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A filtering slot antenna with a simple structure combination using characteristic mode analysis (CMA) is proposed. To realize filtering characteristics, characteristic magnetic currents of line and ring slots are analyzed and designed. Then, the folding-line slot and double-ring slot are selected to realize radiation null separately and combined to construct the basic slot antenna. By properly exciting the selected characteristic modes, a wide filtering bandwidth and a stable gain are obtained. To validate the design process, a prototype antenna with a finite ground plane of about 1.1 λ × 1.1 λ is designed and fabricated. Simulated and measured results agree well, which both show a sharping roll rate in the lower and higher frequency and a flat gain realization in the pass band. The filtering bandwidth is 32.7%, the out-of-band suppression level at the higher frequency is over 20 dB, and the gain in the working frequency varies from 3.9 to 5.2 dB. [ABSTRACT FROM AUTHOR]

High-frequency (HF) radar plays a crucial role in the detection of far-range, stealth, and high-speed targets. Nevertheless, the echo signal of such targets typically exhibits a low signal-to-noise ratio (SNR) and significant amplitude fluctuations because their radar cross-section (RCS) accounting for the HF band is in the resonance region. While enhancing detection performance often requires long-time integration, existing algorithms inadequately consider the impact of amplitude fluctuation. In response to this challenge, this article introduces an improved approach based on coherent and non-coherent integration. Initially, coherent integration, employing the generalized Radon Fourier transform (GRFT), is utilized to derive a candidate detection set of targets' range–time trajectories. This involves a joint solution for range migration (RM) and Doppler frequency migration (DFM) through a multi-parameter motion model search. Subsequently, the removal of low SNR pulses, followed by non-coherent integration, is implemented to mitigate amplitude fluctuation, referred to as Amplitude Fluctuation Suppression (AFS), and refine the detection outcomes. Both simulation and experiment results are provided to prove the effectiveness of the proposed AFS-GRFT algorithm. [ABSTRACT FROM AUTHOR]

This article studies both experimentally and numerically the backscattering radar cross section (RCS) and Doppler spectrum characteristics from 2-D linear and nonlinear time-varying sea-like surface at UHF band under low grazing incidence. The small slope approximation and choppy wave model are applied to solve rough surface scattering and generate nonlinear sea waves, respectively. A coherent Doppler radar operating at 340 MHz was deployed at the tip of Huangqi peninsula in the southeast coast of China to measure the echo spectrum from the actual sea surfaces. At the same time, an ocean buoy was placed in the radar coverage to monitor the sea states. The RCS and Doppler spectrum are analyzed and compared comprehensively between radar measurements and numerical predictions. After compensating the influence of wind direction, the responses of radar echo power and numerical predicted RCS to wind speed are basically consistent and are more sensitive in low sea states. The correlation of Doppler spectra between radar measurements and numerical simulations exceed 0.96 during the whole experiment. The intensity of the high-order peaks increases rapidly with the wind speed, while the intensity of the Bragg peak decreases slightly. Doppler spectrum will be shifted by an amount proportional to radial surface current. [ABSTRACT FROM AUTHOR]

In this paper, Bragg and non-Bragg scattering mechanisms and frequency shifts from time-varying periodic water wave are studied from three aspects: wave tank measurements with an ultrahigh frequency radar, numerical simulation using the method of moments, and theoretical derivation applying the small perturbation method. The scattering field, radar cross section (RCS), and frequency shifts are discussed in both horizontal and vertical polarizations. The wave tank observations show that backscattering enhancement occurs when water wavelength is an integer multiple of Bragg wavelength, and there are several Doppler harmonics with frequency shifts of water-wave frequency and its integer multiples. Numerical simulations indicate that these Doppler harmonics except the one associated with the water-wave phase velocity are caused by the water surface edge effect. Moreover, theoretical analyses, numerical simulations, and wave tank experiments all show a clear exponential relationship between backscattering RCS and wave height. In addition, we further analyze the bistatic scattering and find that the scattering field is composed of plane waves propagating in the directions determined by water wavelength and radio wavelength, the bistatic frequency shift is the harmonic frequency of water wave, and the bistatic RCS also has an exponential relation with water-wave height. [ABSTRACT FROM AUTHOR]

Crossed-loop (CL)/monopole antenna has been widely used in high-frequency ground-wave radar for ocean surface remote sensing owing to its compact size. The multiple signal classification (MUSIC) algorithm is commonly adapted to achieve a favorable angular resolution for this broad beam antenna. However, the direction of arrival (DOA) estimation is always troubled by the frequently occurring distortion of antenna pattern. Previous studies are mainly focused on the calibration by using the actual pattern or other assistant algorithms. In this paper, theoretical analysis is made to illustrate the reason for pattern distortion, which draws a conclusion that the distortion is essentially due to the different influence of environmental obstacles upon the electric field part and magnetic field part. This also implies that there is nearly no distortion between the two loops, which is validated by three different experiments. Based on this conclusion, the DOA estimation performance of the MUSIC algorithm is studied by creating a numerical relationship associating the estimation error with distortion level. Furthermore, a new method using ideal pattern is proposed to improve the estimation performance by removing the amplitude information of monopole and relying on the CL processing. Both simulation and experimental results are given to prove its validity. [ABSTRACT FROM AUTHOR]

Windowing is a common method to reduce spectral leakage in Fourier analysis. Based on the principle that time domain multiplication corresponds to frequency domain convolution, this paper suggests frequency convolution to implement windowing functions by FIR filter structure. The proposed digital filter has full compatibility for variable length of window and is capable of implementing the three most popular windows, viz. Hanning, Hamming and Blackman. Numerical simulation indicates that the method consumes $$78\,\%$$ less area, $$11\,\%$$ higher throughput rate than the CORDIC-based (co-ordinate rotation digital computer) method, and achieves $$33\,\%$$ lower quantization error for fixed point than the time domain multiplication method. Furthermore, an example of stretch processing in HF radar is shown to reduce the $$99\,\%$$ computational complexity because of the segmental frequency points windowing. [ABSTRACT FROM AUTHOR]

Herein is proposed a low-power-density signal based on time-staggered frequency modulated continuous waveform (TS-FMCW) for portable high-frequency (HF) radar. According to the principle of pulse compression that the signal-to-noise ratio (SNR) is related to the total energy, the proposed signals can carry more energy to get higher SNR within same level power density in time–frequency plane. The range grating lobes and Doppler grating lobes shown in the ambiguity function of our proposed waveform can be avoided in the practical HF radar application. A signal processing architecture containing low-pass filtering and fast Fourier transform is proposed. Experimental results demonstrate that higher SNRs are achievable with the same range and Doppler resolution when the same power density is used as the conventional FMCW. [ABSTRACT FROM AUTHOR]

An efficient demodulation method designed for FMCW (Frequency-Modulated ContinuousWave) radar is presented. It is a kind of modified DFT (IDFT) algorithm; the spectrum segment of interest can be easily extracted from the original signal without calculating the whole DFT/FFT. It provides fast demodulation and extraction of desired frequency bands in our HFSWR (High- Frequency Surface Wave Radar) system. The proposed approach enhances the performances of radar system and reduces the computing complexity. The new structure could also be inversely used for signal modulation. And also arbitrary sampling rate conversion could be achieved with the combination of forward and backward structure. [ABSTRACT FROM AUTHOR]

• The UHF radar is applied to detect water-surface velocities to be used as the boundary condition for flow measurement. • The Reynolds-Averaged Navier-Stokes (RANS) is proposed to analyze cross-section velocity distribution. • The suggested methodology performs better than the power law and the log law especially in the narrow channel region. Non-contact flow measurement method plays an increasingly important role in river discharge measurement. However, most channel cross-section velocity distribution models proposed by researchers have certain limitations in application, underwater velocities are always necessary when applied in narrow channels, which makes it challenging to calculate natural river discharge using water-surface velocities measured by remote sensing instruments. This letter takes water-surface velocities detected by UHF radar as boundary conditions and a new velocity distribution model is derived based on the Reynolds-Averaged Navier-Stokes (RANS) equations. UHF radar measures surface velocities of the cross-section, and velocities on the river bed of the cross-section are considered to be 0. The RANS equations are simplified to be a two-dimensional Poisson equation and the cross-section velocity distribution is solved by using the closed boundary conditions. Some field experiments were conducted in the Hanjiang River at Xiantao, Hubei, China in September 2017 and April–July 2018, the processing results of which show that the proposed model is superior to the power law and the log law models, especially near the side wall (narrow channel region). River discharges calculated by this method are highly consistent with those provided by Hubei Xiantao hydrologic station, which verifies the reliability of the model and the feasibility of using UHF radar to measure natural river discharge continuously and automatically. [ABSTRACT FROM AUTHOR]

An effective method for radio frequency interference suppression in HF radars based on time-frequency analysis is proposed. The method performs well on ocean echo data acquired with the HF system OSMAR2000. It can also be regarded as a soft realisation of the real time radar working frequency selection. [ABSTRACT FROM AUTHOR]

The direction-finding high-frequency (HF) radar that employs a crossed-loop/monopole antenna as receiving has been widely applied in sea surface dynamics remote sensing due to its compact footprint and remarkable performance. Nevertheless, the direction-of-arrival (DOA) estimation of this system remains challenging in the case of coherent signals, which imposes a great threat to the radar measurement accuracy but has rarely been concerned in the past. In this article, a novel method combining the covariance matrix reconstruction process and subspace estimation technology is proposed to deal with this problem. By exploiting the purely real property of the array manifold, the rank loss of the covariance matrix due to the coherence of signals is mitigated. Both the theoretical derivation and numerical analysis prove that the proposed method is valid in estimating two coherent signals, and the DOA estimation accuracy is mainly related to the signal-to-noise ratio (SNR) and angle separation of the signals. Finally, field experiment data are also used to validate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

Based on the sea surface scattering mechanism of radio wave, compact high-frequency surface wave radar that employs the direction finding technology also shows promising potential for remotely mapping of ocean wave parameters. However, due to the low signal-to-noise ratio (SNR) of scattered echoes, the diverse external interference and clutter signals, other unresolved measurement uncertainties, the quality (such as accuracy, temporal, and spatial coverage rates) of wave maps are often limited. In this article, a novel, real-time, data quality control method is proposed to alleviate these issues. A comprehensive three-stage processing scheme is established, including the range-Doppler spectral processing, the spatial-grid processing, and the temporal-scale Kalman filtering. The first two stages aim to improve the echo signal quality and reduce the spatial gaps, respectively. The third stage is designed to mitigate the estimation error using an autoregression prediction model and to relate the observation error variance to the SNR of second-order Doppler spectral peak. A detailed verification and performance analysis between the field radar data and in situ ground truth data over one-month period is carried out, indicating that the proposed method can improve the reliability of wave maps with respect to the conventional Doppler spectral smoothing or averaging method, particularly in low sea state (i.e., low SNR) scenarios. [ABSTRACT FROM AUTHOR]

Attributed to the maneuverability, the shipborne high-frequency surface wave radar (HFSWR) enables a larger coverage in ocean wind measurement than a shored-based system does. However, the antenna aperture of shipborne radar is usually limited by the ship size, which troubles the direction of arrival (DOA) estimation accuracy. In addition, the wind direction ambiguity caused by monostatic radar illumination remains challenging. In this article, an unambiguous wind direction estimation method based on a compact shipborne HFSWR is proposed. An equivalent dual-station model combining the successive radar data collected at two close locations is developed to solve the DOA ambiguity in wind direction estimation. A direction-finding algorithm incorporating the Doppler shifts due to ship motion and current shear is adopted to estimate wind direction from the ratio of the positive and negative Bragg peak powers. Moreover, three different wave directional spreading models are applied for performance comparison. Numerical simulation is conducted to evaluate the effect of dual-station configuration on the estimation accuracy. Finally, field experimental results are given to verify the correctness of the method. Radar-derived wind direction field agrees well with that provided by a numerical weather model. [ABSTRACT FROM AUTHOR]

Compact high-frequency surface wave radar has been widely applied to the measurement of sea surface current, but its accuracy and direction resolution of wave parameter estimation are always limited due to the wide beam of the antenna. In this article, a novel wave-height mapping method based on the second-order harmonic peak (SHP) of radar Doppler spectra is proposed to address this concern. The characteristic of the SHP at the Doppler frequency of $\sqrt {2}$ times the Bragg frequency is studied through the theoretical derivation and numerical simulation. A relationship between the ratio ($R$) of the SHP power to the Bragg peak power and significant wave height ($H_{s}$) is derived. Furthermore, the $R$ – $H_{s}$ model is improved by incorporating influences, such as background noise and antenna beamwidth. With this improved model, a wave-height mapping algorithm based on the direction finding technique is presented. This approach enables the significant wave-height map extraction using a broad-beam radar. Finally, wave-height maps obtained at different sea states are depicted and analyzed, and the wave heights appearing on the maps are compared with buoy data over a one-month experiment to verify the validity and robustness of the algorithm. During this period, the significant wave height varies from about 0.5 to 4.5 m, and the radar measured wave heights at different range/distance bins show an overall root-mean-square error (RMSE) of 0.33–0.77 m and a correlation coefficient (CC) of 0.78–0.94, with respect to the buoy measurements. [ABSTRACT FROM AUTHOR]

Oceanic eddy is a common natural phenomenon that has large influence on human activities, and the measurement and detection of offshore eddies are significant for oceanographic research. The previous classical detecting methods, such as the Okubo–Weiss algorithm (OW), vector geometry algorithm (VG), and winding angles algorithm (WA), not only depend on expert's experiences to set an accurate threshold, but also need heavy calculations for large detection regions. Differently from the previous works, this paper proposes a deep eddy detection neural network with pixel segmentation skeleton on high frequency radar (HFR) data, namely, the deep eddy detection network (DEDNet). An offshore eddy detection dataset is firstly constructed, which has origins from the sea surface current data measured by two HFR systems on the South China Sea. Then, a spatial globally optimum and strong detail-distinguishing pixel segmentation network is presented to automatically detect and localize offshore eddies in a flow chart. An eddy detection network based on fully convolutional networks (FCN) is also presented for comparison with DEDNet. Experimental results show that DEDNet performs better than the FCN-based eddy detection network and is competitive with the classical statistics-based methods. [ABSTRACT FROM AUTHOR]

OSMAR-S, a portable high-frequency surface wave radar (HFSWR), has been in operation for ten years in China for current mapping and shares more than 80% of the domestic HFSWR radar market. In this article, comprehensive quantitative validation and intercomparison of sea state parameter estimation from the OSMAR-S radar with multiple other sensors over a period of two months are presented. These sensors include five buoys temporarily deployed at range from 10 to 85 km away from the radar and another two types of commercially available phased-array (PA) radar made in China. A performance validation method of HFSWR compared with buoys deployed in both the high-precision area (HPA) and the edge area of the radar coverage is proposed for a full evaluation in a wide range area. A quantitative evaluation method using a variety of statistical metrics and their weights is proposed to obtain a comprehensive score for comparing the performance of different types of HFSWR. The good agreements with buoy data in a wide coverage area demonstrate the good capability of sea state parameters measurement using the OSMAR-S radar. Compared with the other two PA radars, OSMAR-S also shows a better performance in terms of accuracy and stability. [ABSTRACT FROM AUTHOR]

Ocean wave height measurement using a wide-beam high-frequency surface wave radar (HFSWR) remains challenging due to its poor spatial resolution, which significantly limits the application of such compact systems. In this article, a novel method for wave height field extraction from the first-order Doppler spectra of a dual-frequency wide-beam radar is proposed. A model relating significant wave height to the ratio of the first-order spectral powers associated with two radar frequencies is put forward and studied numerically. Through theoretical analysis and experimental validation, it is confirmed that the first-order Doppler peaks of two radar frequencies have arisen from an approximately same direction of arrival (DOA), and their amplitudes are also affected by a similar wave directional spreading. Hereby, an algorithm combining beamforming and direction finding is developed to determine the spatial distribution of the first-order spectral power ratio and derive the significant wave height field. Finally, experimental results are given to verify the algorithm. The radar-derived wave height field agrees well with that obtained using a numerical wave model. Furthermore, the radar-measured wave heights are compared with the data collected by two buoys at the distances of 12.7 and 73 km, respectively. The comparison shows that the corresponding root-mean-square errors are 0.3 and 0.5 m and the correlation coefficients are 0.85 and 0.88, respectively. [ABSTRACT FROM AUTHOR]

Wave–current interaction is a common and important phenomenon in the ocean. As an ocean remote sensing tool, high-frequency (HF) radar can be used to measure currents and wave parameters. In this paper, the possibility of studying wave–current interaction using HF radar is investigated. The first-order spectral power (FSP) of HF radar is used to explore the effect of current on the Bragg wave. By analyzing the FSP change with current (FSP-current distribution), we find that, in deep water, the wave–current interactions mainly belong to 2-D refraction case, while, over a relatively shallow shelf, the interactions are stronger and more complicated. Based on local topography and current field data at Taiwan Strait, the simulation results obtained using the SWAN model confirm the 2-D refraction of the Bragg wave. When the wave–current interaction is stable, we compensate the FSP with radar-measured currents according to the radar extracted FSP-current distribution and achieve a more accurate wind estimation. Comparisons between the original and refined wind fields show the effectiveness and necessity of the current-based compensation. [ABSTRACT FROM AUTHOR]

This Special Issue hosts papers related to ocean radars including the high-frequency (HF) surface wave and sky wave radars, X-, L-, K-band marine radars, airborne scatterometers, and altimeter. The topics covered by these papers include sea surface wind, wave and current measurements, new methodologies and quality control schemes for improving the estimation results, clutter and interference classification and detection, and optimal design as well as calibration of the sensors for better performance. Although different problems are tackled in each paper, their ultimate purposes are the same, i.e., to improve the capacity and accuracy of these radars in ocean monitoring. [ABSTRACT FROM AUTHOR]

This study compared the efficiencies of two widely used automatic eddy detection algorithms-that is, the winding-angle (WA) method and the vector geometry (VG) method-and investigated the submesoscale eddy properties using surface current observations derived from high-frequency radars (HFRs) in the Taiwan Strait. The results showed that the WA method using the streamline and the VG method based on the streamfunction field have almost the same capacity for identifying eddies, but the former is more competent than the latter in capturing the eddy size. The two algorithms simultaneously identified 1080 submesoscale eddies, with the centers and boundaries determined only by the WA method, and they were further used to investigate the eddy properties. In general, no significant difference was observed between the cyclonic and anticyclonic eddies in terms of radius, life span, and kinematics, as well as the evolution during their life cycles. The typical radius of the eddy in this region was 3-18 km. And a strong correlation was observed between the life span and the radius. The spatial distribution of the eddies indicated that topography played a significant role in the generation of the eddies. And the trajectories of the eddies suggested that all the eddies in this area mostly tended to move southeastward. Statistically, three different stages of the eddy's life span could be identified by the significant growth and decay of the radius and the mean kinetic energy. This study shows the great capability of HFRs in oceanography research and applications, especially for observing the submesocale dynamics. [ABSTRACT FROM AUTHOR]

With the rapid development of deep learning, the neural network becomes an efficient approach for eddy detection. However, previous work employs a traditional neural network with a focus on improving the detecting accuracy only using limited data under a single scenario. Meanwhile, the experience of detecting eddies from one experiment is not directly inherited from the detection model for other experiments. Therefore, a cross-domain submesoscale eddy detection neural network (CDEDNet) based on the high-frequency radar (HFR) data of the Nansan and Xuwen region is proposed in this paper. Firstly, a fundamental deep eddy detection architecture CDEDNet-0 is constructed with a fully convolutional network (FCN). Secondly, for solving the problem of insufficient labeled eddy data, an instance-based domain adaption method is adopted in CDEDNet-1 to increase training samples. Thirdly, for tackling the problem of unable to inherit previous detection experience, parameter-based transfer learning is incorporated in CDEDNet-2 for multi-scene eddy detection. The experiment results demonstrate CDEDNet-1 and CDEDNet-2 perform better than CDEDNet-0 in terms of accuracy. Meanwhile, eddy characteristics including eddy type, radius, occurring time, merger, and dynamic trajectory are analyzed for the Nansan and Xuwen regions. [ABSTRACT FROM AUTHOR]

Compact high-frequency surface wave radar (HFSWR) plays a critical role in ship surveillance. Due to the wide antenna beam-width and low spatial gain, traditional constant false alarm rate (CFAR) detectors often induce a low detection probability. To solve this problem, a joint detection algorithm based on time-frequency (TF) analysis and the CFAR method is proposed in this paper. After the TF ridge extraction, CFAR detection is performed to test each sample of the ridges, and a binary integration is run to determine whether the entire TF ridge is of a ship. To verify the effectiveness of the proposed algorithm, experimental data collected by the Ocean State Monitoring and Analyzing Radar, type SD (OSMAR-SD) were used, with the ship records from an automatic identification system (AIS) used as ground truth data. The processing results showed that the joint TF-CFAR method outperformed CFAR in detecting non-stationary and weak signals and those within the first-order sea clutters, whereas CFAR outperformed TF-CFAR in identifying multiple signals with similar frequencies. Notably, the intersection of the matched detection sets by TF-CFAR and CFAR alone was not immense, which takes up approximately 68% of the matched number by CFAR and 25% of that by TF-CFAR; however, the number in the union detection sets was much (>30%) greater than the result of either method. Therefore, joint detection with TF-CFAR and CFAR can further increase the detection probability and greatly improve detection performance under complicated situations, such as non-stationarity, low signal-to-noise ratio (SNR), and within the first-order sea clutters. [ABSTRACT FROM AUTHOR]