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Field estimation using binary measurements
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DOI：10.1016/j.sigpro.2021.108430.png)
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In this paper we consider the problem of field estimation using binary sensor measurements. A number of agents are equipped with sensors which can make binary measurements of the field. The agents are mobile and can move around to different locations to collect measurements. In estimating the field, we model the field as a sum of radial basis functions, whose parameters are then estimated using sequential Monte Carlo techniques. We incorporate an active sensing mechanism for the agents to adaptively choose their next measurement location, given the information currently collected. In the multi-agent case, we consider both a centralized setup, and a decentralized setup where agents share their past measurements with each other provided they are within communication range. Simulation studies illustrate the performance of the proposed algorithms.Crown Copyright (c) 2021 Published by Elsevier B.V. All rights reserved.
Keyword:
Autonomous agents
Field estimation
Particle filtering
Quantized measurements
Sensor management
期刊
IF:
3.6
论文数:
9.9K
被引数:
1.7W
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An information-based approach to sensor management in large dynamic networks.png)
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OAAI
PROCEEDINGS OF THE IEEEIF25.9
OAAI分享收藏A Weighted Least-Squares Approach to Parameter Estimation Problems Based on Binary Measurements基于二元测量的参数估计问题的加权最小二乘方法
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