Coherent S-band radar has recently been emerged as a promising technique for ocean surface wave and current detection. It can measure ocean surface current by estimating Doppler frequency shifts from sea surface signals. However, the conventional time averaging (TA) method neglects spatial dimension information and is unavailable under low wind speed condition. Two algorithms for ocean current inversion are proposed in this letter: the spatial-temporal averaging (STA) method and the wavenumber-frequency (WF) method. In the STA method, the TA method is extended to the spatial-temporal domain. This approach fully exploits the spatial continuity of radar signals. In the WF method, a 2-D Fast Fourier Transform (2-D FFT) is applied to transform the spatial-temporal radial velocities into the wavenumber-frequency domain. After employing dual filtering to eliminate nonlinear components, the radial current velocity is estimated through a modified dispersion relation fitting. The two methods are based on different physical mechanisms: the STA method measurements include wind drift components, while the WF method remains unaffected by wind drift. Therefore, wind drift can be effectively estimated by calculating the difference between the two methods’ measurements. Validation using observational data collected at Beishuang Island during Typhoon Catfish shows that the estimated wind drifts achieve a correlation coefficient (COR) of 0.90 with the “empirical model predictions”. This confirms the effectiveness of the proposed algorithms.

In this letter, we propose a novel methodology for retrieving wave parameters, i.e., significant wave height and mean wave period, in near-nadir looking mode using a 77 GHz frequency-modulated continuous-wave (FMCW) multipleinput– multiple-output (MIMO) radar. First, the range-Doppler spectrum is estimated from the raw radar data, and the time-Doppler spectrum in the desired direction is obtained by integrating the digital beamforming algorithm with MIMO array techniques. Next, the radial velocity series are calculated using the spectral moment method. A Fourier transform is then applied to estimate the wave height spectrum from the radial velocity series, and the significant wave height and mean wave period can be obtained by the moment estimation method. Finally, the results obtained from numerical simulations and sea surface observations demonstrate that the retrieval method can extract wave parameters with reasonable performance at small incidence angles (0∼18°).

The broadening first-order sea clutters caused by the signals from different directions with various radial current velocities create severe disturbance for target detection using high-frequency surface wave radar (HFSWR). Conventional sea clutter suppression methods tend to remove the sea clutter and target signals when they are mixed in the Doppler spectrum. Based on the characteristics of the target signal and sea clutter in spatial–temporal domain, a new first-order sea clutter suppression method for HFSWR using orthogonal projection is proposed. The proposed method uses the data from multichannels and slow-time domain at the adjacent range cell to construct a covariance matrix, which can be used to obtain the sea clutter subspace by eigendecomposition. Later, original signals are projected onto the sea clutter subspace. Finally, subtract the component of the original signals in the sea clutter subspace from the original signals to achieve the suppression of sea clutter by retaining the target signals. The simulation and experimental results for a single target and multiple targets cases indicate that the proposed method can suppress the first-order sea clutter effectively, which enhances the target detection capacity in the sea clutter zone for HFSWR.

A small-aperture receiving array occupying a small area provides convenience for the layout of HF radars. However, this kind of antennas has a wide beam, which adversely affects wave measurements. To solve this problem, a method for extracting wave parameters from wide-beam radar echoes, that models current variations across the beam, is proposed in this article. The nondirectional wave spectrum is extracted from the echoes of a small-aperture HF radar and wave parameters such as the significant wave height, the peak and mean wave period are then calculated from it. Simulation is carried out to assess the performance of the method for different current velocities, radar frequencies and wind conditions. The proposed method is then applied to a 9-day data set collected by an MHF-C radar for further validation via comparisons between the radar-estimated and the buoy-measured wave parameters. Some factors that may affect the performance of wave height measurements are analyzed, such as the signal-to-noise ratio and radial current velocity. The correlation coefficient (CC) between the radar-estimated and the buoy-measured significant wave height is 0.90, and the root mean square difference (RMSD) is 0.51 m. For the mean wave period, the CC is 0.61 and the RMSD is 0.67 s. The results demonstrate that the significant wave height and the mean wave period extracted by the proposed method are consistent with the buoy-measured values and the proposed method can overcome the broadening influence of the Doppler spectrum caused by ocean currents.

Wind speed inversion is a challenging work in the field of ocean surface remote sensing with high-frequency (HF) radars. Recently, the wind speed inversion method based on the first-order HF radar sea echoes attracts much attention. However, most methods, which use radar data at a fixed operating frequency, provide a limited range for wind speed measurement. To overcome the drawback, a wind speed inversion method based on radar data collected with a multifrequency HF radar is proposed. This new method first fits the relationship between the wind speed and the power of the broad-beam first-order HF radar sea echoes and then combines the fit models with the multifrequency HF radar data to estimate wind speed. The proposed method makes use of the information contained in the first-order sea echoes of various operating frequencies so as to improve the performance of the wind speed measurements. Finally, a comparison between radar-estimated and anemometer-measured wind speeds is made to validate the proposed method. Compared with the anemometer data, the wind speeds estimated by the proposed method have a root-mean-square error (RMSE) of 2.27 m/s.

HF radars have been extensively used for current observation. However, wave measurement with HF radars is challenging mainly due to the limited measurable range of wave height using a single operating frequency. In order to obtain robust wave measurements in complex and various sea states, a wave inversion method is proposed for a multifrequency HF radar. In this method, the nondirectional wave spectrum is directly retrieved from the radar echoes collected at various frequencies (up to four), and then, the significant wave height and the mean wave period are obtained from the integration of the derived nondirectional wave spectrum. Simulation analysis is carried out to evaluate the performance of the proposed method for a case in four various radar frequencies. Then, the proposed method is applied to a three-day observation to validate its advantages by comparing the radar-estimated and WaveRider-measured nondirectional wave spectra. In addition, a 14-day dataset collected with an HF radar operating at 8.267 and 19.2 MHz during a super Typhoon event is selected for further validation via comparisons between the radar-estimated and the buoy-measured wave parameters. The results indicate that the agreement between them is reasonable, and the comparisons also demonstrate that the accuracy of the wave measurement using the proposed multifrequency method is better than that with a single frequency.