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...

Full description

Bibliographic Details
Main Authors: Yu Ren, Zongliang Xie, Yihan Luo, Shaoxiong Xu, Haotong Ma, Yi Tan
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Photonics Journal
Subjects:
Online Access:https://ieeexplore.ieee.org/document/9094044/
id doaj-5c6fcd1f188d4708b45b127916b75287
record_format Article
spelling 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 AT yuren nonlineofsightlocationwithgaussfilteringalgorithmbasedonamodelofphotonflight
AT zongliangxie nonlineofsightlocationwithgaussfilteringalgorithmbasedonamodelofphotonflight
AT yihanluo nonlineofsightlocationwithgaussfilteringalgorithmbasedonamodelofphotonflight
AT shaoxiongxu nonlineofsightlocationwithgaussfilteringalgorithmbasedonamodelofphotonflight
AT haotongma nonlineofsightlocationwithgaussfilteringalgorithmbasedonamodelofphotonflight
AT yitan nonlineofsightlocationwithgaussfilteringalgorithmbasedonamodelofphotonflight
_version_ 1724196939112644608