With the increasing frequency of international shipping and marine resources development activities, ship motion prediction plays an increasingly important role in ensuring the safety of offshore ...operations. However, in the field of ship motion prediction, the deep feature information of raw high-resolution ship motion data, as well as the predictable components in the initial prediction residuals is usually neglected. In this paper, a deterministic ship roll forecasting model based on multi-objective data fusion and multi-layer error correction is proposed. The proposed model consists of three stages, which are data pre-processing stage, multi-objective data fusion forecasting stage, and multi-layer error correction stage. To verify the stability and validity of the proposed model, an experimental study was conducted using three sets of measured ship roll motion data collected in the South China Sea from 2018 to 2020. Taking the 1-step, 5-step, and 10-step predictions of dataset #1 as an example, the RMSE values of the proposed model are 0.0130°, 0.0612°, and 0.0791°, respectively. Through three analytical experiments and four comparison experiments, it is proved that the proposed model is able to obtain accurate deterministic point forecasts, which can better assist the sailor in decision making.
•Propose a novel deterministic ship roll forecasting model.•Process raw high-resolution data using a data pre-processing method.•Use a multi-objective data fusion method to predict ship roll motion.•Develop a multi-layer error correction framework to correct prediction residuals.
Coherent microwave radar utilizes the direct relationship between the orbital wave velocity and the wave height spectrum to retrieve wave parameters. However, due to the broken wave and its ...evolution, "Group-Line" is introduced in the radar-obtained wavenumber-frequency spectrum, and the dominant wave energy is reduced. Many methods have proposed to remove "Group-Line" in the wavenumber-frequency spectrum, but these methods can only remove low-frequency energy and fail to compensate for the dominant wave energy. To solve this problem, a method for wave parameter inversion using quasi-binary variational mode decomposition (QB-VMD) is proposed. First, QB-VMD decomposes the spatial-temporal radial velocity series, and a series of modes is obtained, including "Group-Line" and dominant wave modes. Second, the "Group-Line" mode is discarded, and the dominant wave mode is compensated appropriately to reconstruct the spatial-temporal radial velocity series. Finally, the wave parameters are retrieved according to the reconstructed spatial-temporal radial velocity series. The proposed method is verified by simulation. In addition, this article uses an eight-day dataset collected by the coherent <inline-formula><tex-math notation="LaTeX">S</tex-math></inline-formula>-band radar deployed at Beishuang island for analysis. The significant wave height and mean wave period are retrieved from the dataset. The wave parameters estimated by the proposed method are compared with the buoy results. The correlation coefficients are 0.97 and 0.80, and the root-mean-square errors are 0.12 m and 0.49 s, respectively. The results show that the proposed method can invert wave parameters using the coherent <inline-formula><tex-math notation="LaTeX">S</tex-math></inline-formula>-band radar with reasonable performance.
Non-contact methods, which are of great significance to the measurement of river discharge, can not only improve the efficiency of measurement but can also ensure the safety of equipment and ...personnel. However, owing to their inherent drawbacks such as the requirement of riverbed topography measurements and the difficulty in determining hydrological parameters such as equivalent roughness height, velocity index, etc., there are still challenges for measuring river discharge with high levels of efficiency and accuracy using non-contact methods. To overcome the aforementioned challenges, a new river discharge inversion method is proposed in this paper. In this method, vertical velocities are divided into inner and outer region velocities which can be described by the logarithmic law and the parabolic law, respectively. Applying the river surface velocities collected by microwave Doppler radar and the vertical velocity distributions, the water depths are estimated according to the continuity of the vertical velocities and the shear stresses, and then, the river discharges are obtained by the velocity–area method. The proposed method not only has a simple formula but also comprehensively considers the influence of different hydrological conditions, making it suitable for different river widths and water depths. In this paper, surface velocities collected by microwave Doppler radar on the Yangtze River and the San Joaquin River are used to invert the river discharge, and the results show that for wide–shallow, wide–deep, and narrow–shallow river conditions, the mean percent error (MPE) values of the discharges invertedby the proposed method are 3.91%, 3.82%, and 3.6%, respectively; the root mean square error (RMSE) values are 4.53%, 5.19%, and 4.81%, respectively; and the maximum percent error (MaPE) is less than 15%. The results prove that the proposed method can invert the river discharge with high efficiency and high accuracy under different river widths and water depths without measuring water depth in advance, making it is possible to automatically measure the river discharge in real time.
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.
Currently, shore-based HF radars are widely used for coastal observations, and airborne radars are utilized for monitoring the ocean with a relatively large coverage offshore. In order to take the ...advantage of airborne radars, the theoretical mechanism of airborne HF/VHF radar for ocean surface observation has been studied in this paper. First, we describe the ocean surface wave height with the linear and nonlinear parts in a reasonable mathematical form and adopt the small perturbation method (SPM) to compute the HF/VHF radio scattered field induced by the sea surface. Second, the normalized radar cross section (NRCS) of the ocean surface is derived by tackling the field scattered from the random sea as a stochastic process. Third, the NRCS is simulated using the SPM under different sea states, at various radar operating frequencies and incident angles, and then the influences of these factors on radar sea echoes are investigated. At last, a comparison of NRCS using the SPM and the generalized function method (GFM) is done and analyzed. The mathematical model links the sea echoes and the ocean wave height spectrum, and it also offers a theoretical basis for designing a potential airborne HF/VHF radar for ocean surface remote sensing.
Using a Doppler radar to measure river surface velocity is a safe and effective technique. However, the measurement would be severely affected by undesired targets that enter the illuminated area of ...radar. The issue is worsened when measuring the surface velocities of wide rivers because undesired targets such as boats and ships are more likely to be present. The buoy boats fixed on the river surface and cargo ships sailing on the river would generate ground clutter and moving target interference, respectively. The clutter and interference can mask the signal produced by the Bragg scattering and seriously bias the extraction result of river surface velocity. This paper proposes two effective methods to remove ground clutter and moving target interference, respectively. One is an improved phase-based method that eliminates ground clutter after obtaining its boundaries through the phase in the frequency domain, and another is an improved constant false alarm rate (CFAR) detector that combines smallest-of selection logic and a multi-step deletion scheme to detect and remove interference in the time-Doppler spectrum. The experimental data measuring the surface velocity of the Yangtze River with a coherent S-band radar in July 2022 are used to verify the proposed methods. The results show that the proposed methods can effectively remove ground clutter and moving target interference, respectively. After clutter and interference cancellation, a more reasonable result of river surface velocity distribution can be extracted. Therefore, the methods proposed in this paper can be used to remove clutter and interference when extracting the surface velocity of rivers with numerous undesired targets.
This letter presents a novel signal processing method for HF surface wave radar that offers a solution to suppress significant sea clutter interference. Conventional clutter rejection methods, when ...the target signal and first-order sea clutter are mixed in the Doppler spectrum, tend to eliminate both the target signal and clutter without distinction. To address this problem, the frequency-modulated difference between the target signal and clutter is considered. Target echoes can be characterized as a linear-frequency modulation signal in long coherent time, while first-order sea clutter can be regarded as a superposition of several single-frequency signals. Based on the hybrid use of singular value decomposition (SVD) and the fractional Fourier transform (FRFT), SVD-FRFT filtering is conducted to suppress the components of the first-order sea clutter without impairing the target signals. The effectiveness of this method is illustrated by simulation and experimental results. It is further demonstrated that SVD-FRFT filtering can improve the signal-to-clutter ratio (SCR) to up to 40 dB for different SCRs.
Visible light communication (VLC) and non-orthogonal multiple access (NOMA) have been deemed two promising techniques in the next wireless communication networks. In this paper, secure communications ...in the presence of potential eavesdropper are investigated for a multiple-input single-output VLC system with NOMA. The artificial noise jamming and beamforming technologies are applied to improve secure performance. A robust resource allocation scheme is proposed to minimize the total transmit power taking into account the constraints on the quality of service requirement of the desired users and the maximum tolerable data rate of the eavesdropper, and the practical imperfect channel state information of both the desired users and the eavesdropper. The formulated non-convex optimization problem is tackled based on S-Procedure and semi-definite programming relaxation. Simulation results illustrate that our proposed resource allocation scheme can effectively guarantee communication security and achieve transmit power saving. Moreover, the height and number of LED can significantly affect system performance and the optimum LED height can be obtained for different LED numbers.
Radio frequency interference (RFI) is a common interference source in high-frequency surface wave (HFSW) radar. Its existence degrades the performance of HFSW radar greatly and makes it necessary to ...find an effective method to mitigate the interferences. There are two kinds of RFI in the experimental data. One is transient RFI, which is usually suppressed by temporal processing. The other is nontransient RFI, which is suppressed by adaptive beamforming methods. However, the temporal processing techniques suffer performance loss in nontransient cases, whereas the adaptive beamforming methods need spatially structuring, which is difficult to meet within the coherent integration time (CIT) of a few minutes. The fact that the experimental data are usually interfered by two kinds of RFI over a CIT motivates us to find a unified method for interference mitigation. In this letter, a new method based on complex empirical mode decomposition (CEMD) is proposed. CEMD is a local decomposition algorithm that can decompose the echoes and the RFI including transient and nontransient RFI into different intrinsic mode functions (IMFs). Then, the IMFs that correspond to RFI are processed. Experimental results indicate that the proposed method can effectively mitigate both kinds of RFI, and improve the signal-to-noise ratio without losing echoes.
This letter proposes using the 2-D multiple-signal classification (MUSIC) based on sparse recovery (SR) to improve the target-detection capability of high-frequency surface wave radar (HFSWR). ...Usually, for wide-beam HFSWRs, target detection is first conducted in the range-Doppler spectrum, and bearings are then estimated by superresolution methods such as MUSIC. Unfortunately, the conventional cascaded method can easily result in unfavorable deterioration of multitarget detection when different target signals tend to become mixed in the Doppler spectrum. Moreover, sea clutter is an unwanted signal that frequently masks target signals. To enhance the detection of multiple targets and targets embedded in sea clutter, spatial-temporal joint estimation has been proposed. However, because of the lack of spatial-temporal snapshots caused by the nonstationarity of target signals, the efficiency of the estimator cannot be guaranteed. To overcome this shortcoming, multiple-measurement-vector-based SR, which has been used to solve many under-sampling problems in the past ten years, is adopted. Our approach can effectively detect a target embedded in sea clutter as well as multiple adjacent targets and distinguish them from each other. Results obtained using real data with opportunistic targets validate our approach. Therefore, the proposed 2-D SR-MUSIC approach improves target detection and outperforms conventional cascaded methods.
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