High Frequency Surface Wave Research Articles

A method for sea clutter elimination in the detector of high frequency surface wave radar

In high frequency surface wave radars, the detection capability is limited by the first-order sea clutter spikes. The energy, location, and Doppler frequency of first-order sea clutter depend on the sea states, which is difficult to model using a fixed expression to eliminate sea clutter. Based on the characteristics of first-order sea clutter, the paper proposed a two-stage detector to eliminate sea clutter. The approach shows the capability to eliminate uncertain first-order sea clutter and detect targets in the vicinities of sea clutter in the Range – Doppler map.

A Motion Compensation Method for Shipborne HFSWR by Using Dual Reference RF Signals Generated Onshore

The echo of shipborne high-frequency surface wave radar (HFSWR) is modulated by six-degrees-of-freedom (6-DOF) motion, affecting the detection of the target and the remote sensing of ocean surface dynamics parameters. Commonly, motion compensation methods of shipborne HFSWR describe each aspect of the 6-DOF motion as the superposition of sinusoidal motion, which results in the effect of motion compensation affected by the precision of 6-DOF motion parameters. A motion compensation method based on dual reference radio frequency (RF) signals is proposed in this paper, without depending on a sinusoidal motion model to describe the 6-DOF motion. By using the motion compensation parameters, which are relevant to the motion attitude and calculated from the information of dual reference RF signals located onshore, the method realizes the compensation of shipborne HFSWR echo modulated by platform 6-DOF motion. This paper proposes the extraction of reference RF signals from radar echo and analyzes the influence of the location of the reference RF signals’ emission source on the motion compensation method. The result shows that a good motion compensation effect is achieved in eliminating the influence of 6-DOF motion modulation. In addition, a traversal of different reference RF signals’ emission source locations is conducted, and the simulation results show that the method proposed in this paper has universality.

Effect of interfacial damping on high-frequency surface wave resonance on a nanostrip-bonded substrate

Since surface acoustic waves (SAWs) are often generated on substrates to which nanostrips are periodically attached, it is very important to consider the effect of an interface between the deposited strip and the substrate surface, which is an unavoidable issue in manufacturing. In this article, we propose a theoretical model that takes into account interface damping and calculate the dispersion relationships both for frequency and for attenuation of SAW resonance. These results show that the interface damping has an insignificant effect on resonance frequency; but, interestingly, attenuation of the SAW can decrease significantly in the high-frequency region as the interface damping increases. Using picosecond ultrasound spectroscopy, we confirm the validity of our theory; the experimental results show similar trends both for resonant frequency and attenuation in the SAW resonance. Furthermore, the resonant behavior of the SAW is simulated using the finite element method, and the intrinsic cause of interface damping on the vibrating system is discussed. These findings strongly indicate the necessity of considering interfacial damping in the design of SAW devices.

Ship Monitoring With Bistatic Compact HFSWR of Small Aperture

High-frequency surface wave radar (HFSWR) can detect and continuously track ship targets in real time and beyond the horizon. Compared with transmit/receive (T/R) monostatic HFSWR, the T-R bistatic HFSWR has the advantages of flexibility, receiver concealment, and large coverage because of the separation between the radar transmitter and receiver locations. So far, there is little research on marine ship monitoring for bistatic HFSWR. This article examines ship monitoring performance with T-R bistatic compact HFSWR of small aperture based on measured experimental data. The first-order sea-clutter characteristics and detection blind zone for T-R bistatic HFSWR were investigated theoretically, and the formulas for the moving ships were derived and its position accuracy were analyzed from simulation results. The experimental results of ship target detection of bistatic compact HFSWR carried out in 2015 were presented, and the spectrum characteristics of the bistatic HFSWR were analyzed with measured experimental data. A method integrating detection and tracking was applied to the target detection data collected by the bistatic compact radar, and two targets examples tracked were given. Finally, the validity of the method and the tracing results were verified by using synchronous automatic identification system data, and the ship positioning accuracy of the bistatic compact HFSWR was statistically analyzed. The analysis shows that bistatic radars have larger errors than monostatic T/R radars, with a positioning error as large as 10 km.

Identification of ships moving in formation by HFSWR using an ISAR cross-range imaging algorithm

ABSTRACT High-frequency surface wave radar (HFSWR) has been widely used for ship detection to improve human marine activities. However, the azimuthal resolution is a major challenge for ship detection in HFSWR. Synthetic aperture technology can improve azimuthal resolution, which is different from increasing the size of the antenna array directly in practice. A new method to improve HFSWR azimuthal resolution for ships moving in formation is proposed. The proposed method extends inverse synthetic aperture radar (ISAR) cross-range imaging method to HFSWR, allowing ships in formation to be distinguished from each other in the cross-range domain. In the framework of HFSWR cross-range imaging, the motion of the ship formation is regarded as a rotating turntable by motion compensation. Based on the turntable configuration, the relationship between the cross-range domain and Doppler frequency can be built precisely. Then, the cross-range profile is obtained from the echo data by Fourier transform, and the cross-range spacing between ships can be estimated by the cross-range scaling. The simulated results demonstrate the effectiveness of the proposed method. The present work provides a new idea to improve the azimuthal resolution of HFSWR.

Improving Ship Detection in Clutter-Edge and Multi-Target Scenarios for High-Frequency Radar

As one of the main sensors for continuous maritime measurements of sea state parameters, high-frequency surface wave radar (HFSWR) also plays an important role in ship detection and tracking. Compact HFSWR often suffers from missing targets, especially when the target appears near the Doppler region with heavy sea clutter or near another target in a multi-target scenario. To address this problem, an automatic ship detection method based on time–frequency (TF) analysis is presented in this paper. The TF target ridge areas are extracted in the TF image via the eigenvalues of the Hessian matrix, image edge detection, and local maximum search. Then, whether ship signals exist in the TF ridges or not is decided by a decision threshold that is calculated by fitting the probability distribution function (PDF) of sea clutter in the TF domain. The proposed TF method can separate TF ridges of similar Doppler frequency and performs constant false alarm rate (CFAR) detection for TF targets, which facilitates detecting these targets that are masked by sea clutter and other large targets. Experimental results show that the number of detected ships that match with the automatic identification system (AIS) records is four times more than that obtained by the conventional constant false alarm rate (CFAR) detectors and 1.3 times more than that by the state-of-the-art TF method in consideration of approximately the same number of detected targets.

Ionospheric Clutter Suppression with an Auxiliary Crossed-Loop Antenna in a High-Frequency Radar for Sea Surface Remote Sensing

Ionospheric clutter is one of the main problems for high-frequency surface wave radars (HFSWRs), as it severely interferes with sea surface state monitoring and target detection. Although a number of methods exist for ionospheric clutter suppression, most are suitable for radars with a large-sized array and are inefficient for small-aperture radars. In this study, we added an auxiliary crossed-loop antenna to the original compact radar antenna, and used an adaptive filter to suppress the ionospheric clutter. The experimental results of the HFSWRs data indicated that the suppression factor of the ionospheric clutter was up to 20 dB. Therefore, the Bragg peaks that were originally submerged by the ionospheric clutters could be recovered, and the gaps in the current maps can, to a large extent, be filled. For an oceanographic radar, the purpose of suppressing ionospheric clutter is to extract an accurate current speed; the radial current fields that were generated by our method showed an acceptable agreement with those generated by GlobCurrent data. This result supports the notion that the ionospheric suppression technique does not compromise the estimation of radial currents. The proposed method is particularly efficient for a compact HFSWRs, and can also be easily used in other types of antennas.

Direct target localization and vector-velocity measurement method based on bandwidth synthesis in distributed high frequency surface wave radar

The accuracy of target position and velocity measurement is one of the most concerned indexes of Distributed High Frequency Surface Wave Radar (HFSWR). The target localization of HFSWR is commonly achieved by indirect positioning approach. Recently, some direct positioning methods using the raw signals collected on all base-stations have been studied, which have superior positioning performance compared with indirect approaches. But there is almost no joint estimation method for target position and vector-velocity. In this paper, a novel direct target localization and vector-velocity measurement method based on bandwidth synthesis (BS-DTL) in distributed HFSWR system is investigated to improve the accuracy of the target. BS-DTL algorithm that makes full use of the information of all base-stations is considered for the joint estimation of target position and vector-velocity. This paper studies the detection and estimation performance of the BS-DTL algorithm and traditional direct target localization method (DTL). Numerical simulation results show that the proposed algorithm outperforms the traditional DTL method and the position and vector-velocity can be accurately estimated.

Study on the crustal velocity structure of the Dunhua-Mishan fault based on the dense seismic array by ambient noise tomography

The Dunhua-Mishan fault is a component of the Tanlu fault zone, and it is also a major regional fault structure in Liaoning area. The study area is located in Fushun area of the Dunhua-Mishan fault. In order to study the crustal velocity structure in this region, we used 60 sets of three-component short-period seismographs and lay out two temporary profiles in Fushun, Liaoning from Nov. 3 to 25, 2019. Each temporary profiles is about 12km long that is composed of 30 seismometers, which nearly vertically cross the Dunhua-Mishan fault where the survey lines are 6km apart. The installation stations spacing distance from 200 to 400m use the external GPS time service to record frequency range of 0.2 to 150Hz in the instrument. The crustal structure characteristics of the fault zone are studied by ambient noise cross-correlation method. In order to efficiently extract high and low frequency surface wave dispersion signals at the same time, we adopt the Extended Range Phase Shift (ERPS) method. Finally, we use ERPS method to process the collected data and invert the S-wave velocity structure. We initially obtained the S-wave velocity structure of the upper crust below 5 km in the area, which matches well with the local geological data. The S-wave velocity structure has significant lateral inhomogeneity of the Dunhua-Mishan fault in Fushun area. The S-wave velocity is obviously lower on the Dunhua-Mishan fault, while with the existence of ancient mixed granite the velocity on both sides of the fault is obviously higher.

Sea clutter suppression algorithm in spatial domain based on singular value decomposition

In order to detect the targets in the first-order sea clutter spectrum of high frequency surface wave radar (HFSWR), a method based on singular value decomposition (SVD) is proposed to suppress sea clutter in spatial domain. The sea clutter suppression method is based on the strong correlation of sea clutter, thus we take the adjacent range bin as the reference. Then the sea clutter subspace and noise subspace in the spatial domain is estimated by singular value decomposition of its array covariance matrix. Finally, we subtract its projection in the sea clutter subspace from the array signal with the orthogonality of subspace, and achieves the purpose of suppressing sea clutter in the spatial domain. Compared with the existing methods of sea clutter suppression in spatial domain, there is no need to know the azimuth of sea clutter in advance. The subspace is estimated by singular value decomposition of its array covariance matrix, which makes it easier and more accurate to estimate the sea clutter subspace and noise subspace. The result shows that the method improves the signal to clutter plus noise ratio (SCNR), which is benefit to target detection.

IoT OTH Maritime Surveillance Service over Satellite Network in Equatorial Environment: Analysis, Design and Deployment

This paper explores the challenges and constraints when over the horizon (OTH) maritime surveillance service utilizes an Internet of Things (IoT) as its backbone. The service is based on High Frequency Surface Wave Radars (HFSWRs) and relies on a satellite communication network as its communication infrastructure in harsh environments. The complete IoT OTH maritime surveillance network is currently deployed in the Gulf of Guinea, which due to its tropical climate represents an unfavorable environment for sensors and communications. In this paper, we have examined the service performance under various meteorological conditions specific to the Gulf of Guinea. To the best of our knowledge, this is the first analysis of IoT OTH maritime surveillance service in equatorial environment. Our analysis aims to mathematically describe the impact of harsh weather conditions on the performance of the service in order to mitigate it with careful overall system design and provide constant quality of the service. Analyses presented in the paper show that average service latency is about 90 s, but it can rise to about 120 s, which is used as a key information during the sensor data fusion algorithm design. Validity of the analyses is demonstrated through high quality of service with an outage probability of just 0.1% in the driest months up to the 0.7% in the rainiest months. The work presented here can be used as a guideline for deployment of maritime surveillance service solutions in other equatorial regions. Moreover, the gained experience presented in this paper will significantly facilitate future expansions of the existing maritime surveillance network with more HFSWRs. This will be done in such a way that it will not affect the quality of service of the entire system on a large scale.

Vessel Target Echo Characteristics and Motion Compensation for Shipborne HFSWR under Non-Uniform Linear Motion

For shipborne high-frequency surface wave radar (HFSWR), the movement of the ship has a great impact on the radar echo, thus affecting target detection performance. In this paper, the characteristics of the target echo spectrum and the motion compensation methods for shipborne HFSWR are investigated. Firstly, simulation analysis of echo from a moving target under different ship motion conditions was conducted with a focus on the frequency shift and broadening characteristics of the target echo spectrum. The simulation results show that the non-uniform linear motion and yaw of the ship will shift and broaden the target echoes, resulting in signal-to-noise ratio (SNR) reduction. When the ship velocity and yaw angle change periodically, false target echo peaks will appear in the echo spectrum, which will reduce the accuracy of target detection. To tackle this problem, a motion compensation scheme for the target echo is proposed, including the heading compensation for the effect of yaw and the velocity compensation for non-uniform movement. The influence of the velocity and yaw angle measurement accuracy on the compensation results is also analyzed. Finally, the target echo characteristics and motion compensation method of shipborne HFSWR are verified with experimental data.

A SOLUTION TO STABILIZE THE RECEIVER BEAMWIDTH WHEN CHANGING THE OPERATING FREQUENCY OF HIGH-FREQUENCY SURFACE WAVE RADAR

A single-station High-Frequency Surface Wave Radar (HFSRR) consists of transmitting and receiving antennas in an area with a distance between them approximately ten times their wavelength. At the coast, these antennas are usually deployed at fixed optimal distances for an operating frequency in the HF band (3÷30Mhz). Because the signal used is linear frequency modulation (FMCW), the HFSWS always requires an interference-resistant frequency band. So, it is necessary to change the operating frequency in HFSWR to avoid strong interference, frequency bands. This also results in a change in the received waveform, which affects signal processing quality. In this article, a design solution is proposed to maintain a consistent beamwidth when changing the operating frequency in the HFSWS.

Chaotic dynamics of ionospheric clutter from high frequency surface wave radar

The detection performance of high frequency surface wave radar is impacted by the ionospheric clutter. In order to suppress the ionospheric clutter, it is important to research the physical mechanism of ionosphere. In this paper, it is demonstrated, convincingly for the first time, the chaotic dynamics of the ionospheric clutter. The results are obtained using the actual data collected from a series of experiments in Weihai Radar Station, China. The study includes the stationarity and nonlinearity test, phase-space reconstruction, correlation dimension analysis and Lyapunov exponents analysis. And finally, it is found that ionospheric clutter in HFSWR is a chaotic dynamical process with relatively few degrees of freedom, in contrast to the stochastic approach where the ionospheric clutter is viewed as a random process with a large number of degrees of freedom[1]. Also, this new approach will further provide an original way to analyse the ionospheric clutter suppression method.

Simulation analysis of first order sea clutter spectrum for shipborne bistatic HFSWR

Compared with onshore bistatic high frequency surface wave radar (BHFSWR) and shipborne monostatic HFSWR (MHFSWR), shipborne BHFSWR combines the common advantages of both. It is worth noting that the motion state of both mobile stations needs to be considered. In this paper, the spreading characteristics of first-order sea clutter and the doppler shift of the shipborne BHFSWR were analysed theoretically. Then, the simulation results of forward motion and yaw motion are given, and the co-modulation of the echo signal by the motion of the transmitting and the receiving station was investigated. The simulation results show that the amplitude-frequency characteristics of the first-order sea clutter were more complex when the shipborne transmitter and shipborne receiver were at different uniform motion. Finally, combined with the flexibility of shipborne platform, a new scheme was proposed. That is, it can be adjusted the posture information of the shipborne platform, the detection coverage can be better and the spread range of the first-order sea clutter can be reduced.

HKPM: A Hierarchical Key-Area Perception Model for HFSWR Maritime Surveillance

High-frequency surface wave radar (HFSWR) has become the cornerstone of maritime surveillance because of its low-cost maintenance and coverage of wide area. However, when it comes to the extraction of key areas, such as vessel-target detection and vessel-path tracking, the HFSWR signal is strongly interfered by clutters and noise, which makes maritime surveillance a challenging task. This article proposes a hierarchical key-area perception model for maritime surveillance harnessing range-Doppler (RD) image from HFSWR, Laplacian kernel, a linear classifier (LC), and a subnet-based multilayer representation learning framework (SMRLF). First, a weak LC with a Laplacian kernel is utilized to capture the plausible vessel regions (PVRs). Then, a novel SMRLF is proposed to localize the vessel targets from the PVRs. To handle the noise, a maximum correntropy criterion with variable centers (MCC-VC) is incorporated in the subnet-based learning model. A thorough experimental analysis on cross-domain samples from radar dataset to scene classification dataset shows that the proposed HKPM performs competitively. The model shows a superior performance over most of the state-of-the-art vessel-target detection algorithms with a vessel-target detection accuracy of 94%. The extended analysis on image classification problem proves that the proposed model has great adaptivity and scalability.

Fast Ship Detection With Spatial-Frequency Analysis and ANOVA-Based Feature Fusion

High-frequency surface wave radar (HFSWR) can be effectively used to detect ships in the exclusive economic zone. However, the ship signal is concealed and interfered with various clutter and background noise in the Doppler spectrum. In this letter, a range-Doppler (RD) image-based novel ship detection algorithm is proposed by exploiting spatial-frequency information and a unique feature fusion based on the analysis of variance. The algorithm subsumes three successive stages: Stage I—the plausible region of interest is captured, Stage II—the features from different sources are fused into one generalized feature space, and Stage III—an extreme learning machine-based classifier is utilized to localize the ships. Experimental results on challenging HFSWR-RD datasets demonstrate that the proposed algorithm has a competitive performance over other ship detection algorithms.

Joint Ship Detection Based on Time-Frequency Domain and CFAR Methods with HF Radar

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.

Gravity Wave Observation Experiment Based on High Frequency Surface Wave Radar

Gravity Wave Observation Experiment Based on High Frequency Surface Wave Radar

Improved CFAR Detection and Direction Finding on Time–Frequency Plane With High-Frequency Radar

In addition to sea state monitoring, high-frequency surface wave radar (HFSWR) has attracted more and more attention in ship detection and tracking. Constant false alarm rate (CFAR) detectors have been widely used to handle the complex properties of sea clutters. Due to the relatively high detection threshold, the performance of CFAR in detecting weak and nonstationary targets is often not good. To address this problem, time–frequency analysis (TFA) is involved in the ship detection and direction finding (DF) processing. First, the probability distribution model of sea clutter is achieved in the time–frequency (TF) domain. Corresponding to this sea clutter model, the decision thresholds of targets on the TF plane under different false alarm rates <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$P_{\mathrm {fa}}$ </tex-math></inline-formula> are calculated. Next, the array snapshots are formed by the spectral samples along each extracted TF ridge and later used in the DF process to give the direction of arrival (DOA). Experimental results show that, with the automatic identification system (AIS) records as the ground truth, the number of matched targets detected by the proposed TF-CFAR method is 5%–8% greater than that by the cell averaging (CA)-CFAR method. Moreover, the TF multiple-signal classification (MUSIC) also outperforms MUSIC with an improvement of 3.52° in the root-mean-square error (RMSE) of the DOA estimates under a low signal-to-noise ratio (SNR). In conclusion, the involvement of TFA can greatly improve the detection and DF performances of compact HF radar, particularly under the situations of low SNR and target nonstationarity.