Reducing the Number of Measurement Nodes in RF Imaging Using Antenna-Pattern Diversity With an Extended Rytov Approximation

Radio frequency (RF) imaging that leverages existing wireless communication infrastructure, such as radio tomographic imaging (RTI) and joint communication and sensing (JCAS) is becoming increasingly important. A challenge of RF imaging is that it requires large measurement datasets containing indep...

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Bibliographic Details
Published in:IEEE transactions on antennas and propagation 2023-11, Vol.71 (11), p.8881-8893
Main Authors: Ma, Dingfei, Dubey, Amartansh, Xu, Zihao, Shen, Shanpu, Zhang, Qingfeng, Murch, Ross
Format: Article
Language:English
Subjects:
Antenna measurements
Antennas
Approximation
Configurations
Extended Rytov approximation (xRA)
Image reconstruction
Imaging
inverse scattering
Mathematical analysis
Nodes
pattern diversity
Radio frequency
radio frequency (RF) imaging
radio tomographic imaging (RTI)
Receiving antennas
Rytov approximation (RA)
Transmitting antennas
Wireless communication
Wireless communications
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Summary:Radio frequency (RF) imaging that leverages existing wireless communication infrastructure, such as radio tomographic imaging (RTI) and joint communication and sensing (JCAS) is becoming increasingly important. A challenge of RF imaging is that it requires large measurement datasets containing independent measurements. In this article, we investigate a method to reduce the number of measurement nodes in RF imaging so that it is more suitable for integration with wireless communication. The approach is to exploit antenna-pattern diversity so that each node can collect multiple independent measurements from the same measurement location, thereby decreasing the number of measurement nodes required. Furthermore, we formulate pattern diversity for RF imaging using the recently developed extended Rytov approximation (xRA), which has been demonstrated to provide remarkable RF reconstruction accuracy. The advantage of utilizing xRA is that it allows us to utilize the metric of sensing capacity to straightforwardly quantify the potential of various pattern diversity configurations. Using the sensing capacity metric, we are able to identify configurations where the number of measurement nodes can be reduced by at least a factor of 2. Simulation results are provided to verify the RF imaging approach with reduced measurement nodes, which demonstrates the potential of using pattern diversity.
ISSN:0018-926X
1558-2221
DOI:10.1109/TAP.2023.3310200