Partially-Blocked Near-Field Sensing: Joint Source DoA and Blockage Range Estimation

A diffraction-based channel model is developed for characterizing the line-of-sight channel where the receive array is partially blocked by near-field obstacles. An analytic receive signal model is established where the range and size parameters of the blockage are explicitly modeled in the array steering vector. Based on the proposed model, we consider the joint estimation of the direction of arrivals (DoAs) of impinging RF signals and the parameters of interest for the blockage. General analytical expressions are derived for the Cramér-Rao bounds (CRBs) of both the source-dependent parameters and environmental (common) parameters using both deterministic and stochastic maximum likelihood models. Finally, a Newton's method-based approach is developed to optimize the maximum likelihood criterion to obtain estimates of the DoAs and blockage range of the sensing problem. Numerical results reveal that the maximum likelihood estimates for the DoAs and the blockage range attain the CRB for the stochastic model.

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Published
2024-10-27
DOI
https://doi.org/10.1109/ieeeconf60004.2024.10942642
Primary Topic
Electromagnetic Compatibility and Measurements
Type
article
Field-Weighted Citation Impact
0.00

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article

Partially-Blocked Near-Field Sensing: Joint Source DoA and Blockage Range Estimation

A. Lee Swindlehurst, Jiaqi Xu, Björn Ottersten
Electromagnetic Compatibility and Measurements
article

Partially-Blocked Near-Field Sensing: Joint Source DoA and Blockage Range Estimation

A. Lee Swindlehurst, Jiaqi Xu, Björn Ottersten
article en

Abstract

A diffraction-based channel model is developed for characterizing the line-of-sight channel where the receive array is partially blocked by near-field obstacles. An analytic receive signal model is established where the range and size parameters of the blockage are explicitly modeled in the array steering vector. Based on the proposed model, we consider the joint estimation of the direction of arrivals (DoAs) of impinging RF signals and the parameters of interest for the blockage. General analytical expressions are derived for the Cramér-Rao bounds (CRBs) of both the source-dependent parameters and environmental (common) parameters using both deterministic and stochastic maximum likelihood models. Finally, a Newton's method-based approach is developed to optimize the maximum likelihood criterion to obtain estimates of the DoAs and blockage range of the sensing problem. Numerical results reveal that the maximum likelihood estimates for the DoAs and the blockage range attain the CRB for the stochastic model.

University of Luxembourg (LU), University of California, Irvine (US)
National Science Foundation
Climate action
Openalex Percentile: Top 73%
Electromagnetic Compatibility and Measurements
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