A novel algebraic solution for moving target localization in multi-transmitter multi-receiver passive radar

2018 ◽  
Vol 143 ◽  
pp. 303-310 ◽  
Author(s):  
Yongsheng Zhao ◽  
Yongjun Zhao ◽  
Chuang Zhao
Keyword(s):  
Target Localization ◽  
Algebraic Solution ◽  
Moving Target ◽  
Passive Radar

An Improved Algebraic Solution for Moving Target Localization in Noncoherent MIMO Radar Systems

2016 ◽  
Vol 64 (1) ◽  
pp. 258-270 ◽  
Author(s):  
Heeseong Yang ◽  
Joohwan Chun
Keyword(s):  
Mimo Radar ◽  
Target Localization ◽  
Algebraic Solution ◽  
Moving Target ◽  
Radar Systems

scholarly journals Calibrating the Transmitter and Receiver Location Errors for Moving Target Localization in Multistatic Passive Radar

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 118173-118187 ◽  
Author(s):  
Yongsheng Zhao ◽  
Dexiu Hu ◽  
Zhixin Liu ◽  
Yongjun Zhao
Keyword(s):  
Target Localization ◽  
Moving Target ◽  
Passive Radar ◽  
Location Errors

scholarly journals Moving target localization for multistatic passive radar using delay, Doppler and Doppler rate measurements

2020 ◽  
Vol 31 (5) ◽  
pp. 939-949
Author(s):  
Zhao Yongsheng ◽  
Hu Dexiu ◽  
Zhao Yongjun ◽  
Liu Zhixin
Keyword(s):  
Target Localization ◽  
Moving Target ◽  
Passive Radar

scholarly journals High-Accuracy Recognition and Localization of Moving Targets in an Indoor Environment Using Binocular Stereo Vision

2021 ◽  
Vol 10 (4) ◽  
pp. 234
Author(s):  
Jing Ding ◽  
Zhigang Yan ◽  
Xuchen We
Keyword(s):  
Stereo Vision ◽  
Stereo Matching ◽  
Three Dimensional ◽  
Target Localization ◽  
Parallel Structure ◽  
Moving Target ◽  
Target Area ◽  
Moving Targets ◽  
Binocular Stereo Vision ◽  
Binocular Stereo

To obtain effective indoor moving target localization, a reliable and stable moving target localization method based on binocular stereo vision is proposed in this paper. A moving target recognition extraction algorithm, which integrates displacement pyramid Horn–Schunck (HS) optical flow, Delaunay triangulation and Otsu threshold segmentation, is presented to separate a moving target from a complex background, called the Otsu Delaunay HS (O-DHS) method. Additionally, a stereo matching algorithm based on deep matching and stereo vision is presented to obtain dense stereo matching points pairs, called stereo deep matching (S-DM). The stereo matching point pairs of the moving target were extracted with the moving target area and stereo deep matching point pairs, then the three dimensional coordinates of the points in the moving target area were reconstructed according to the principle of binocular vision’s parallel structure. Finally, the moving target was located by the centroid method. The experimental results showed that this method can better resist image noise and repeated texture, can effectively detect and separate moving targets, and can match stereo image points in repeated textured areas more accurately and stability. This method can effectively improve the effectiveness, accuracy and robustness of three-dimensional moving target coordinates.

Sea and air moving target measurements using a GSM based passive radar

2005 ◽  
Author(s):  
D.K.P. Tan ◽  
Hongbo Sun ◽  
Yilong Lu
Keyword(s):  
Moving Target ◽  
Passive Radar

Maritime Target Localization from Bistatic Range Measurements in Space-Based Passive Radar

2021 ◽  
pp. 1-1
Author(s):  
Mohammad Sadeghi ◽  
Fereidoon Behnia ◽  
Rouhollah Amiri
Keyword(s):  
Target Localization ◽  
Passive Radar ◽  
Range Measurements

scholarly journals 3D Target Localization by Using Particle Filter with Passive Radar Having one Non-cooperative Transmitter and one Receiver

2021 ◽  
Vol 17 (1) ◽  
pp. 36-43
Author(s):  
Anas Mahmoud Almanofi ◽  
Adnan Malki ◽  
Ali Kazem
Keyword(s):  
Particle Filter ◽  
Target Localization ◽  
Passive Radar
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