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This article discusses a study on the estimation of regurgitation in patients with percutaneous left ventricular assist devices (PLVAD) during full support. The study proposes an estimation system based on a regurgitation model and uses an unscented Kalman filter (UKF) as an estimation approach. The effectiveness of the algorithm is assessed using a mock circulatory loop experimental platform. The research findings demonstrate that the proposed system can accurately estimate regurgitation during PLVAD full support, providing valuable information for clinical practitioners to manage potential complications. [Extracted from the article]

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]

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]

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]

Wind spreading functions (WSF) are crucial for high-frequency radar (HFR) wind-direction inversion. The popular half-angle cosine WSF always fails to describe observed HFR Doppler spectra and tends to provide almost fixed relative angle estimations. In this letter, analysis of the data from a broad-beam HFR radar, deployed on the Taiwan Strait’s west coast, shows that a modified WSF (based on the cosine WSF) has a better wind-direction estimation performance. The modified WSF fits average Bragg ratios of 15-day data well with the aid of data from buoys. The data of the next 13 days are used to test the modified WSF. The wind direction estimated by the modified WSF has an advantage when Bragg ratios have adequate average processing, and directions of arrival are around the upwind or downwind direction. The root mean square error of the modified WSF wind-direction estimate is 32.59° for the entire observation, decreasing to 14.18° when a significant wave height is between 1 and 2 m. [ABSTRACT FROM PUBLISHER]

High-frequency (HF) radars have great potential for maritime surveillance, and the multiple signal classification (MUSIC) algorithm is usually used to estimate the direction of arrival (DOA) of targets for a wide-beam radar. However, the performance of the MUSIC algorithm relies on the precision of the antenna pattern, which could be contaminated by nearby electromagnetic interference. Therefore, the actual antenna pattern must be measured and used. In order to remove the requirement of antenna pattern measurement, a new method for target DOA estimation from wide-beam HF radar data using support vector regression (SVR) is proposed in this letter. A system model that relates target bearing and radar data feature is obtained through the SVR-based machine learning using the automatic identification system data and data associated with the vessels successfully detected by the HF radar. Then, such a model is used to determine the DOAs of targets from new data. The field experimental results at two sites demonstrate that the performance of the SVR method is better than that of the MUSIC algorithm. [ABSTRACT FROM PUBLISHER]

High-frequency surface wave radar equipped with a crossed-loop/monopole antenna has been applied to estimate vessel direction of arrival (DOA). However, unavoidable distortion of the antenna pattern and complicated channel calibration are challenges for achieving high angular accuracy when the multiple signal classification (MUSIC) algorithm that relies on the antenna pattern is employed. Although various methods of pattern measurement and calibration have been proposed, high system complexity and considerable time cost are still troublesome problems, especially for the temporary use of radar. In this letter, we first analyze the characteristics of measured pattern and then rapidly calibrate the crossed-loop antenna using sea echoes and the automatic identification system data. Finally, vessels’ DOAs are estimated using MUSIC algorithm and the calibrated loop-only patterns. The high accuracy of DOA estimation is validated at an angle range of less than $\text{180}^{\circ }$. This method effectively reduces the system complexity and time cost when compared with the conventional method. A simulation and two field experiments are conducted. Both the rapid pattern calibration for 115 min and the comparison of processing results demonstrate the validity of this proposed method. [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]