Marine Target Localization with Passive GNSS-Based Multistatic Radar: Experimental Results

Author(s):  
M. Antoniou ◽  
A.G. Stove ◽  
D. Tzagkas ◽  
M. Cherniakov ◽  
H. Ma
2021 ◽  
Vol 13 (4) ◽  
pp. 707
Author(s):  
Yu’e Shao ◽  
Hui Ma ◽  
Shenghua Zhou ◽  
Xue Wang ◽  
Michail Antoniou ◽  
...  

To cope with the increasingly complex electromagnetic environment, multistatic radar systems, especially the passive multistatic radar, are becoming a trend of future radar development due to their advantages in anti-electronic jam, anti-destruction properties, and no electromagnetic pollution. However, one problem with this multi-source network is that it brings a huge amount of information and leads to considerable computational load. Aiming at the problem, this paper introduces the idea of selecting external illuminators in the multistatic passive radar system. Its essence is to optimize the configuration of multistatic T/R pairs. Based on this, this paper respectively proposes two multi-source optimization algorithms from the perspective of resolution unit and resolution capability, the Covariance Matrix Fusion Method and Convex Hull Optimization Method, and then uses a Global Navigation Satellite System (GNSS) as an external illuminator to verify the algorithms. The experimental results show that the two optimization methods significantly improve the accuracy of multistatic positioning, and obtain a more reasonable use of system resources. To evaluate the algorithm performance under large number of transmitting/receiving stations, further simulation was conducted, in which a combination of the two algorithms were applied and the combined algorithm has shown its effectiveness in minimize the computational load and retain the target localization precision at the same time.


Author(s):  
Aaron K. Shackelford ◽  
Jean de Graaf ◽  
Sukomal Talapatra ◽  
Karl Gerlach ◽  
Shannon D. Blunt

2013 ◽  
Vol 347-350 ◽  
pp. 3774-3779
Author(s):  
Yu Yang ◽  
Yong Xing Jia ◽  
Chuan Zhen Rong ◽  
Li Juan Wang ◽  
Yuan Wang ◽  
...  

With a focus on complex environments, the present paper describes a new algorithm in scale changed object tracking through color feature. Mean shift (MS) iterative procedure is the best color-based algorithm to find the location of an object. The algorithm performance is not acceptable once tracking scale changed objects in complex environments. In this paper, the main aim is to improve the MS method, using corrected background-weighted histogram (CBWH) algorithm to reduce the interference of background in target localization. To fit the object scale change, the sum of gradient mode (SGM) is employed. The experimental results show that the proposed method is superior to the traditional mean shift tracking in the following aspects: 1) it provides consistent object tracking throughout the video; 2) it is not influenced by the tracked objects scale changes; 3) it is less prone to the background clutter.


2018 ◽  
Vol 56 (8) ◽  
pp. 4808-4819 ◽  
Author(s):  
Hui Ma ◽  
Michail Antoniou ◽  
Andrew G. Stove ◽  
Jon Winkel ◽  
Mikhail Cherniakov

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