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Extraction of ocean surface wind field from data collected by shipborne high-frequency surface wave radar (HFSWR) is an ongoing challenge because of the inherent directional ambiguity and the effect of complicated platform motion on radar Doppler spectra. Here, a method for extracting the wind direction and speed from the spreading first-order radar Doppler spectra is first presented. First, the mathematical model of the wind direction versus a variable spreading parameter is developed. Moreover, based on the spreading characteristic of the first-order spectra, an approach for simultaneously determining the unambiguous wind direction and the unique spreading parameter with a single receiving antenna is presented. Furthermore, the relationship between the wind speed and the spreading parameter is derived on the basis of the relationship between the drag coefficient and the spreading parameter, and the wind speed can be determined. Therefore, the wind field of ocean area covered by shipborne HFSWR can be measured by sequentially exploiting the presented method, which is more beneficial for shipborne HFSWR because of smaller installation space and less cost. Simulation results and discussions of basic applications show the feasibility of wind field measurement in shipborne HFSWR. Experimental results validate the presented method and evaluate the detection accuracy and distance limit. The range for wind field measurement is up to 120 km, which is the range for which the signal-to-noise ratio typically exceeds about 11 dB in the relevant first-order portions of the backscatter spectra. Comparisons between the radar-measured and forecasting or buoy-measured results show good agreement. [ABSTRACT FROM AUTHOR]

Shipborne high-frequency surface wave radar (SHFSWR) has exhibited great advantages over onshore HFSWR (OHFSWR) in ocean remote sensing. Unlike OHFSWR, SHFSWR suffers the problem of Doppler spectrum spread owing to platform movement, which is a great challenge preventing the extraction of ocean surface parameters for SHFSWR. To address this challenge, in this letter, the mathematical model of ocean surface wind direction is first investigated based on the first-order SHFSWR cross section. Furthermore, a method for the wind direction inversion without ambiguity from the spread Doppler spectrum is proposed using a single receiving antenna. Meanwhile, the wind directions of the sea area covered by radar can be obtained by sequentially utilizing the proposed method, which is more appropriate for the application of SHFSWR with limited deck space and less cost. Experimental results of the real data collected in Taiwan Strait preliminarily verify the detection accuracy and the distance limit of the wind direction inversion, as the root-mean-square error and the detection range are 9.85° and 120 km, respectively [ABSTRACT FROM PUBLISHER]

Sea clutter has a major impact on the detection performance of a shipborne high-frequency surface wave radar (HFSWR) system. Due to the platform motion of shipborne HFSWR, the Doppler spectrum of the first-order sea clutter suffers from some broadening so that the targets submerged in this broadening Doppler spectrum can be hardly detected. In this letter, an improved oblique projection (IOP) method, combining the oblique projection (OP) algorithm and the method of sea clutter suppression in the Doppler domain, is proposed to suppress sea clutter in both Doppler domain and spatial domain for shipborne HFSWR. Compared with the OP and the orthogonal weighting algorithms, the proposed IOP algorithm is shown to give far superior suppression results in the Doppler domain and can achieve better azimuth estimation results based on real data. [ABSTRACT FROM PUBLISHER]

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]

To investigate the characteristics of sea clutter, based on ocean surface electromagnetic scattering theory, the first- and second-order ocean surface scattering cross sections for bistatic high-frequency (HF) radar incorporating a multi-frequency six degree-of-freedom (DOF) oscillation motion model are mathematically derived. The derived radar cross sections (RCSs) can be reduced to the floating platform based monostatic case or onshore bistatic case for corresponding geometry setting. Simulation results show that the six DOF oscillation motion will result in more additional peaks in the radar Doppler spectra and the amplitudes and frequencies of these motion-induced peaks are decided by the amplitudes and frequencies of the oscillation motion. The effect of the platform motion on the first-order radar spectrum is greater than that of the second-order, and the motion-induced peaks in the first-order spectrum may overlap with the second-order spectrum. Furthermore, yaw is the dominant factor affecting the radar spectra, especially the second-order. Moreover, the effect of platform motion on radar spectra and the amplitudes of the second-order spectrum decreases as the bistatic angle increases. In addition, it should be noted that the amplitudes of the Bragg peaks may be lower than those of the motion-induced peaks due to the low frequency (LF) oscillation motion of the floating platform, which is an important finding for the applications of the floating platform based bistatic HF radar in moving target detection and ocean surface dynamics parameter estimation. [ABSTRACT FROM AUTHOR]