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.

scholarly journals Accurate detection method of moving target based on sequential SAR images with multiple azimuth squint angles

2021 ◽  
Vol 2083 (3) ◽  
pp. 032051
Author(s):  
Shiqi Yang ◽  
Yang Liu ◽  
Peili Xi ◽  
Chunsheng Li ◽  
Wei Yang ◽  
...  
Keyword(s):  
False Alarm ◽  
Detection Method ◽  
Synthetic Aperture ◽  
Moving Target ◽  
Constant False Alarm Rate ◽  
Moving Targets ◽  
Sar Images ◽  
Block Level ◽  
Detection Block ◽  
Motion Characteristics

Abstract In this paper, a novel moving target detection method for sequential Synthetic Aperture Radar (SAR) images with different azimuth-squint angles is proposed. In sequential SAR images, due to the movement of the target, the imaging position of moving targets among different frames differs. The method proposed in this paper uses this kind of motion characteristics to achieve the detection of moving targets in multi-frame SAR images. This algorithm can be divided into two parts: block-level detection and pixel-level detection. Block-level detection is achieved by stacked denoising autoencoders to extract the high-dimensional features of the moving target. Pixel-level detection consists of Local Binary Similarity Patterns (LBSP) coding as well as grayscale background subtraction. Pixel-level detection only needs to consider the pixels of foreground image pieces which contain moving targets. This method can not only increase the detection speed, but also suppress the false alarm problem caused by clutter. Experiments are carried out for verifying the validation of the method and the comparison are made between the proposed method and the traditional Constant False Alarm Rate (CFAR) algorithm.

scholarly journals Three-step ground moving target detection method for bistatic forward-looking SAR

2019 ◽  
Vol 2019 (19) ◽  
pp. 5909-5912
Author(s):  
Zhutian Liu ◽  
Zhongyu Li ◽  
Qing Yang ◽  
Junjie Wu ◽  
Yulin Huang ◽  
...  
Keyword(s):  
Target Detection ◽  
Detection Method ◽  
Moving Target ◽  
Moving Target Detection ◽  
Ground Moving Target Detection ◽  
Forward Looking

scholarly journals Multi-Camera Based Setup for Geometrical Measurement of Free-Falling Molten Glass Gob

Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1041
Author(s):  
Mazhar Hussain ◽  
Mattias O’Nils ◽  
Jan Lundgren
Keyword(s):  
Free Fall ◽  
Frame Rate ◽  
Geometrical Parameters ◽  
Contactless Method ◽  
Molten Material ◽  
Dynamic Changes ◽  
Direct Measurements ◽  
Molten Materials ◽  
Free Falling

High temperatures complicate the direct measurements needed for continuous characterization of the properties of molten materials such as glass. However, the assumption that geometrical changes when the molten material is in free-fall can be correlated with material characteristics such as viscosity opens the door to a highly accurate contactless method characterizing small dynamic changes. This paper proposes multi-camera setup to achieve accuracy close to the segmentation error associated with the resolution of the images. The experimental setup presented shows that the geometrical parameters can be characterized dynamically through the whole free-fall process at a frame rate of 600 frames per second. The results achieved show the proposed multi-camera setup is suitable for estimating the length of free-falling molten objects.

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.

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