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

Zhao, Chen; Chen, Zezong; Li, Jian; Zhang, Longgang; Huang, Weimin; Gill, Eric W.

doi:10.1109/tgrs.2019.2955077

Cited by 11 publications

(3 citation statements)

References 34 publications

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“…Information about ocean wind fields is essential for maritime operations and the safe navigation of ships [36]. To obtain the wind direction and speed values of the monitoring points on the ship surface, the CFD calculation software FLUENT 15.0 is used to numerically simulate the steady-state wind field.…”

Section: Numerical Simulation Physical Modelmentioning

confidence: 99%

A Method for Estimating Ship Surface Wind Parameters by Combining Anemometer and X-Band Marine Radar Data

Zhang,

Lu,

Tian

et al. 2023

Remote Sensing

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The steady airflow field on a ship is affected by structure and motion and challenged by phenomena such as the low measurement accuracy of the wind field caused by the occlusion of the anemometer. In this work, an improvement in the accuracy of wind measurements affected by structure is proposed, and a method for combining anemometer and X-band marine radar (RCRF) data is designed to further obtain wind parameters. The first step is to use the multivariate bias strategy to achieve the optimal layout of multiple anemometers based on computational fluid dynamics (CFD) numerical simulation data. Then, random forest (RF) is employed to train the wind parameter estimation model. Finally, the wind parameters are optimally estimated by combining the anemometer with the X-band radar. Under the ideal simulation, noise, and temporal uncertainty combined with anemometer noise conditions, the RCRF algorithm performance is evaluated. Compared with the bias correction combination four-anemometer weighted fusion algorithm (FAF-BC) and the BP neural network algorithm for radar wind measurement combination (RCBP), the mean errors in wind direction and speed are reduced by 1.99° and 6.99% at most. The maximum errors are reduced by 14.46° and 15.81% at most, respectively.

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Section: Numerical Simulation Physical Modelmentioning

confidence: 99%

A Method for Estimating Ship Surface Wind Parameters by Combining Anemometer and X-Band Marine Radar Data

Zhang,

Lu,

Tian

et al. 2023

Remote Sensing

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“…ea surface wind is an important factor in ocean dynamics, and significant to marine exploration, navigation safety and on-and off-ships activities [1]. The sea surface wind field based on marine radar inversion is one of the important environmental factors for continuous and real-time take-off and landing safety of carrier-borne aircraft under the condition of sea dynamic vehicle.…”

Section: Introductionmentioning

confidence: 99%

An Energy Spectrum Algorithm for Wind Direction Retrieval From X-Band Marine Radar Image Sequences

Wang

Qiu

et al. 2021

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

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In this study, an energy spectrum (ES) algorithm is proposed to retrieve wind direction from Xband marine radar image sequences. This algorithm is based on utilizing the occlusion area zero-pixel percentage (OZPP) to distinguish rain-free and rain-contaminated radar data. And then the rain-contaminated images are detected and discarded. The effect of radar radial attenuation in radar image sequences is modified by the piecewise fitting technique. Wind direction is determined from rain-free and radial correction data, based on the energy spectrum of small-scale wind streaks. The energy spectrum of small-scale wind streaks is obtained by establishing an energy spectrum scale separation filter. Based on the wind streak characteristics, a two-dimensional fast Fourier transform (FFT) is used to obtain the energy spectrum of radar images. The wind streak characteristics are derived from the distribution of the azimuth normalization radar cross-section (NRCS). The proposed algorithm is tested using data collected from X-band radar images and in-situ anemometer data from the coast of the East China Sea. Compared with the anemometer data, after using the proposed algorithm, the root-mean-square difference for wind direction is 12.13°, which is an acceptable result for engineering application.

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“…On the one hand, shore-based HF radars are important components of coastal operational monitoring systems [2][3][4]. Many countries have utilized shore-based HF radars to obtain ocean current, wind and wave fields [5,6]. The maximum detection range of shore-based HF radars can reach 250 km, with the time resolution ranging from 10 min to 1 h and the spatial resolution varying from 300 m to 5 km.…”

Section: Introductionmentioning

confidence: 99%

Sea Echoes for Airborne HF/VHF Radar: Mathematical Model and Simulation

et al. 2020

Self Cite

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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.

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

Cited by 11 publications

References 34 publications

A Method for Estimating Ship Surface Wind Parameters by Combining Anemometer and X-Band Marine Radar Data

A Method for Estimating Ship Surface Wind Parameters by Combining Anemometer and X-Band Marine Radar Data

An Energy Spectrum Algorithm for Wind Direction Retrieval From X-Band Marine Radar Image Sequences

Sea Echoes for Airborne HF/VHF Radar: Mathematical Model and Simulation

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