Information space of sensor networks: Lagrangian,energy-momentum tensor,and applications |
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Institution: | 1. School of Automation Science and Electrical Engineering, Beihang University, Beijing 100083, China;2. Wuhan Second Ship Design and Research Institute, Wuhan 430205, China;3. School of Aeronautics and Astronautics, Shanghai Jiao Tong University, Shanghai 200240, China |
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Abstract: | It is a challenge to investigate the interrelationship between the geometric structure and performance of sensor networks due to the increasingly complex and diverse architecture of them. This paper presents two new formulations for the information space of sensor networks, including Lagrangian and energy–momentum tensor, which are expected to integrate sensor networks target tracking and performance evaluation from a unified perspective. The proposed method presents two geometric objects to represent the dynamic state and manifold structure of the information space of sensor networks. Based on that, the authors conduct the property analysis and target tracking of sensor networks. To the best of our knowledge, it is the first time to investigate and analyze the information energy–momentum tensor of sensor networks and evaluate the performance of sensor networks in the context of target tracking. Simulations and examples confirm the competitive performance of the proposed method. |
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Keywords: | Energy-momentum tensor Information science Information space Sensor networks Target tracking |
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