Multiple Anchors and RIS-Aided Localization Method in Complex NLOS Environments

Zhenqian Wu

doi:10.1109/JIOT.2024.3433948

2024-11-15

PRE

DOI：10.1109/JIOT.2024.3433948

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摘要

En 中文

This article addresses the localization problem of wireless sensor networks (WSNs) in complex non line-of-sight (NLOS) environments where multiple regions are separated by the blockages. Reconfigurable intelligent surface (RIS) and ultrawideband (UWB) technology are exploited to form a novel multiple anchors and RIS-aided localization (MARL) method, in which anchors and RISs are deployed in pairs in each separated region. The method consists of two stages: 1) a coarse stage and 2) a fine stage. In the coarse stage, each RIS is dynamically adjusted in accordance with predesigned conjugate orthogonal configuration sequence to extract the direct or reflected path components effectively from all anchors during each UWB pulse period. A coarse position of the target is then determined based on the time-delay estimation of the extracted path components, while NLOS bias is assumed to exist in each path. In this stage, the region where the target exists is also identified. In the fine stage, a reflection response vector estimation process is initiated by adjusting the RIS located in the identified region, which is used to formulate a minimum mean square error (MMSE) problem. The solution of the MMSE problem is calibrated with the path coefficient generated from the previously acquired coarse estimate. Then, a reflection vector that contains the true position of the target is obtained. Finally, an accurate estimate is achieved by using gradient descent search algorithm. Simulation results show that the proposed MARL method is a cost-effective scheme for target localization in NLOS environments of WSNs.

Keyword:

Non line-of-sight (NLOS)

reconfigurable intelligent surface (RIS)

ultrawideband (UWB)

wireless sensor networks (WSNs)

Non line-of-sight (NLOS)

reconfigurable intelligent surface (RIS)

ultrawideband (UWB)

wireless sensor networks (WSNs)