The Experts below are selected from a list of 1335 Experts worldwide ranked by ideXlab platform
Paul Racette - One of the best experts on this subject based on the ideXlab platform.
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NASA's L-Band Digital Beamforming Synthetic Aperture Radar
IEEE Transactions on Geoscience and Remote Sensing, 2011Co-Authors: Rafael F. Rincon, Manuel A. Vega, Manuel Buenfil, Alessandro Geist, Lawrence Hilliard, Paul RacetteAbstract:The Digital Beamforming Synthetic Aperture Radar (DBSAR) is a state-of-the-art L-band Radar that employs advanced Radar technology and a customized data acquisition and real-time processor in order to enable multimode measurement techniques in a single Radar Platform. DBSAR serves as a test bed for the development, implementation, and testing of digital beamforming Radar techniques applicable to Earth science and planetary measurements. DBSAR flew its first field campaign on board the National Aeronautics and Space Administration P3 aircraft in October 2008, demonstrating enabling techniques for scatterometry, synthetic aperture, and altimetry.
Zhijun Qiao - One of the best experts on this subject based on the ideXlab platform.
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non stationary Platform inverse synthetic aperture Radar maneuvering target imaging based on phase retrieval
Sensors, 2018Co-Authors: Ting Yang, Zhijun QiaoAbstract:As a powerful signal processing tool for imaging moving targets, placing Radar on a non-stationary Platform (such as an aerostat) is a future direction of Inverse Synthetic Aperture Radar (ISAR) systems. However, more phase errors are introduced into the received signal due to the instability of the Radar Platform, making it difficult for popular algorithms to accurately perform motion compensation, which leads to severe effects in the resultant ISAR images. Moreover, maneuvering targets may have complex motion whose motion parameters are unknown to Radar systems. To overcome the issue of non-stationary Platform ISAR autofocus imaging, a high-resolution imaging method based on the phase retrieval principle is proposed in this paper. Firstly, based on the spatial geometric and echo models of the ISAR maneuvering target, we can deduce that the radial motion of the Radar Platform or the vibration does not affect the modulus of the ISAR echo signal, which provides a theoretical basis for the phase recovery theory for the ISAR imaging. Then, we propose an oversampling smoothness (OSS) phase retrieval algorithm with prior information, namely, the phase of the blurred image obtained by the classical imaging algorithm replaces the initial random phase in the original OSS algorithm. In addition, the size of the support domain of the OSS algorithm is set with respect to the blurred target image. Experimental simulation shows that compared with classical imaging methods, the proposed method can obtain the resultant motion-compensated ISAR image without estimating the Radar Platform and maneuvering target motion parameters, wherein the fictitious target is perfectly focused.
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Aerostat borne ISAR autofocus imaging based on phase retrieval
Radar Sensor Technology XXII, 2018Co-Authors: Zhijun QiaoAbstract:Compared with the ground-based Inverse Synthetic Aperture Radar (ISAR), although there are many advantages in the aerostat borne ISAR, but its Radar Platform is a degree of instability, which will interfere with ISAR imaging. For aerostat borne ISAR autofocus imaging, a high-resolution imaging algorithm based on phase retrieval principle is proposed in this paper. Theoretical analysis shows that the translational motion or vibration of the Radar Platform does not affect the magnitude of ISAR echo. Therefore, phase retrieval algorithm can eliminate the instability of the Radar Platform. Compared with the traditional algorithms, the results show that the proposed method in this paper can obtain better imaging results without estimating the motion parameters of the Radar Platform.
Rafael F. Rincon - One of the best experts on this subject based on the ideXlab platform.
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NASA's L-Band Digital Beamforming Synthetic Aperture Radar
IEEE Transactions on Geoscience and Remote Sensing, 2011Co-Authors: Rafael F. Rincon, Manuel A. Vega, Manuel Buenfil, Alessandro Geist, Lawrence Hilliard, Paul RacetteAbstract:The Digital Beamforming Synthetic Aperture Radar (DBSAR) is a state-of-the-art L-band Radar that employs advanced Radar technology and a customized data acquisition and real-time processor in order to enable multimode measurement techniques in a single Radar Platform. DBSAR serves as a test bed for the development, implementation, and testing of digital beamforming Radar techniques applicable to Earth science and planetary measurements. DBSAR flew its first field campaign on board the National Aeronautics and Space Administration P3 aircraft in October 2008, demonstrating enabling techniques for scatterometry, synthetic aperture, and altimetry.
Fu Qiang - One of the best experts on this subject based on the ideXlab platform.
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Radar Platform Motion Characteristics and Their Effect on Range Profile
Journal of National University of Defense Technology, 2020Co-Authors: Fu QiangAbstract:Analysis of how motion characteristics of Radar Platform influence imaging is the premise of researching on motion compensation,detection,recognition and tracking methods.Aiming at the problem of Radar Platform motion characteristics and its effect on range profile,the study firstly analyzed the motion characteristics of Radar Platform,gave an LFM signal model based on motion Platform,and quantitatively analyzed the influence on range profile which result from the motion characteristics of the Radar Platform.It is concluded that,under the condition of general Radar Platform,the micro-motion of Platform influencing the radial velocity/acceleration can be ignored;the translational-motion of Platform is the main factor influencing the range profile,the micro-motion of Platform have little influence on range profile;radial acceleration influencing the range profile can be ignored.Finally,the simulation results verify the correctness of conclusion.
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An analysis on error sources of guidance Radar detection performance
Proceedings of 2011 IEEE CIE International Conference on Radar, 2011Co-Authors: Liu Zheng, Tang Xing, Fu QiangAbstract:Target detection is the premise of identification/tracking of the guidance Radar. There are many factors affect the detection performance of the guidance Radar. Analysis and research the error sources is the basis of performance evaluation and system optimization design for guidance Radar, and it provides technical support for the target detection performance evaluation and further testing and optimization of the guidance Radar's signal processing algorithms. This paper analyzes and researches the error sources of guidance Radar from the target, clutter characteristics and motion characteristics of Radar Platform, the simulation results show correctness of the analysis.
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doppler parameters estimation technique using the radon transform for high forward squint sar imaging
Signal Processing, 2009Co-Authors: Fu QiangAbstract:For forward-squint synthetic aperture Radar (SAR) imaging,the determination of the Doppler centroid is indispensa- ble.Analyzing the characteristics of the range cell migration,a Doppler centroid estimation technique is proposed,which utilizes the Ra- don transform to extract the skew angle information from the shape of the target response in the range-compressed image and then calcu- lates the Doppler centroid.It can resolve the Doppler ambiguity without the prior knowledge of the Radar Platform velocity and the beam squint angle,and which is especially usable to high forward-squint SAR.Furthermore,when the Radar Platform velocity is known,the beam squint angle and thereby the Doppler frequency rate and the higher-order phase factors can be estimated too.Using the estimated phase factors,we can perform the phase compensation and azimuth compression.Simulation results demonstrate the effectiveness of the method.
Ting Yang - One of the best experts on this subject based on the ideXlab platform.
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non stationary Platform inverse synthetic aperture Radar maneuvering target imaging based on phase retrieval
Sensors, 2018Co-Authors: Ting Yang, Zhijun QiaoAbstract:As a powerful signal processing tool for imaging moving targets, placing Radar on a non-stationary Platform (such as an aerostat) is a future direction of Inverse Synthetic Aperture Radar (ISAR) systems. However, more phase errors are introduced into the received signal due to the instability of the Radar Platform, making it difficult for popular algorithms to accurately perform motion compensation, which leads to severe effects in the resultant ISAR images. Moreover, maneuvering targets may have complex motion whose motion parameters are unknown to Radar systems. To overcome the issue of non-stationary Platform ISAR autofocus imaging, a high-resolution imaging method based on the phase retrieval principle is proposed in this paper. Firstly, based on the spatial geometric and echo models of the ISAR maneuvering target, we can deduce that the radial motion of the Radar Platform or the vibration does not affect the modulus of the ISAR echo signal, which provides a theoretical basis for the phase recovery theory for the ISAR imaging. Then, we propose an oversampling smoothness (OSS) phase retrieval algorithm with prior information, namely, the phase of the blurred image obtained by the classical imaging algorithm replaces the initial random phase in the original OSS algorithm. In addition, the size of the support domain of the OSS algorithm is set with respect to the blurred target image. Experimental simulation shows that compared with classical imaging methods, the proposed method can obtain the resultant motion-compensated ISAR image without estimating the Radar Platform and maneuvering target motion parameters, wherein the fictitious target is perfectly focused.
