Non-Line-of-Sight Location With Gauss Filtering Algorithm Based on a Model of Photon Flight
Recently, non-line-of-sight (NLOS) detection based on time of flight (TOF) has been investigated. In order to simulate the NLOS location of a hidden object, we derive the signal scattered by the object and build a model of photon flight based on photon scattering and propagation. To improve the auth...
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doaj-5c6fcd1f188d4708b45b127916b752872021-03-29T18:00:47ZengIEEEIEEE Photonics Journal1943-06552020-01-0112311510.1109/JPHOT.2020.29947849094044Non-Line-of-Sight Location With Gauss Filtering Algorithm Based on a Model of Photon FlightYu Ren0https://orcid.org/0000-0002-0423-1485Zongliang Xie1https://orcid.org/0000-0002-8553-2537Yihan Luo2https://orcid.org/0000-0003-0058-6526Shaoxiong Xu3Haotong Ma4https://orcid.org/0000-0001-8359-370XYi Tan5Institute of Optics and Electronics, Chinese Academy of Science, Chengdu, ChinaInstitute of Optics and Electronics, Chinese Academy of Science, Chengdu, ChinaInstitute of Optics and Electronics, Chinese Academy of Science, Chengdu, ChinaInstitute of Optics and Electronics, Chinese Academy of Science, Chengdu, ChinaInstitute of Optics and Electronics, Chinese Academy of Science, Chengdu, ChinaInstitute of Optics and Electronics, Chinese Academy of Science, Chengdu, ChinaRecently, non-line-of-sight (NLOS) detection based on time of flight (TOF) has been investigated. In order to simulate the NLOS location of a hidden object, we derive the signal scattered by the object and build a model of photon flight based on photon scattering and propagation. To improve the authenticity of the model, the bidirectional reflectance distribution function (BRDF) is used to characterize the scattering process. The Gauss filter is proposed to extract the TOF of the scattering sources of interest without a priori information or manual judgment of the useful scattered signal by filtering the disturbance out of the histogram. The hidden object can then be located by TOF processing. Compared with previous work using a fitting algorithm, the Gauss filtering approach preserves more waveform information and presents improved positioning accuracy and robustness under the influence of noise, which is demonstrated in both simulation and experiment. It is possible to locate a NLOS object automatically through filtering identification of the object signal. The simplicity, high efficiency, and automation of this algorithm make it applicable for tracking a hidden moving object.https://ieeexplore.ieee.org/document/9094044/Non-line-of-sight detectionGauss filterbidirectional reflectance distribution function |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Yu Ren Zongliang Xie Yihan Luo Shaoxiong Xu Haotong Ma Yi Tan |
spellingShingle |
Yu Ren Zongliang Xie Yihan Luo Shaoxiong Xu Haotong Ma Yi Tan Non-Line-of-Sight Location With Gauss Filtering Algorithm Based on a Model of Photon Flight IEEE Photonics Journal Non-line-of-sight detection Gauss filter bidirectional reflectance distribution function |
author_facet |
Yu Ren Zongliang Xie Yihan Luo Shaoxiong Xu Haotong Ma Yi Tan |
author_sort |
Yu Ren |
title |
Non-Line-of-Sight Location With Gauss Filtering Algorithm Based on a Model of Photon Flight |
title_short |
Non-Line-of-Sight Location With Gauss Filtering Algorithm Based on a Model of Photon Flight |
title_full |
Non-Line-of-Sight Location With Gauss Filtering Algorithm Based on a Model of Photon Flight |
title_fullStr |
Non-Line-of-Sight Location With Gauss Filtering Algorithm Based on a Model of Photon Flight |
title_full_unstemmed |
Non-Line-of-Sight Location With Gauss Filtering Algorithm Based on a Model of Photon Flight |
title_sort |
non-line-of-sight location with gauss filtering algorithm based on a model of photon flight |
publisher |
IEEE |
series |
IEEE Photonics Journal |
issn |
1943-0655 |
publishDate |
2020-01-01 |
description |
Recently, non-line-of-sight (NLOS) detection based on time of flight (TOF) has been investigated. In order to simulate the NLOS location of a hidden object, we derive the signal scattered by the object and build a model of photon flight based on photon scattering and propagation. To improve the authenticity of the model, the bidirectional reflectance distribution function (BRDF) is used to characterize the scattering process. The Gauss filter is proposed to extract the TOF of the scattering sources of interest without a priori information or manual judgment of the useful scattered signal by filtering the disturbance out of the histogram. The hidden object can then be located by TOF processing. Compared with previous work using a fitting algorithm, the Gauss filtering approach preserves more waveform information and presents improved positioning accuracy and robustness under the influence of noise, which is demonstrated in both simulation and experiment. It is possible to locate a NLOS object automatically through filtering identification of the object signal. The simplicity, high efficiency, and automation of this algorithm make it applicable for tracking a hidden moving object. |
topic |
Non-line-of-sight detection Gauss filter bidirectional reflectance distribution function |
url |
https://ieeexplore.ieee.org/document/9094044/ |
work_keys_str_mv |
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