Local detection of moving target by focusing in SAR images

2016 ◽  
Author(s):  
Viet Vu ◽  
Mats Pettersson ◽  
Thomas Sjogren
Keyword(s):  
Moving Target ◽  
Sar Images ◽  
Local Detection

scholarly journals Extended GLRT Detection of Moving Targets for Multichannel SAR Based on Generalized Steering Vector

Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1478
Author(s):  
Chong Song ◽  
Bingnan Wang ◽  
Maosheng Xiang ◽  
Wei Li
Keyword(s):  
Likelihood Ratio ◽  
Likelihood Ratio Test ◽  
Moving Target ◽  
Ratio Test ◽  
Constant False Alarm Rate ◽  
Moving Targets ◽  
Sar Images ◽  
Steering Vector ◽  
Current Cell ◽  
Data Vector

A generalized likelihood ratio test (GLRT) with the constant false alarm rate (CFAR) property was recently developed for adaptive detection of moving targets in focusing synthetic aperture radar (SAR) images. However, in the multichannel SAR-ground moving-target indication (SAR-GMTI) system, image defocus is inevitable, which will remarkably degrade the performance of the GLRT detector, especially for the lower radar cross-section (RCS) and slower radial velocity moving targets. To address this issue, based on the generalized steering vector (GSV), an extended GLRT detector is proposed and its performance is evaluated by the optimum likelihood ratio test (LRT) in the Neyman-Pearson (NP) criterion. The joint data vector formulated by the current cell and its adjacent cells is used to obtain the GSV, and then the extended GLRT is derived, which coherently integrates signal and accomplishes moving-target detection and parameter estimation. Theoretical analysis and simulated SAR data demonstrate the effectiveness and robustness of the proposed detector in the defocusing SAR images.

scholarly journals Road Extraction from High-Resolution SAR Images via Automatic Local Detecting and Human-Guided Global Tracking

2012 ◽  
Vol 2012 ◽  
pp. 1-10 ◽  
Author(s):  
Jianghua Cheng ◽  
Wenxia Ding ◽  
Xishu Ku ◽  
Jixiang Sun
Keyword(s):  
High Resolution ◽  
Sar Images ◽  
The Road ◽  
Global Tracking ◽  
On The Road ◽  
Airborne Sar ◽  
Fitting In ◽  
Searching Method ◽  
Local Detection ◽  
Local Road

Because of existence of various kinds of disturbances, layover effects, and shadowing, it is difficult to extract road from high-resolution SAR images. A new road center-point searching method is proposed by two alternant steps: local detection and global tracking. In local detection step, double window model is set, which consists of the outer fixed square window and the inner rotary rectangular one. The outer window is used to obtain the local road direction by using orientation histogram, based on the fact that the surrounding objects always range along with roads. The inner window rotates its orientation in accordance with the result of local road direction calculation and searches the center points of a road segment. In global tracking step, particle filter of variable-step is used to deal with the problem of tracking frequently broken by shelters along the roadside and obstacles on the road. Finally, the center-points are linked by quadratic curve fitting. In 1 m high-resolution airborne SAR image experiment, the results show that this method is effective.

Ground Moving Target Indication in SAR Images With Symmetric Doppler Views

2016 ◽  
Vol 54 (1) ◽  
pp. 533-543 ◽  
Author(s):  
Gaohuan Lv ◽  
Yuan Li ◽  
Gang Wang ◽  
Yuling Zhang
Keyword(s):  
Moving Target ◽  
Sar Images ◽  
Ground Moving Target Indication

scholarly journals Moving Target Shadow Analysis and Detection for ViSAR Imagery

2021 ◽  
Vol 13 (15) ◽  
pp. 3012
Author(s):  
Zhihua He ◽  
Xing Chen ◽  
Tianzhu Yi ◽  
Feng He ◽  
Zhen Dong ◽  
...  
Keyword(s):  
Detection Method ◽  
Simulated Data ◽  
Shadow Detection ◽  
Frame Rate ◽  
Moving Target ◽  
Sar Images ◽  
Dynamic Changes ◽  
Moderate Resolution ◽  
Formation Method ◽  
Ground Moving Target Detection

The video synthetic aperture radar (ViSAR) is a new application in radar techniques. ViSAR provides high- or moderate-resolution SAR images with a faster frame rate, which permits the detection of the dynamic changes in the interested area. A moving target with moderate velocity can be detected by shadow detection in ViSAR. This paper analyses the frame rate and the shadow feature, discusses the velocity limitation of ViSAR moving target shadow detection and quantitatively gives the expression of velocity limitation. Furthermore, a fast factorized back projection (FFBP) based SAR video formation method and a shadow-based ground moving target detection method are proposed to generate SAR videos and detect the moving target shadow. The experimental results with simulated data prove the validity and feasibility of the proposed quantitative analysis and the proposed methods.

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