High Frequency Surface Wave Research Articles

Coast–Ship Bistatic HF Surface Wave Radar: Simulation Analysis and Experimental Verification

The coast–ship bistatic high-frequency surface wave radar (HFSWR) not only has the anti-interference advantages of the coast-based bistatic HFSWR, but also has the advantages of maneuverability and an extended detection area of the shipborne HFSWR. In this paper, theoretical formulas were derived for the coast–ship bistatic radar, including the first-order sea clutter scattering cross-section and the Doppler frequency shift of moving targets. Then, simulation results of the first-order sea clutter spectrum under different operating conditions were given, and the range of broadening of the first-order sea clutter spectrum and its influence on target detection were investigated. The simulation results show the broadening ranges of the right sea clutter spectrum and left sea clutter spectrum were symmetric when the shipborne platform was anchored, whereas they were asymmetric when the shipborne platform was underway. This asymmetry is primarily a function of platform velocity and radar frequency. Based on experimental data of the coast–ship bistatic HFSWR conducted in 2019, the broadening range of the sea clutter and the target frequency shift were analyzed and compared with simulation results based on the same parameter configuration. The agreement of the measured results with the simulation results verifies the theoretical formulas.

HF Radar Ocean Surface Cross Section for the Case of Floating Platform Incorporating a Six-DOF Oscillation Motion Model

To interpret the characteristics of ocean surface echo signals, the general first- and second-order high-frequency surface wave radar (HFSWR) ocean surface scattering cross sections are mathematically derived for an omnidirectional receiving antenna being deployed on a floating ocean platform incorporating a six-degree-of-freedom (DOF) oscillation motion model. The six-DOF oscillation motion includes sway, surge, yaw, heave, pitch, and roll. The derived radar cross sections can be degenerated to existing results involving some simple oscillation motion models or an onshore case. Simulation results show that six-DOF oscillation motion can induce additional peaks in radar spectra and these motion-induced peaks appear symmetrically in frequency. Furthermore, the positions and intensities of these motion-induced peaks depend on the angular frequency and amplitude of each 1-D oscillation motion. In particular, the intensities of the Bragg peaks may be lower than those of the motion-induced peaks in some conditions, which is an extremely important phenomenon for ocean remote sensing using floating-based platform HFSWR. In addition, yaw appears to have the largest effect on the radar spectra and the antenna should be placed near the center of rotation. Measured radar spectra also preliminarily confirmed the reliability of the derived scattering model. This article provides a significant theoretical foundation in future investigation and practical application of ocean remote sensing and moving target detection using floating-based platform HFSWR.

Continuous Tracking of Targets for Stereoscopic HFSWR Based on IMM Filtering Combined with ELM

High frequency surface wave radar (HFSWR) plays an important role in marine surveillance on account of its ability to provide wide-range early warning detection. However, vessel target track breakages are common in large-scale marine monitoring, which limits the continuous tracking ability of HFSWR. The following are the possible reasons for track fracture: highly maneuverable vessels, dense channels, target occlusion, strong clutter/interference, long sampling intervals, and low detection probabilities. To solve this problem, we propose a long-term continuous tracking method for multiple targets with stereoscopic HFSWR based on an interacting multiple model extended Kalman filter (IMMEKF) combined with an extreme learning machine (ELM). When the trajectory obtained by IMMEKF breaks, a new section of the track will start on the basis of the observation data. For multiple-target tracking, a number of broken tracks can be obtained by IMMEKF tracking. Then the ELM classifies the segments from the same vessel by extracting different features including average velocity, average curvature, ratio of the arc length to the chord length, and wavelet coefficient. Both the simulation and the field experiment results validate the method presented here, showing that this method can achieve long-term continuous tracking for multiple vessels, with an average correct track segment association rate of over 91.2%, which is better than the tracking performance of conventional algorithms, especially when the vessels are in dense channels and strong clutter/interference area.

Density Based Clustering Data Association Procedure for Real–Time HFSWRs Tracking at OTH Distances

In order to efficiently cover maritime areas at over the horizon (OTH) distances and thus increase marine safety in a nation’s exclusive economic zone (EEZ), a network of maritime sensors built around High Frequency Surface Wave Radars (HFSWR) can be an excellent choice. The critical parameter for success of the deployed sensor network is a real time tracking of all detected vessels. During the tracking process, data association (DA) is the first step and it defines the complexity and thus the speed of the whole tracking process. This paper presents a density based clustering DA procedure where the cluster complexity determines the applied DA procedure within the cluster itself. It is demonstrated that the great majority of clusters (over 98 % of all clusters in the worst case) may be processed in a timely manner with an optimal DA procedure, or more precisely, a Joint Probability Data Association (JPDA). However, a small number of unusually large clusters (less than 2 % of all clusters) requires the application of a sub–optimal DA procedure, more accurately, the Roecker’s suboptimal JPDA algorithm, in order to maintain real time performance of the whole tracking process. Moreover, unlike standard JPDA procedure which tends to be inapplicable for real time tracking in heavily cluttered environment, the density based clustering DA procedure presented here provides real time performances in the very same environment. The whole analysis is done on real HFSWR data obtained from two HFSWR, located in the Gulf of Guinea. The data set used for the experiments includes data obtained during a month and a half of constant HFSWR operation.

The high frequency surface wave radar solution for vessel tracking beyond the horizon

With maximum range of about 200 nautical miles (approx. 370 km) High Frequency Surface Wave Radars (HFSWR) provide unique capability for vessel detection far beyond the horizon without utilization of any moving platforms. Such uniqueness requires design principles unlike those usually used in microwave radar. In this paper the key concepts of HFSWR based on Frequency Modulated Continuous (FMCW) principles are presented. The paper further describes operating principles with focus on signal processing techniques used to extract desired data. The signal processing describes range and Doppler processing but focus is given to the Digital Beamforming (DBF) and Constant False Alarm Rate (CFAR) models. In order to better present the design process, data obtained from the HFSWR sites operating in the Gulf of Guinea are used.

Experimental Observation and Analysis of Ionosphere Echoes in the Mid-Latitude Region of China Using High-Frequency Surface Wave Radar and Ionosonde

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 article 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 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.

Method for the Sea Clutter Characterization in HF Surface Wave Radars From the Fields Diffracted by the Sea Surface

A new method for the characterization of the sea clutter in high-frequency surface wave radars is presented. The method is applied for the bistatic and the monostatic case. This method is based on the discretization of the sea surface in multiple patches. The fields diffracted by each patch are determined. Subsequently, the voltage that the diffracted fields induce on the receiving antenna is calculated. The sum of the voltages induced by all the patches is the sea clutter to be characterized. The fields diffracted by the sea patches are characterized in the form of field charts on a Huygens surface surrounding each patch. Field charts are modeled by analytical expressions. The current induced on the receiving antenna by the diffracted fields is calculated by means of the Lorentz reciprocity theorem. The feasibility of the method of characterization of the sea clutter is verified by means of the characterization of the fields diffracted by a single patch. The calculation of the induced current is done using the diffracted fields that are reconstructed from the analytical expressions that model them. It is also verified that the transmitting and receiving antenna can be replaced by plane wave sources, in order to simplify the calculations of the radiated fields that take part in the Lorentz reciprocity theorem. As a validation of the proposed method, the Doppler spectrum of a moving sea surface is calculated for the monostatic case.

A Two-Step Method for Ionospheric Clutter Mitigation for HFSWR With Two-Dimensional Dual-Polarized Received Array

For high-frequency surface wave radar (HFSWR), the unwanted radio wave originated from the ionosphere is commonly called ionospheric clutter. Its presence seriously affects the performance of the HFSWR and extremely degrades the radar capability to detect target over long distances. To solve this problem, this paper proposes a two-step method for ionospheric clutter mitigation with two-dimensional dual-polarized received array. The proposed method first performs parameter estimation of the clutter, and then gives a polarimetric-adaptive-based oblique projection filter (PAB-OPF) to suppress the clutter. In the first step, due to the fact that vertically and horizontally polarized antennas are at different array elements for reducing mutual coupling and hardware cost, 2-D DOAs are estimated to give phase compensation for polarization phase delay estimation. In the second step, the PAB-OPF is proposed to eliminate phase inconsistency by matching different polarization phase delays for different vertically polarized antennas, and then to suppress the clutter efficiently in space-polarization domain. Error analysis and computational complexity of the proposed method are derived. Experimental results are shown to illustrate the superiority of the proposed method for ionospheric clutter suppression.

Target Detection for HFSWR Based on an S3D Algorithm

Because of the influence of clutter and interference, intelligent detection is of great importance for high-frequency surface wave radar (HFSWR) in complex environment. In this paper, we propose a cascade HFSWR target detection strategy based on semi-supervised self-distillation ( $\sf S^{3}D$ ) learning algorithm. First, based on the results of constant false alarm rate (CFAR) detection, the $\sf S^{3}D$ algorithm proposed in this paper further classifies the real and other targets. Moreover, the non-maximum suppression (NMS) is combined to remove redundant target boxes, in order to achieve accurate location. For supervised learning, the classification needs to label all the samples, which is extremely difficult and time consuming, especially for HFSWR data under complex environment. While the $\sf S^{3}D$ algorithm can make use of both labeled and unlabeled samples. For labeled data, labels are directly used to restrict both the deep and shallow layers of the network, so that both layers represent the same semantic categories. For unlabeled data, the pseudo-label is retained only if the deepest layer produces a high-confidence prediction. The deep and shallow layers are then updated to predict the pseudo-label when fed a strongly augmented version of the same unlabeled samples. The above multiple consistency regularization methods can improve the generalization performance of the network effectively. Finally, the simulations conducted across public datasets show that compared with other semi-supervised learning methods, $\sf S^{3}D$ can better improve the performance of network generalization. Besides, the $\sf S^{3}D$ -based HFSWR target detection method can significantly improve the vessel detection performance by using only a minority of sample labels.

Signal Processing of Coast-Ship Bistatic High-Frequency Surface-Wave Radar Using One-Bit Quantized Measurement

The feasibility of one-bit quantization in coast-ship bistatic high-frequency surface-wave radar (HFSWR) is mainly discussed in order to enjoy the advantages of simplicity, low cost and low power consumption. Our theoretical derivation shows that the received signal after one-bit quantization can be expressed as a linear combination of infinite components. These components include the original component and the high-order components that can be regarded as the interference terms. Then, the variation of the magnitude of each component with the signal-to-noise ratio (SNR) is given. To reduce the negative impact of these high-order components on the radar system, the detailed signal forms are analyzed. Furthermore, some comparative simulations of one-bit quantization and traditional high-precision quantization are provided to verify the correctness of our theoretical analysis. Both theories and simulation results indicate that the high-order components can be ignored in coast-ship bistatic HFSWR and that one-bit quantization is effective. Finally, real data analysis also validates the efficiency of one-bit quantization in practice.

A Higher-Order Singular Value Decomposition-Based Radio Frequency Interference Mitigation Method on High-Frequency Surface Wave Radar

Recently, high-frequency surface wave radar (HFSWR) has been widely applied in ocean surface dynamic parameter measurement. However, the radar echoes backscattered from ocean surface tend to be contaminated by the external radio frequency interference (RFI), and the mitigation of RFI becomes an intractable problem, especially for wide beam HFSWR. The HFSWR measured data are multichannel. The higher-order singular value decomposition (HOSVD) is an effective method to improve the accuracy of subspace estimation by exploiting this multidimensional structure. In this article, we develop an RFI mitigation method based on the HOSVD algorithm and orthogonal subspace projection. Simulations indicate that, compared with the previous orthogonal subspace projection RFI cancellation schemes, the proposed method has significant advantages in keeping the desired signals while suppressing the interference. The proposed method is applied to the experimental data of the HFSWR with severe RFI. The ocean surface currents inverted from the RFI-mitigated data agree reasonably with the tidal features in the radar detection area. After RFI mitigation, the performance of the HFSWR system is significantly improved on the effective current detection range and precision.

Wind Direction Estimation Using Small-Aperture HF Radar Based on a Circular Array

Compact high-frequency (HF) antenna arrays are convenient to deploy. However, using a small-aperture HF surface wave radar for wind direction measurement is still a challenging problem, since an unsatisfactory array pattern degrades the performance of Bragg ratio estimation. To address this issue, a digital beamforming method based on a superdirective synthesis technique for an HF receiving array that consists of seven elements positioned on a 5-m diameter circle is proposed. This superdirective beamforming method contains a sidelobe constraint. Subsequently, a hybrid superdirective beamforming and direction-finding method is adopted to estimate the wind direction using a multifrequency HF radar based on a circular array (MHF-C). The superdirective beamforming approach, as well as the wind direction estimation method, is presented in detail. The wind direction estimation method has been applied to the raw data sets that were collected with two MHF-C radars installed along the coast of the East China Sea in April 2015 and comparisons between radar-derived and in situ wind directions have been made. Ship-mounted anemometers were used to obtain in situ measurements at six sampling locations within the overlapping coverage of both radars. Another comparison between the radar-derived and anemometer-derived wind directions, which were obtained from June 15, 2015 to August 12, 2015, has also been made. The results indicate that the proposed method is effective for wind direction estimation with root-mean-square differences (RMSDs) between 24.1° and 33.1°, when wind speeds were higher than 5 m/s. The analysis encourages us to recommend a minimum wind speed of 5 m/s for reasonably assessing wind direction measurement performance.

Fractional Fourier Transform-Based Radio Frequency Interference Suppression for High-Frequency Surface Wave Radar

High-frequency surface wave radar (HF SWR) plays an important role in marine stereoscopic monitoring system. Nevertheless, the congestion of external radio frequency interference (RFI) in HF band degrades its performance seriously. In this article, two novel fractional Fourier transform (FRFT)-based RFI suppression approaches are proposed. One is based on the orthogonal projection of sequences from fractional Fourier domain, and the other is based on singular value decomposition (SVD) of Hankel matrix of sequences from fractional inverse-Fourier domain. Simulation and experimental data collected by HF SWR from Wuhan University were used to test the effectiveness as well as the application condition of the proposed RFI suppression algorithms. The FRFT-based orthogonal projection algorithm is practicable for suppressing stationary RFI with unvaried carrier frequency, while the FRFT-based SVD algorithm is applicable equally for mitigating nonstationary RFI with time-varying carrier frequency or occasional duration time. The processing results may provide useful guidelines for interference suppression of HF SWR, and inspiring the further application of the FRFT-based methods for signal processing.

Stationary Time Statistical Property of Ionospheric Clutter in High-Frequency Surface-Wave Radar

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.

Wave Height Field Extraction From First-Order Doppler Spectra of a Dual-Frequency Wide-Beam High-Frequency Surface Wave Radar

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.

A Vessel Azimuth and Course Joint Re-Estimation Method for Compact HFSWR

Small-aperture compact high-frequency surface wave radar (HFSWR) suffers from low azimuth accuracy for target detection due to its wide beamwidth. Multitarget tracking (MTT) algorithms, when applied to the raw target detection data of HFSWR, fail to effectively filter the target azimuths, and thus, resulting in inaccurate target tracks and courses. In this article, a vessel azimuth and course joint re-estimation method by exploring Doppler velocity and the information accumulated from consecutive observations is presented. It begins with applying an MTT algorithm to a measured target states data sequence acquired by HFSWR to establish initial target tracks, from which the measured range, azimuth, and radial velocity data sequences are obtained. Then, the azimuth trend is extracted from the obtained azimuth data sequence as roughly corrected azimuth estimates, with which the target locations are roughly corrected. Subsequently, target speeds and initial courses are estimated based on the roughly corrected location data sequence, followed by a data selection procedure based on proposed control parameter rules to select the qualified data for calculating the projected angles in terms of speed and direction, separately. Eventually, the target azimuth data sequence is further refined using a linear azimuth error model, whose parameters are obtained by minimizing the difference between the projected angles using a constrained optimization method. Experimental results from field data demonstrate that the proposed method can estimate the target azimuths with significantly improved accuracy. The deviations of the corrected target locations are considerably reduced, and the accuracy of course estimation is enhanced.

Wave-Height Mapping From Second-Order Harmonic Peaks of Wide-Beam HF Radar Backscatter Spectra

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.

Doppler compensation method for the complementary phase‐coded signal

The Doppler sensitivity issue is an urgent problem to be solved for the phase-coded radar although it can give the promise of improved range resolution and resistance against various kinds of distortion. Due to the ideal autocorrelation and cross-correlation properties, the complementary sequence is utilised in high-frequency surface wave radar and MIMO radar. However, the Doppler frequency shift affects the autocorrelation property of the complementary sequence. This study aims to solve this problem. Based on the signal model and mathematical derivation, a new algorithm is proposed and the simulation results indicate the effectiveness of this method. This study also puts forward the signal processing diagram and the method to obtain the new code.

DOA estimation with extended sparse and parametric approach in multi‐carrier MIMO HFSWR

To obtain a higher angle resolution of multiple-in multiple-out high-frequency surface wave radar (MIMO HFSWR) for direction of arrival (DOA) estimation with a limited number of antenna sensors, multiple working frequencies are proposed to enlarge the aperture of the virtual array of the MIMO HFSWR. The scenario that all targets have the identical reflection at all working frequencies is studied, which permits the abstraction of a virtual received data vector by using all frequencies. This virtual data vector can be taken as the measurement of a virtual non-uniform linear array (VNLA) with a single reference working frequency. To extend the sparse and parametric approach (SPA) to the VNLA for DOA estimation, the manifold separation technique is utilised to decompose the array steering vector of the VNLA into two different parts, one is a characteristic matrix that is related to the array itself. The other is a Vandermonde vector that contains the DOAs of the targets. Then the authors use the Vandermonde structure to develop a SPA-liked method for the DOA estimation. Simulation results are provided to confirm the validity of the proposed method.

Application of joint domain localised matrix CFAR detector for HFSWR

Target detection is one of the most important parts of high-frequency surface wave radar (HFSWR) signal processing, to find targets in noise or clutter and obtain targets’ information. However, some factors, such as the influence of clutter and the increase of detection range, will degrade the signal-to-clutter ratio (SCR). In the low SCR scenario, the classical detector of HFSWR, which uses the amplitude of receipt signal only, could hardly detect targets. To solve this problem, this study proposes a novel detector called joint domain localised matrix constant false-alarm rate (CFAR) detector based on receipt signal's multi-dimensional information. This detector employs joint domain localised algorithm to get signal information in angle and Doppler domain, and use information geometry method to map them to Hermitian positive-definite (HPD) matrix space which can be depicted as Riemannian manifold. Then, based on HPD matrix, in the range domain the matrix CFAR detector is built to detect targets. The experiments’ results verify that the detector can improve radar detection performance effectively.