scholarly journals Passive Localization of Moving Target with Channel State Information

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Xiaolong Yang ◽  
Jiacheng Wang ◽  
Wei Nie ◽  
Yong Wang

With the popularity of wireless networks and smart devices, wireless signal-based passive target sensing and localization have become a hot research topic and attracted numerous researchers’ interests. The existing passive localization solutions require multiple receivers, which is not practical for real-world applications. In response to this compelling problem, in this paper, we propose a practical single access point-based passive moving target localization system. Concretely, it first utilizes multiple antennas of the access point to form an antenna array and extended antenna, to capture channel state information (CSI) at different spatial locations. Then, leveraging the obtained CSI, the signal parameters, including the angle of arrival (AoA) and time of flight (ToF), are estimated. Based on the estimated signal parameters and the locations of the antenna array and extended antenna, finally, the passive localization of the moving target is realized. Comprehensive experiments are conducted under the real-world scenario with two different test platforms, and the experimental results show the proposed algorithm’s median localization can reach 1.087 m when the number of antennas is 4 and the signal bandwidth is 80 MHz, demonstrating the effectiveness of the proposed algorithm.

2020 ◽  
Vol 12 (12) ◽  
pp. 1995
Author(s):  
David Sánchez-Rodríguez ◽  
Miguel A. Quintana-Suárez ◽  
Itziar Alonso-González ◽  
Carlos Ley-Bosch ◽  
Javier J. Sánchez-Medina

In recent years, indoor localization systems based on fingerprinting have had significant advances yielding high accuracies. Those approaches often use information about channel communication, such as channel state information (CSI) and received signal strength (RSS). Nevertheless, these features have always been employed separately. Although CSI provides more fine-grained physical layer information than RSS, in this manuscript, a methodology for indoor localization fusing both features from a single access point is proposed to provide a better accuracy. In addition, CSI amplitude information is processed to remove high variability information that can negatively influence location estimation. The methodology was implemented and validated in two scenarios using a single access point located in two different positions and configured in 2.4 and 5 GHz frequency bands. The experiments show that the methodology yields an average error distance of about 0.1 m using the 5 GHz band and a single access point.


Author(s):  
Xiaolong Yang ◽  
Yuan She ◽  
Liangbo Xie ◽  
Zhaoyu Li

AbstractSmart environment sensing and other applications play a more and more important role along with the rapid growth of device-free sensing-based services, and extracting parameters contained in channel state information (CSI) accurately is the basis of these applications. However, antenna arrays in wireless devices are all planar arrays whose antenna spacing does not meet the spatial sampling theorem while the existing parameter estimation methods are almost based on the array satisfying the spatial sampling theorem. In this paper, we propose a parameter estimation algorithm to estimate the signal parameters of angle of arrival (AoA), time of flight (ToF), and Doppler frequency shift (DFS) based on the service antenna array, which does not satisfy the spatial sampling theorem. Firstly, the service antenna array is mapped to a virtual linear array and the array manifold of the virtual linear array is calculated. Secondly, the virtual linear array is applied to estimate the multi-dimensional parameters of the signal. Finally, by calculating the geometric relationship between the service antenna and the virtual linear array, the parameters of the signal incident on the service antenna can be obtained. Therefore, the service antenna can not only use the communication channel for information communication, but also sense the surrounding environment and provide related remote sensing and other wireless sensing application services. Simulation results show that the proposed parameter estimation algorithm can accurately estimate the signal parameters when the array antenna spacing does not meet the spatial sampling theorem. Compared with TWPalo, the proposed algorithm can estimate AoA within 3∘, while the error of ToF and DFS parameter estimation is within 1 ns and 1 m/s.


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