model. Simulation results show that the peak power of FMCW in average is lower than that of pulsed waveform. Furthermore, different incident angles and magnetic field in mid-latitude can also influence the power density of the backscattering ionospheric clutter. Finally, the data analysis results from the high frequency surface wave radar (HFSWR) and Ionosonde collected in Yellow Sea preliminarily verify the inversion of the variance of the electron density fluctuation and the vertical drift velocity of the irregularities within ionosphere.