Search

In addition to target echoes, high frequency surface wave radar (HFSWR) receives sea and ionospheric clutter. Among these clutters, the ionospheric clutter is dominant and significantly affects the detection performance of HFSWR, particularly when the targets are located 100 kilometers away from the radar, rendering it an unsolved problem for HFSWR. Existing studies concerning HFSWR ionospheric clutter lack empirical research on the nonlinear dynamical characteristics of the ionosphere of HFSWR as existing ionospheric suppression methods are still insufficient to adapt the project application. Therefore, the present study utilized the threshold segmentation method to eliminate the sea clutter in HFSWR Range-Doppler spectrum and extracted ionospheric signals from this spectrum by edge feature extraction. Subsequently, the chaotic invariants, such as correlation dimension and the largest Lyapunov exponent of HFSWR ionospheric clutter, were calculated by phase space reconstruction, whilst the chaotic dynamical characteristics of HFSWR ionospheric clutter were determined by the 0-1 test for chaos and other algorithms. Furthermore, the present study demonstrated, for the first time, the chaotic dynamics of the ionospheric clutter of HFSWR with a low-dimensional attractor by processing and analyzing the experimental data from the Weihai High Frequency Radar Station. The conclusion redefines HFSWR ionospheric clutter based on chaotic dynamics rather than regarding it as a stochastic process, which is conducive to efforts to explore the formation mechanism of ionospheric clutter in essence, which can ultimately improve the detection capability of HFSWR, particularly for long-distance targets.

High frequency surface wave radar (HFSWR) is traditionally unable to detect target altitude information. To simultaneously estimate the target altitude and radar cross-sections (RCS) with bistatic HFSWR, a novel estimation model is proposed with the variation of the propagation attenuation, and the target echoes are utilized to construct the measurement equation. The presented model is completely observable to the target state, which can contribute to preferable estimation results. In order to improve the estimation accuracy, a centralized fusion model is adopted to fuse four measurement vectors. Simulations and practical examples demonstrate the effectiveness of the proposed estimation model.

Investigating the dynamic evolution process of the ocean and ionosphere in sudden sea conditions poses a challenging problem. To address this objective, this study utilizes actual data from high-frequency surface wave radar (HFSWR) to analyze, validate, summarize, and characterize the echo properties of the ocean and ionosphere during the severe Typhoon Muifa. By employing the short-time Fourier transform (STFT) method, the HFSWR ocean and ionosphere echoes stimulated by typhoon-induced gravity waves are observed, and the joint gravity wave features of the ocean and ionosphere echoes at different time scales are extracted. Additionally, the phase-space reconstruction method is employed to characterize the dynamical evolution of the joint gravity wave features in higher-dimensional space. Furthermore, the chaotic dynamics behavior of the joint gravity wave features is analyzed using the largest Lyapunov exponents. By combining the gravity wave features with chaotic dynamics, this study introduces a method to characterize the joint gravity wave features. The extraction of joint gravity wave features in HFSWR echoes stimulated by typhoons, along with the construction of a chaotic characterization scheme for the gravity wave features, provides an innovative approach and a solid technical foundation for studying the ocean and ionosphere using HFSWR under sudden sea conditions. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

High frequency surface wave radar (HFSWR) cannot detect target altitude directly and is unable to identify flight mode. Assuming that the estimation and identification processes are mutually dependent, an integrated method called simultaneous identification and estimation (SIE) is proposed by applying a two-level multiple model approach to the flight mode probability mass function (pmf) and state probability density function (pdf) simultaneously. The SIE involves two altitude estimation mode-conditioned model sets, which are established utilizing the variation property of the propagation attenuation at different flight modes. The multiple model approach incorporated in SIE is different from the traditional interacting multiple model (IMM). It is applied at two levels: within each mode-conditioned estimation model set and across all the mode-conditioned estimation model sets. Simulations and real trials demonstrate the performance of the proposed SIE method. [ABSTRACT FROM AUTHOR]

The spreading of the dominant first-order Bragg lines in shipborne high-frequency surface wave radar (HFSWR) severely obscures the detection of the slow-moving targets and the measurement of ocean clutter. Space–time adaptive processing (STAP) is an effective tool for solving the problem. It normally requires a large number of independent and identically distributed (i.i.d.) training samples to estimate the ocean clutter spectrum and design the filter to eliminate the ocean clutter from the test cell. However, the training samples are insufficient due to the system limitation of shipborne HFSWR, and the stationarity of training data is destroyed in the nonstationary and nonhomogeneous ocean environment, which result in decreased performance. Thus, the estimation of the ocean clutter spectrum with small training samples or even only the test cell is an important work for shipborne HFSWR. In this paper, by exploiting the intrinsic sparsity of the ocean clutter in shipborne HFSWR, the multiple signal classification (MUSIC) algorithm based on the sparse representation technique, called SR–MUSIC, is introduced to estimate the ocean clutter spectrum. The correctness of the ocean clutter sparsity and the validity of the SR–MUSIC algorithm for the high-resolution ocean clutter spectrum estimation are verified by the simulation results. [ABSTRACT FROM PUBLISHER]

The work presented in this paper makes two contributions for exploiting Doppler (range rate) measurements in tracking systems. First, a new linear filter, the converted Doppler measurement Kalman filter (CDMKF), is presented to extract nonlinear pseudostates from converted Doppler measurements (i.e., the product of the range measurements and Doppler measurements). The pseudostates are constructed from the converted Doppler and its derivatives. The linearly evolving equations of the pseudostates are derived for common target motion models. The second contribution of this paper is using the CDMKF along with the converted position measurement Kalman filter (CPMKF), in which only the position measurements are used, to establish a new filtering structure, statically fused converted measurement Kalman filters (SF-CMKF). The resulting states of CPMKF and CDMKF are combined by a static minimum mean squared error (MMSE) estimator, where the nonlinearity and correlation between the pseudostates and the Cartesian states are handled simultaneously, to yield the final state estimates. The dynamic nonlinear estimation problem is converted into dynamic linear estimation followed by static nonlinear fusion. The estimation accuracy can be enhanced by incorporating the Doppler measurements via the linear CDMKF, while the filtering stability can be improved by dealing with nonlinearity outside the filtering recursions. Monte Carlo simulations and comparison with the posterior Cramer-Rao bound demonstrate the effectiveness of the CDMKF and SF-CMKF. [ABSTRACT FROM PUBLISHER]

In this paper we present a population declining ant colony optimization (PDACO) multiuser detector for asynchronous CDMA communications. Ant colony optimization (ACO) algorithms have already been used in multiuser detection in CDMA systems; however, as the pheromone accumulates, we may not get a global optimum because it stops searching early. PDACO can enlarge searching range through increasing the initial population of the ant colony, and the population declines in successive iterations. So, the performance of PDACO is superior with the same computational complexity. PDACO is applied to multiuser detection in asynchronous CDMA systems over slowly multipath Rayleigh-fading channels in this paper. Via computer simulations it is shown that the performance of PDACO detector is much better in bit-error rate and near-far effect resistance than conventional detector, ACO detector and genetic algorithm detector, and is close the optimal multiuser detector. [ABSTRACT FROM AUTHOR]

This paper describes the principle of the target detection and estimation with a high frequency ground wave over-the-horizon radar, introduces the structure and the implementation of the detection and estimation subsystem that can process signals in parallel. The accomplished experimental results demonstrate that this system can successfully detect and estimate the over-the-horizon ship and aircraft [ABSTRACT FROM PUBLISHER]