Space-borne synthetic aperture radar received data simulation based on airborne SAR image data

2008 ◽  
Vol 41 (11) ◽  
pp. 1818-1821 ◽  
Author(s):  
Shunsheng Zhang ◽  
Teng Long ◽  
Tao Zeng ◽  
Zegang Ding
Keyword(s):  
Synthetic Aperture Radar ◽  
Image Data ◽  
Synthetic Aperture ◽  
Sar Image ◽  
Data Simulation ◽  
Simulation Based ◽  
Airborne Sar ◽  
Aperture Radar

scholarly journals Refocusing Moving Ship Targets in SAR Images Based on Fast Minimum Entropy Phase Compensation

Sensors ◽  
2019 ◽  
Vol 19 (5) ◽  
pp. 1154 ◽  
Author(s):  
Xiangli Huang ◽  
Kefeng Ji ◽  
Xiangguang Leng ◽  
Ganggang Dong ◽  
Xiangwei Xing
Keyword(s):  
Synthetic Aperture Radar ◽  
Phase Error ◽  
Synthetic Aperture ◽  
Sar Image ◽  
Minimum Entropy ◽  
Sar Images ◽  
Phase Compensation ◽  
Translation Motion ◽  
Airborne Sar ◽  
Aperture Radar

Moving ship targets appear blurred and defocused in synthetic aperture radar (SAR) images due to the translation motion during the coherent processing. Motion compensation is required for refocusing moving ship targets in SAR scenes. A novel refocusing method for moving ship is developed in this paper. The method is exploiting inverse synthetic aperture radar (ISAR) technique to refocus the ship target in SAR image. Generally, most cases of refocusing are for raw echo data, not for SAR image. Taking into account the advantages of processing in SAR image, the processing data are SAR image rather than raw echo data in this paper. The ISAR processing is based on fast minimum entropy phase compensation method, an iterative approach to obtain the phase error. The proposed method has been tested using Spaceborne TerraSAR-X, Gaofeng-3 images and airborne SAR images of maritime targets.

scholarly journals Change Detection in Synthetic Aperture Radar Images Based on a Generalized Gamma Deep Belief Networks

Sensors ◽  
2021 ◽  
Vol 21 (24) ◽  
pp. 8290
Author(s):  
Meng Jia ◽  
Zhiqiang Zhao
Keyword(s):  
Synthetic Aperture Radar ◽  
Change Detection ◽  
Yellow River ◽  
Image Data ◽  
Synthetic Aperture ◽  
Sar Image ◽  
Data Set ◽  
Generalized Gamma ◽  
Difference Images ◽  
Aperture Radar

Change detection from synthetic aperture radar (SAR) images is of great significance for natural environmental protection and human societal activity, which can be regarded as the process of assigning a class label (changed or unchanged) to each of the image pixels. This paper presents a novel classification technique to address the SAR change-detection task that employs a generalized Gamma deep belief network (gΓ-DBN) to learn features from difference images. We aim to develop a robust change detection method that can adapt to different types of scenarios for bitemporal co-registered Yellow River SAR image data set. This data set characterized by different looks, which means that the two images are affected by different levels of speckle. Widely used probability distributions offer limited accuracy for describing the opposite class pixels of difference images, making change detection entail greater difficulties. To address the issue, first, a gΓ-DBN can be constructed to extract the hierarchical features from raw data and fit the distribution of the difference images by means of a generalized Gamma distribution. Next, we propose learning the stacked spatial and temporal information extracted from various difference images by the gΓ-DBN. Consequently, a joint high-level representation can be effectively learned for the final change map. The visual and quantitative analysis results obtained on the Yellow River SAR image data set demonstrate the effectiveness and robustness of the proposed method.

scholarly journals Micro-Motion Estimation of Maritime Targets Using Pixel Tracking in Cosmo-Skymed Synthetic Aperture Radar Data—An Operative Assessment

2019 ◽  
Vol 11 (14) ◽  
pp. 1637 ◽  
Author(s):  
Filippo Biondi ◽  
Pia Addabbo ◽  
Danilo Orlando ◽  
Carmine Clemente
Keyword(s):  
Synthetic Aperture Radar ◽  
Wide Band ◽  
Radar Data ◽  
Satellite System ◽  
Synthetic Aperture ◽  
Sar Image ◽  
Synthetic Aperture Radar Data ◽  
Micro Motion ◽  
Novel Strategy ◽  
Aperture Radar

In this paper, we propose a novel strategy to estimate the micro-motion (m-m) of ships from synthetic aperture radar (SAR) images. To this end, observe that the problem of motion and m-m detection of targets is usually solved using synthetic aperture radar (SAR) along-track interferometry through two radars spatially separated by a baseline along the azimuth direction. The approach proposed in this paper for m-m estimation of ships, occupying thousands of pixels, processes the information generated during the coregistration of several re-synthesized time-domain and not overlapped Doppler sub-apertures. Specifically, the SAR products are generated by splitting the raw data according to a temporally small baseline using one single wide-band staring spotlight (ST) SAR image. The predominant vibrational modes of different ships are then estimated. The performance analysis is conducted on one ST SAR image recorded by COSMO-SkyMed satellite system. Finally, the newly proposed approach paves the way for application to the surveillance of land-based industry activities.

scholarly journals Verification of Imaging Algorithm for Signal Processing Software within Synthetic Aperture Radar (SAR) System

2019 ◽  
Vol 2019 ◽  
pp. 1-12 ◽  
Author(s):  
Le-tian Zeng ◽  
Chun-hui Yang ◽  
Mao-sheng Huang ◽  
Yue-long Zhao
Keyword(s):  
Signal Processing ◽  
Data Processing ◽  
Synthetic Aperture Radar ◽  
Software Testing ◽  
Real Data ◽  
Synthetic Aperture ◽  
Data Simulation ◽  
Motion Error ◽  
Processing Software ◽  
Aperture Radar

In the signal processing software testing for synthetic aperture radar (SAR), the verification for algorithms is professional and has a very high proportion. However, existing methods can only perform a degree of validation for algorithms, exerting an adverse effect on the effectiveness of the software testing. This paper proposes a procedure-based approach for algorithm validation. Firstly, it describes the processing procedures of polar format algorithm (PFA) under the motion-error circumstance, based on which it analyzes the possible questions that may exist in the actual situation. By data simulation, the SAR echoes are generated flexibly and efficiently. Then, algorithm simulation is utilized to focus on the demonstrations for the approximations adopted in the algorithm. Combined with real data processing, the bugs concealed are excavated further, implementing a comprehensive validation for PFA. Simulated experiments and real data processing validate the correctness and effectiveness of the proposed algorithm.

scholarly journals A Synthetic Aperture Radar (SAR)-Based Technique for Microwave Imaging and Material Characterization

Electronics ◽  
2018 ◽  
Vol 7 (12) ◽  
pp. 373 ◽  
Author(s):  
Yuri Álvarez López ◽  
María García Fernández ◽  
Raphael Grau ◽  
Fernando Las-Heras
Keyword(s):  
Synthetic Aperture Radar ◽  
Material Characterization ◽  
A Priori ◽  
Microwave Imaging ◽  
Synthetic Aperture ◽  
Sar Image ◽  
A Priori Information ◽  
Priori Information ◽  
Constitutive Parameters ◽  
Aperture Radar

This contribution presents a simple and fast Synthetic Aperture Radar (SAR)-based technique for microwave imaging and material characterization from microwave measurements acquired in tomographic systems. SAR backpropagation is one of the simplest and fastest techniques for microwave imaging. However, in the case of heterogeneous objects and media, a priori information about the constitutive parameters (conductivity, permittivity) is needed for an accurate imaging. In some cases, a first guess of the constitutive parameters can be extracted from an uncorrected SAR image, and then the estimated parameters can be introduced in a second step to correct the SAR image. The main advantage of this methodology is that there is little or no need for a priori information about the object to be imaged. Besides, calculation time is not significantly increased with respect to conventional SAR, thus allowing real-time imaging capabilities. The methodology has been validated by means of measurements acquired in a cylindrical setup.

A Visual Interpretation of an ERS- I SAR Image of the Thames Estuary

1995 ◽  
Vol 48 (1) ◽  
pp. 97-104
Author(s):  
S. T. Culshaw
Keyword(s):  
Sediment Transport ◽  
Synthetic Aperture Radar ◽  
Coastal Zone ◽  
Synthetic Aperture ◽  
Sar Image ◽  
Visual Interpretation ◽  
Thames Estuary ◽  
Nautical Chart ◽  
Seabed Topography ◽  
Aperture Radar

This paper examines a Synthetic Aperture Radar (SAR) image of the Thames Estuary aided by the relevant nautical chart, tidal, weather and shipping information of the area. By correlating this information it is possible to identify gross sediment transport which would otherwise be hard and financially expensive to detect. Seabed topography, seabed pipelines, some shipping, coastal zone features and different water parcels can be identified.

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