scholarly journals An Online Multisensor Data Fusion Framework for Radar Emitter Classification

2016 ◽  
Vol 2016 ◽  
pp. 1-16 ◽  
Author(s):  
Dongqing Zhou ◽  
Xing Wang ◽  
Siyi Cheng ◽  
Xi Zhang
Keyword(s):  
Data Fusion ◽  
Data Clustering ◽  
Classification Problem ◽  
Local Processing ◽  
Training Process ◽  
Multisensor Data Fusion ◽  
Electronic Support ◽  
Fusion Framework ◽  
And Training ◽  
Multisensor Data

Radar emitter classification is a special application of data clustering for classifying unknown radar emitters in airborne electronic support system. In this paper, a novel online multisensor data fusion framework is proposed for radar emitter classification under the background of network centric warfare. The framework is composed of local processing and multisensor fusion processing, from which the rough and precise classification results are obtained, respectively. What is more, the proposed algorithm does not need prior knowledge and training process; it can dynamically update the number of the clusters and the cluster centers when new pulses arrive. At last, the experimental results show that the proposed framework is an efficacious way to solve radar emitter classification problem in networked warfare.

scholarly journals Common Data Fusion Framework: An open-source Common Data Fusion Framework for space robotics

2020 ◽  
Vol 17 (2) ◽  
pp. 172988142091176
Author(s):  
Raul Dominguez ◽  
Mark Post ◽  
Alexander Fabisch ◽  
Romain Michalec ◽  
Vincent Bissonnette ◽  
...  
Keyword(s):  
Data Fusion ◽  
Autonomous Systems ◽  
Vital Role ◽  
Sensor Data ◽  
Space Robotics ◽  
Multisensor Data Fusion ◽  
Framework Approach ◽  
The Common ◽  
Fusion Framework ◽  
Multisensor Data

Multisensor data fusion plays a vital role in providing autonomous systems with environmental information crucial for reliable functioning. In this article, we summarize the modular structure of the newly developed and released Common Data Fusion Framework and explain how it is used. Sensor data are registered and fused within the Common Data Fusion Framework to produce comprehensive 3D environment representations and pose estimations. The proposed software components to model this process in a reusable manner are presented through a complete overview of the framework, then the provided data fusion algorithms are listed, and through the case of 3D reconstruction from 2D images, the Common Data Fusion Framework approach is exemplified. The Common Data Fusion Framework has been deployed and tested in various scenarios that include robots performing operations of planetary rover exploration and tracking of orbiting satellites.

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