A novel method for estimation of the target rotation angle in SAR image

2015 ◽  
Author(s):  
Yun Zhang Yun Zhang ◽  
Yuan Zhuang Yuan Zhuang ◽  
Hongzhi Li Hongzhi Li ◽  
Xu Zhang Xu Zhang ◽  
Xiaohui Zhao Xiaohui Zhao
Keyword(s):  
Rotation Angle ◽  
Sar Image ◽  
Target Rotation ◽  
Novel Method

scholarly journals Deceptive Jamming Detection for SAR Based on Cross-Track Interferometry

Sensors ◽  
2018 ◽  
Vol 18 (7) ◽  
pp. 2265 ◽  
Author(s):  
Qingqing Feng ◽  
Huaping Xu ◽  
Zhefeng Wu ◽  
Wei Liu
Keyword(s):  
Sar Interferometry ◽  
Synthetic Aperture ◽  
Sar Image ◽  
Frequency Detection ◽  
Interferometric Phase ◽  
Deceptive Jamming ◽  
Jamming Detection ◽  
Novel Method ◽  
The Difference ◽  
Cross Track

Deceptive jamming against synthetic aperture radar (SAR) can create false targets or deceptive scenes in the image effectively. Based on the difference in interferometric phase between the target and deceptive jamming signals, a novel method for detecting deceptive jamming using cross-track interferometry is proposed, where the echoes with deceptive jamming are received by two SAR antennas simultaneously and the false targets are identified through SAR interferometry. Since the derived false phase is close to a constant in interferogram, it is extracted through phase filtering and frequency detection. Finally, the false targets in the SAR image are obtained according to the detected false part in the interferogram. The effectiveness of the proposed method is validated by simulation results based on the TanDEM-X system.

A Modified Phase Correlation Method for Image Registration

2011 ◽  
Vol 48-49 ◽  
pp. 48-51
Author(s):  
Lu Jing Yang ◽  
Wei Hao ◽  
Chong Lun Li
Keyword(s):  
Image Registration ◽  
Rotation Angle ◽  
Translational Motion ◽  
Correlation Method ◽  
Phase Correlation ◽  
Flow Chart ◽  
Reference Image ◽  
Sar Image ◽  
Registration Method ◽  
Simulation Results

Image registration is a very fundamental and important part in many multi-sensor image based applications. Phase correlation-based image registration method is widely concerned for its small computation amount, strong anti-interference property. However, it can only solve the image registration problem with translational motion. Hence, we proposed a modified phase correlation registration method in the paper. We analyzed the principle of registration, gave the flow chart, and applied the method to the SAR image registration problems with scaling, rotation and translation transformation. Simulation results show that the method can accurately estimate the translation parameters, zoom scale and rotation angle of registrating image relative to the reference image.

Implement of Robot Arm Body Feeling Interaction System Based on the Kinect Skeletal Information

2012 ◽  
Vol 220-223 ◽  
pp. 1203-1206
Author(s):  
Hai Bo Lin ◽  
Wei Lin Mei ◽  
Yi Zhang
Keyword(s):  
Rotation Angle ◽  
The Body ◽  
Experimental Results ◽  
Robot Arm ◽  
Depth Data ◽  
Interaction System ◽  
Calculation Results ◽  
Novel Method ◽  
Tracking Technology ◽  
Wrist Joints

This paper presents a novel method to control a robot arm based on the human skeletal information. First, the depth data is obtained by using a Kinect device. Skeletal tracking technology is used to deal with the depth data to match the various parts of the body and the 3D coordinates of each joint of the body are established. Then, the 3D coordinates are proposed to calculate the rotation angle of the human waist, shoulder, elbow and wrist joints. These four joints of the body are one-to-one correspondence with the four joints of 4-DOF robot arm. Finally, a transformation is conducted to map the calculation results into control commands, and the control commands are sent to the controller of robot arm by serial ports to achieve body feeling interaction. The experimental results show that the method can effectively control the robot arm to rotate and grab objects.

High Accuracy DEM Reconstruction Using SAR Clinometry and Interferometry Method

2013 ◽  
Vol 367 ◽  
pp. 280-285
Author(s):  
Jian Guo Hou ◽  
Yu Chu
Keyword(s):  
High Accuracy ◽  
Weighting Factor ◽  
The Other ◽  
Synthetic Aperture ◽  
Sar Image ◽  
Digital Elevation ◽  
Interferometry Method ◽  
Novel Method ◽  
Elevation Model ◽  
High Coherence

In this paper, a novel method is proposed by combining of radar clinometry and interferometry to improve the accuracy of digital elevation model (DEM) reconstruction. In synthetic aperture radar (SAR) signal processing, the interferometry method uses a couple of high-coherence SAR complex images and the clinometry method uses only one. On one hand, interferometry-derived DEM is much more accurate in regions of higher coherence than the clinometry one. However, in regions of lower coherence, some pronounced errors are produced with the interferometry method due to phase filtering and unwrapping problems. On the other hand, the clinometry method can produce a more robust DEM result by using the intensity of SAR image. Therefore the clinometry-and interferometry-derived DEM is fused by introducing a user-defined weighting factor, where in regions of higher coherence, the DEM results with the interferometry method are remained, and in regions of lower coherence, the interferometry-derived DEM is updated with the clinometry-derived one. Finally, the experimental results with Envisat data show the effectiveness of our approach.

Method for measuring target rotation angle by theodolites

2013 ◽  
Vol 24 (5) ◽  
pp. 055001 ◽  
Author(s):  
Zelin Sun ◽  
Zhao Wang ◽  
Huanchun Zhai ◽  
Xiaoxu Yang
Keyword(s):  
Rotation Angle ◽  
Target Rotation

scholarly journals A Novel Method for L Band SAR Image Segmentation Based on Pulse Coupled Neural Network

2021 ◽  
Vol 4 (2) ◽  
pp. 117
Author(s):  
Harwikarya Harwikarya ◽  
Sabar Rudiarto ◽  
Glorin Sebastian
Keyword(s):  
Neural Network ◽  
Image Processing ◽  
Network Architecture ◽  
Third Generation ◽  
Sar Image ◽  
Neural Network Architecture ◽  
Pulse Coupled Neural Network ◽  
Sar Image Segmentation ◽  
Novel Method ◽  
L Band

Pulse Coupled Neural Network (PCNN) is claimed as a third generation neural network. PCNN has wide purpose in image processing  such as segmentation, feature extraction, sharpening etc.  Not like another neural network architecture, PCNN do not need training. The only weaknes point  of PCNN is parameter tune due to  seven parameters in its five equations. In this research we proposed a novel method for segmentation based on modified PCNN.  In order to evaluate the proposed method, we processed L Band Multipolarisation  Synthetic Apperture Radar Image. The Results showed all area extracted both by using PCNN and ICM-PCNN from the SAR image are match to the groundtruth. There fore the proposed method is work properly.Copyright © 2017  International Journal of  Artificial Intelegence Research.All rights reserved.

Estimation of Instantaneous Hand Joint Centers of Rotation Using 3D Reconstructed Hand Skeleton Motion from CT Scans

2018 ◽  
Vol 62 (1) ◽  
pp. 681-685
Author(s):  
Xiaopeng Yang ◽  
Zhichan Lim ◽  
Hayoung Jung ◽  
Wonsup Lee ◽  
Heecheon You
Keyword(s):  
Ct Scan ◽  
Rotation Angle ◽  
Index Finger ◽  
Ct Scans ◽  
Hand Posture ◽  
Distal Interphalangeal ◽  
Novel Method ◽  
Better Than

The present study estimated instantaneous hand joint centers of rotation (CoR) using 3D reconstructed hand skeleton motions captured from CT scan. We proposed a novel method for estimation of instantaneous joint CoR using the same bone surfaces for different hand postures. Each bone in a template hand posture was registered to the corresponding bone of different hand postures. The registered hand postures (having the same bone surfaces as the template hand posture but different postures) with the template hand posture were then used for estimation of instantaneous joint CoR. The proposed method performed better than the existing methods in estimation of instantaneous joint CoR. Consistency of instantaneous joint CoRs determined in the same rotation angle range was improved by 31.7% to 51.0% in the proposed method. The present study focused on distal interphalangeal (DIP) and proximal interphalangeal (PIP) joints of the index finger of a participant. Joints of the whole hands of more participants will be studied for further generalization of the findings.

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