Download or read book Development and Evaluation of New Algorithms for the Retrieval of Wind and Internal Wave Parameters from Shipborne Marine Radar Data written by Björn Lund and published by . This book was released on 2012 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: The goal of this work is to develop and evaluate techniques for the retrieval of wind and internal wave (IW) information from marine X-band radar data. While ocean wind measurements are crucial for the transfer of energy and momentum across the air-sea interface, IWs play an important role in tidal energy transport. Marine radars work by transmitting microwave energy from a rotating antenna that also measures the backscatter. The radar backscatter from the sea surface is controlled by the wind-generated small ripple waves through the Bragg-scattering mechanism. Surface winds are thus the dominant factor for generating the radar backscatter. The varying surface current fields associated with IWs interact with the ripples, generating rough convergent and smooth divergent zones. Radars are capable of imaging such IW-induced surface signatures as bands of enhanced and weakened backscatter. The advantage of radar-based wind information is that it is obtained from a large area around the instrument. Marine radar wind data are therefore much less likely to be affected by platform-induced air flow distortions than in-situ measurements. Previous investigators have already demonstrated marine radar's suitability as a wind sensor [31, 30], however, these works have been limited to fixed-platform data. Here, the focus lies on shipborne marine radar data. Such data present the challenge that the existing wind streak-based approach for retrieving wind directions cannot be directly applied. This is because the wind streak signal may become obscured by the horizontal ship motion, since wind streaks become visible only after averaging over a sequence of radar images. In addition, moving platforms face a greater variability of conditions, which may further complicate a radar-based wind retrieval. Grazing incidence HH-polarized (horizontal transmit and receive) X-band radar data exhibit a single intensity peak in upwind direction. To retrieve the wind direction, this work proposes a least-squares fit technique that identifies the upwind peak in the range-averaged backscatter dependency on the antenna look direction. This technique requires no motion correction and is therefore well-suited for shipborne data. In addition, it functions well even if sections of the radar field of view are masked. An empirical model function is derived to retrieve the wind speed from the mean radar backscatter intensity. Data from the U.S. Office of Naval Research (ONR) Impact of Typhoons on the Ocean in the Pacific (ITOP) experiment are used for a comparison between radar-based wind estimates and anemometer measurements. The two data sets show good agreement. In addition, this work proposes a technique that uses geolocated marine radar data to extract wind streak information through a localized Radon transform. To compare streak- and upwind peak-based wind direction retrieval techniques, fixed and moving platform marine radar data from the ONR-sponsored High Resolution Air-Sea Interaction (Hi-Res) experiment are used. Wind directions obtained using the upwind peak method show a better agreement with the reference data than those obtained from the wind streaks. The difference between fixed and moving platform for the wind streak approach indicates that the image geolocation affects the wind retrieval negatively. Standard deviations as low as 6.0° and 0.42 m/s for the comparison between radar-based and reference wind data show that marine radars can yield highly reliable wind estimates. Regarding IWs, a new fully automated tool to retrieve IW signatures from marine radar image sequences is developed and applied to data collected during ONR's Non-Linear Internal Wave Initiative / Shallow Water '06 experiment (NLIWI/SW06). Marine radars have the advantage over satellite systems that their high temporal resolution enables the study of the IW evolution. The proposed technique employs our knowledge about the wind dependency of the radar backscatter to correct for the image ramp, i.e. the return signal's dependency on range and antenna look direction. The ramp-corrected radar images are then geolocated and averaged, which greatly enhances the IW signal. By determining the IW group velocity and correcting for it before the radar images are averaged, the IW signal is further enhanced. Such pre-processing enables a reliable retrieval of IW surface signatures by clustering local peaks and troughs, and tracking those clusters through time. This work also includes a detailed analysis of data collected during the tracking of a particularly energetic IW. The radar-derived time series of IW speed, direction, and soliton maps yield unique information about the IW's spatio-temporal evolution, including evidence of wave-wave interactions. In addition, it is demonstrated that marine radar data can be used to retrieve information about the interior ocean dynamics associated with the IW. The IW-induced backscatter modulation is correlated with the measured surface current gradients and IW amplitudes. Alternatively, results are shown where IW amplitudes were derived from the distances between positive and negative radar backscatter peaks. This approach was first introduced by Xue et al. [132] and is based on an extended Korteweg-de-Vries (eKdV) equation. This approach has the advantage that it is much less dependent on the prevailing wind conditions. To summarize, the marine radar backscatter dependency on wind is analyzed, and new wind retrieval techniques from shipborne radar data are proposed. The gained knowledge on the backscatter's wind dependency is then applied to marine radar data containing IW surface signatures. This work proposes a new methodology for retrieving these signatures and uses the resulting IW soliton maps to derive information about the IW-associated interior ocean dynamics.

Download or read book Advanced Technology Related to Radar Signal Imaging and Radar Cross Section Measurement written by Hirokazu Kobayashi and published by MDPI. This book was released on 2020-06-16 with total page 570 pages. Available in PDF, EPUB and Kindle. Book excerpt: Radar-related technology is mainly processed within the time and frequency domains but, at the same time, is a multi-dimensional integrated system including a spatial domain for transmitting and receiving electromagnetic waves. As a result of the enormous technological advancements of the pioneers actively discussed in this book, research and development in multi-dimensional undeveloped areas is expected to continue. This book contains state-of-the-art work that should guide your research.

Download or read book Ocean Wind and Wave Parameter Estimation from Ship borne X band Marine Radar Data written by Xinlong Liu and published by . This book was released on 2018 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Ocean wind and wave parameters are important for the study of oceanography, on- and off-shore activities, and the safety of ship navigation. Conventionally, such parameters have been measured by in-situ sensors such as anemometers and buoys. During the last three decades, sea surface observation using X-band marine radar has drawn wide attention since marine radars can image both temporal and spatial variations of the sea surface. In this thesis, novel algorithms for wind and wave parameter retrieval from X-band marine radar data are developed and tested using radar, anemometer, and buoy data collected in a sea trial off the east coast of Canada in the North Atlantic Ocean. Rain affects radar backscatter and leads to less reliable wind parameters measurements. In this thesis, algorithms are developed to enable reliable wind parameters measurements under rain conditions. Firstly, wind directions are extracted from raincontaminated radar data using either a 1D or 2D ensemble empirical mode decomposition (EEMD) technique and are seen to compare favourably with an anemometer reference. Secondly, an algorithm based on EEMD and amplitude modulation (AM) analysis to retrieve wind direction and speed from both rain-free and rain-contaminated X-band marine radar images is developed and is shown to be an improvement over an earlier 1D spectral analysis-based method. For wave parameter measurements, an empirical modulation transfer function (MTF) is required for traditional spectral analysis-based techniques. Moreover, the widely used signal-to-noise ratio (SNR)-based method for significant wave height (HS) estimation may not always work well for a ship-borne X-band radar, and it requires external sensors for calibration. In this thesis, two methods are first presented for HS estimation from X-band marine radar data. One is an EEMD-based method, which enables satisfactory HS measurements obtained from a ship-borne radar. The other is a modified shadowingbased method, which enables HS measurements without the inclusion of external sensors. Furthermore, neither method requires the MTF. Finally, an algorithm based on the Radon transform is proposed to estimate wave direction and periods from X-band marine radar images with satisfactory results.

Download or read book Algorithms for Wind Parameter Retrieval from Rain contaminated X band Marine Radar Images written by Yali Wang and published by . This book was released on 2016 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Foundations for Innovative Application of Airborne Radars written by Alexey Nekrasov and published by Springer Science & Business Media. This book was released on 2013-10-09 with total page 106 pages. Available in PDF, EPUB and Kindle. Book excerpt: The ‘wind vector’ – wind speed and direction – is a main meteorological quantity and relevant for air-sea exchange processes. This book explores the use of several airborne microwave instruments, some of which are part of standard aircraft equipment, in determining the local wind vector over water. This is worthwhile as local wind information is usually only available at measurements sites like weather stations and airports, and global wind information from satellites has very coarse resolution and poor temporal coverage – at most a few times daily. In his book, Nekrasov uses known results in a novel way and gives explicit and application-oriented descriptions how to additionally retrieve local wind information from standard airborne microwave instruments. The results presented here are highly valuable for flight operation above the sea (e.g., search-and-rescue) but also for complementing other measurements of atmospheric or oceanic parameters during research flights.

Download or read book Foundations for Innovative Application of Airborne Radars written by Alexey Nekrasov and published by Springer Nature. This book was released on 2021-04-02 with total page 124 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book discusses methods for measuring the water surface backscattering signature and estimating the near-surface wind vector over water using airborne radars, in addition to their standard application. Airborne FMCW demonstrator system, Doppler navigation system, airborne weather radar, airborne radar altimeter, and airborne precipitation radar are analyzed in order to be used for that purpose. The radars functionality is enhanced for their operation in a scatterometer mode. A circle flight and/or a rectilinear flight of an aircraft over the water surface is considered depending on the radar design features to perform measurements of the azimuth normalized radar cross section curve of the water surface and/or the near-surface wind speed and direction. Flight recommendations to perform measurements along with algorithms for measuring the water surface backscattering signature and for retrieval of the wind speed and direction over water are presented.

Download or read book Scientific and Technical Aerospace Reports written by and published by . This book was released on 1992 with total page 1572 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Sea Surface Wind and Wave Parameter Estimation from X band Marine Radar Images with Rain Detection and Mitigation written by Xinwei Chen and published by . This book was released on 2021 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: In this research, the application of X-band marine radar backscatter images for sea surface wind and wave parameter estimation with rain detection and mitigation is investigated. In the presence of rain, the rain echoes in the radar image blur the wave signatures and negatively affect estimation accuracy. Hence, in order to improve estimation accuracy, it is meaningful to detect the presence of those rain echoes and mitigate their influence on estimation results. Since rain alters radar backscatter intensity distribution, features are extracted from the normalized histogram of each radar image. Then, a support vector machine (SVM)-based rain detection model is proposed to classify radar images obtained between rainless and rainy conditions. The classification accuracy shows significant improvement compared to the existing threshold-based method. By further observing images obtained under rainy conditions, it is found that many of them are only partially contaminated by rain echoes. Therefore, in order to segment between rain-contaminated regions and those that are less or unaffected by rain, two types of methods are developed based on unsupervised learning techniques and convolutional neural network (CNN), respectively. Specifically, for the unsupervised learning-based method, texture features are first extracted from each pixel and then trained using a self organizing map (SOM)-based clustering model, which is able to conduct pixel-based identification of rain-contaminated regions. As for the CNN-based method, a SegNet-based semantic segmentation CNN is first designed and then trained using images with manually annotated labels. Both shipborne and shore-based marine radar data are used to train and validate the proposed methods and high classification accuracies of around 90% are obtained. Due to the similarities between how haze affects terrestrial images and how rain affects marine radar images, a type of CNN for image dehazing purposes, i.e., DehazeNet, is applied to rain-contaminated regions in radar images for correcting the in uence of rain, which reduces the estimation error of wind direction significantly. Besides, after extracting histogram and texture features from rain-corrected radar images, a support vector regression (SVR)-based model, which achieves high estimation accuracy, is trained for wind speed estimation. Finally, a convolutional gated recurrent unit (CGRU) network is designed and trained for significant wave height (SWH) estimation. As an end-to-end system, the proposed network is able to generate estimation results directly from radar image sequences by extracting multi-scale spatial and temporal features in radar image sequences automatically. Compared to the classic signal-to-noise (SNR)-based method, the CGRU-based model shows significant improvement in both estimation accuracy (under both rainless and rainy conditions) and computational efficiency.

Download or read book Global Evaluation of Special Sensor Microwave imager Ocean Surface Wind Speed Retrieval Algorithms for the Period September 1991 April 1992 written by William A. Hesser and published by . This book was released on 1995 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Fleet Numerical Meteorology and Oceanography Center (FNMOC) has the charter to provide Special Sensor Microwave/Imager (SSMI) data to the DOD and the NOAA. This has led FNMOC to examine new methods for processing SSM/I data to generate SSM/I products. Of particular interest is the ability to use the SSM/I to remotely sense ocean surface winds. For this study four candidate wind retrieval algorithms initially proposed at the SSM/I Algorithm Symposium held in June, 1993 are examined for potential implementation at FNMOC. Previous calibrarion/validarion studies of the efficacy of wiod speed algorithms focused on regional (mid-latitude or tropical) data sets prompting the requirement to develop a more encompassing, global data set on which to evaluate the proposed algorithms. Comparisons of SSM/I wind retrieval methods reveal that the current FNMOC operational algorithm overestimates wind speeds when atruospheric water vapor content exceeds 5O kg/sq-m2. Adjustments made to this algorithm effectively mitigate the high wind speed bias, but at the cost of eliminating a significant amount of data. Neural network algorithms display high wind speed bias for winds above 11 m/s and low wind speed bias for winds below 4 m/s. The performance of neural network algorithms is largely independent of atmospheric moisture content. A new, global training data set is necessary to enable neural network algorithms to perform properly over the full range of global wind speeds. The use of brightness temperature based rain flags are recommended for use in all wind speed retrieval methods.

Download or read book Evaluation and Improvement of Methods for Estimating Sea Surface Wave Parameters from X band Marine Radar Data written by Zhiding Yang and published by . This book was released on 2022 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Algorithms for Sea Surface Wind Parameter Extraction from X band Shipborne Nautical Radar Images written by Ying Liu and published by . This book was released on 2015 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Global Evaluation of Special Sensor Microwave imager Ocean Surface Wind Speed Retrieval Algorithms for the Period September 1991 April 1992 written by William A. Hesser and published by . This book was released on 1995 with total page 101 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Fleet Numerical Meteorology and Oceanography Center (FNMOC) has the charter to provide Special Sensor Microwave/Imager (SSMI) data to the DOD and the NOAA. This has led FNMOC to examine new methods for processing SSM/I data to generate SSM/I products. Of particular interest is the ability to use the SSM/I to remotely sense ocean surface winds. For this study four candidate wind retrieval algorithms initially proposed at the SSM/I Algorithm Symposium held in June, 1993 are examined for potential implementation at FNMOC. Previous calibrarion/validarion studies of the efficacy of wiod speed algorithms focused on regional (mid-latitude or tropical) data sets prompting the requirement to develop a more encompassing, global data set on which to evaluate the proposed algorithms. Comparisons of SSM/I wind retrieval methods reveal that the current FNMOC operational algorithm overestimates wind speeds when atruospheric water vapor content exceeds 5O kg/sq-m2. Adjustments made to this algorithm effectively mitigate the high wind speed bias, but at the cost of eliminating a significant amount of data. Neural network algorithms display high wind speed bias for winds above 11 m/s and low wind speed bias for winds below 4 m/s. The performance of neural network algorithms is largely independent of atmospheric moisture content. A new, global training data set is necessary to enable neural network algorithms to perform properly over the full range of global wind speeds. The use of brightness temperature based rain flags are recommended for use in all wind speed retrieval methods.

Download or read book Implementation and Evaluation of the New Wind Algorithm in Nasa s 50 MHz Doppler Radar Wind Profiler written by National Aeronautics and Space Administration (NASA) and published by Createspace Independent Publishing Platform. This book was released on 2018-07-18 with total page 118 pages. Available in PDF, EPUB and Kindle. Book excerpt: The purpose of this report is to document the Applied Meteorology Unit's implementation and evaluation of the wind algorithm developed by Marshall Space Flight Center (MSFC) on the data analysis processor (DAP) of NASA's 50 MHz doppler radar wind profiler (DRWP). The report also includes a summary of the 50 MHz DRWP characteristics and performance and a proposed concept of operations for the DRWP. Taylor, Gregory E. and Manobianco, John T. and Schumann, Robin S. and Wheeler, Mark M. and Yersavich, Ann M. Unspecified Center ALGORITHMS; DOPPLER RADAR; METEOROLOGICAL RADAR; METEOROLOGY; WIND PROFILES; WIND VELOCITY MEASUREMENT; DATA REDUCTION; ROOT-MEAN-SQUARE ERRORS; WIND (METEOROLOGY); WIND VELOCITY...

Download or read book Enhanced Methods of Ocean Wave Spectra and Sea State Parameter Estimation from X band Marine Radar Data written by Al-Abbass Y. Al-Habashneh and published by . This book was released on 2018 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Due to the ocean's importance in human lives, researchers have been studying the ocean and developing systems to estimate its state since the 19th century. During the last three decades, remote sensing of the ocean surface using X-band marine radars has emerged as a reliable tool to estimate ocean wave spectra and sea state parameters such as mean wave period and direction and significant wave height. The purpose of this thesis is to develop methods that produce accurate and reliable estimates of ocean wave spectra using X-band marine radar data. The approach taken in this thesis is to determine the sources of ocean wave spectra estimation error in existing methods and then to develop new methods that minimize those errors. In this thesis, four sources of error are addressed: the dependency of spectra estimation on the orientation of the analysis windows; the effect of the radar sampling process; the effect of the scan conversion process; and the accuracy of surface current estimation. The azimuthal location of the X-band radar data analysis window affects the estimation of ocean wave spectra. it has been reported in the literature, and supported by our results, that using the up-wave directions for analysis windows produces higher signal to noise ratios and hence more accurate ocean wave spectra estimates. In order to minimize error due to dependency on the orientation of the analysis windows, a new method referred to as the Adaptive Recursive Positioning Method (ARPM) is proposed. The ARPM is a recursive approach that dynamically determines the optimal number of analysis windows and their corresponding orientation toward the up-wave directions. Second, in this thesis, it has been demonstrated that the sampling process of the ocean surface by X-band marine radar during data collection significantly affects the estimation of ocean save spectra from X-band marine radar data. Therefore, a method referred to as the Inverse Sampling Averaging Filter (ISAF) is proposed to mitigate the effect of the radar sampling process of the ocean surface on the ocean wave spectra estimation using X-band marine radars. ISAF was designed based on a novel understanding of the radar sampling process to involve an averaging process or low pass filtering of the ocean wave spectra. Third, in this thesis, a method referred to as the Polar Fourier Transform (PFT) is proposed to eliminate the distortion presented by the scan conversion process to the estimated wave spectra. Unlike the existing methods which use the Cartesian Fourier Transform (CFT) to acquire the ocean wave spectra, the PFT method is designed to apply a Fourier-type transformation on the radar data in its native format, which is sampled in the polar coordinates, without the need for the intermediate stage of scan conversion used to map the data into Cartesian coordinates. The performance of the proposed methods, the ARPM,ISAF and PFT, are individually validated by comparing their ocean wave spectra estimates to those acquired using the existing methods with respect to ground truth wave spectra acquired using a wave rider buoy. Furthermore, the proposed methods were also combined together to seek further enhancement. The wave spectra estimation results from different combinations of the proposed methods were validated in comparison to the ground truth data. Finally, a new method to estimate surface current using X-band marine radar is proposed. This method is referred to as the Hybrid Least Squares (HLS) method. The HLS combines two existing approaches: the Iterative Least Squares (ILS) method and the Normalized Scalar Product (NSP). The HLS is designed to inherit the short computational time of ILS and the high reliability of NSP. To validate its accuracy and reliability, the proposed HLS method was applied on a number of simulated X-band marine radar image sets and the results were compared to the estimates acquired using the ILS and the NSP.

Download or read book Application and Evaluation of Wind Retrieval Algorithms for a Single Doppler Radar written by Kurt Duane Hondl and published by . This book was released on 1990 with total page 346 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Earth Resources written by and published by . This book was released on 1986 with total page 760 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Validation of Special Sensor Microwave imager Ocean Surface Wind Retrievals in Equatorial Regions written by Elton G. Sayward and published by . This book was released on 1994 with total page 69 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Fleet Numerical Meteorology and Oceanography Center (FNMOC) has the charter to provide Special Sensor Microwave/Imager(SSM/I) data to DOD and NOAA users. This tasking has led to new methods for processing SSM/I data being developed to improve NAVY SSM/I products, in particular the ability to remotely sense ocean surface winds. Currently, alternative SSM/I ocean surface wind speed algorithms include 'physical' or 'statistical' methods. Typically "physical" retrievals require additional data. e.g., cloud liquid water, along with SSM/I brightness temperatures while statistical methods are stand alone algorithms based on brightness temperature only. In this study four candidate wind retrieval methods proposed at the SSM/I Algorithm Symposium (June 1993) for implementation at FNMOC are examined. Limitations of the SSM/I calibration/validation data set to the mid-latitude region prompted the requirement to develop a tropical data set for evaluation of alternative algorithms. Comparison of SSM/I wind retrieval methods reveal neural networks display a high wind speed bias for winds above 11 m/s and a low wind speed bias for winds below 3 mi. The current FNMOC operational algorithm may overestimates wind speeds when water vapor is greater than 50 kg/m2. Partitioning of SSM/l retrieved wind speeds according to accuracy is by accomplished when using brightness temperature received at 37 GHZ.