WO2022170634A1 - Line-of-sight path recognition based indoor positioning method independent of device - Google Patents

Line-of-sight path recognition based indoor positioning method independent of device Download PDF

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Publication number
WO2022170634A1
WO2022170634A1 PCT/CN2021/076658 CN2021076658W WO2022170634A1 WO 2022170634 A1 WO2022170634 A1 WO 2022170634A1 CN 2021076658 W CN2021076658 W CN 2021076658W WO 2022170634 A1 WO2022170634 A1 WO 2022170634A1
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line
sight
phase
area
path
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PCT/CN2021/076658
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French (fr)
Chinese (zh)
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夏钢
夏泽宇
方芳
方宁
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苏州优它科技有限公司
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Priority to PCT/CN2021/076658 priority Critical patent/WO2022170634A1/en
Publication of WO2022170634A1 publication Critical patent/WO2022170634A1/en

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    • GPHYSICS
    • G01MEASURING; TESTING
    • G01SRADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S5/00Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations
    • G01S5/18Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations using ultrasonic, sonic, or infrasonic waves
    • G01S5/22Position of source determined by co-ordinating a plurality of position lines defined by path-difference measurements
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04WWIRELESS COMMUNICATION NETWORKS
    • H04W4/00Services specially adapted for wireless communication networks; Facilities therefor
    • H04W4/30Services specially adapted for particular environments, situations or purposes
    • H04W4/33Services specially adapted for particular environments, situations or purposes for indoor environments, e.g. buildings
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04WWIRELESS COMMUNICATION NETWORKS
    • H04W64/00Locating users or terminals or network equipment for network management purposes, e.g. mobility management

Definitions

  • the invention relates to a device-independent line-of-sight path identification indoor positioning method, which belongs to the technical field of indoor positioning and navigation.
  • WiFi indoor positioning methods require the target object to carry a device and communicate data with the detection device to infer position information based on the signal or phase.
  • Passive positioning does not require the target object to carry wireless transmission equipment. It is based on the interference of the target itself to the wireless signal, and the position information is inferred by measuring the signal attenuation degree on the interfered link. Since the target object does not need to carry related equipment, it can be more widely used in various occasions, such as elderly health care.
  • Existing device-independent positioning technologies usually require pre-training. By collecting the signal strength of a specific reference point and a fixed access AP, and matching information such as the degree of signal attenuation to a specific point after adding a target, the fingerprint-based matching positioning method and shell Yessian estimation algorithm, etc., infer the location information of the target object.
  • the current technology achieves pre-training, which increases the difficulty of technical application, hinders the promotion, and is easily disturbed by the complex and changeable indoor environment, resulting in a decrease in positioning accuracy. Therefore, how to achieve reliable and high-precision indoor positioning in the field of device-independent passive positioning technology without prior training has become an important problem that we need to solve.

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  • Engineering & Computer Science (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Signal Processing (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Radar, Positioning & Navigation (AREA)
  • Remote Sensing (AREA)
  • Position Fixing By Use Of Radio Waves (AREA)

Abstract

A line-of-sight path recognition based indoor positioning method independent of a device, comprising step 1: dividing a monitoring area to be a plurality of small grids, an initial value of each small grid being 0; step 2: determining whether each communication link between receiving ends is a line-of-sight path; step 3: if the communication link is not the line-of-sight path, calculating a Fresnel area of the communication link, and adding 1 to all grid values in the Fresnel area; and step 4: traversing all the communication links, a grid having the maximum value being the most likely position of a target object, and if the number of grids having the maximum value is greater than one, taking the center of a plurality of grid positions as the position of the target object.

Description

一种与设备无关的视距路径识别室内定位方法A device-independent line-of-sight path recognition indoor positioning method 技术领域technical field
本发明涉及一种与设备无关的视距路径识别室内定位方法,属于室内定位导航技术领域。The invention relates to a device-independent line-of-sight path identification indoor positioning method, which belongs to the technical field of indoor positioning and navigation.
背景技术Background technique
WIFI技术的广泛应用和部署催生了许多基于WIFI的室内定位技术,无线室内定位技术在其它很多方面也有着广泛的应用,如机器人室内导航、室内游戏、智能人机交互导购、健康护理系统等。WiFi室内定位方法主要分为两种:基于设备的主动式定位方法和与设备无关的被动式定位方法。主动式定位需要目标对象携带设备并与检测设备进行数据通信、根据信号或相位推断位置信息。被动式定位不需要目标对象携带无线传输设设备,是根据目标本身对无线信号产生的干扰,通过测量受干扰链路上信号衰减程度推断位置信息。由于不需要目标对象携带相关设备,因此可以更广泛应用于多种场合,如老人健康护理等。The wide application and deployment of WIFI technology has spawned many WIFI-based indoor positioning technologies, and wireless indoor positioning technology has also been widely used in many other aspects, such as robot indoor navigation, indoor games, intelligent human-computer interaction shopping guide, health care system, etc. There are two main types of WiFi indoor positioning methods: device-based active positioning methods and device-independent passive positioning methods. Active positioning requires the target object to carry a device and communicate data with the detection device to infer position information based on the signal or phase. Passive positioning does not require the target object to carry wireless transmission equipment. It is based on the interference of the target itself to the wireless signal, and the position information is inferred by measuring the signal attenuation degree on the interfered link. Since the target object does not need to carry related equipment, it can be more widely used in various occasions, such as elderly health care.
技术问题technical problem
已有的与设备无关定位技术通常需要事前训练,通过采集特定参考点与固定接入AP的信号强度,以及对加入目标后对特定点信号衰减程度等信息匹配,通过基于指纹匹配定位方法和贝叶斯估计算法等,推断目标对象的位置信息,目前技术实现事前训练让技术应用难度增加,推广受到阻碍,而且也容易受室内复杂多变的环境干扰,导致定位精度下降。因此,如何在设备无关的被动定位技术领域实现可靠且不需要事前训练的高精度室内定位,成为我们需要解决的重要问题。Existing device-independent positioning technologies usually require pre-training. By collecting the signal strength of a specific reference point and a fixed access AP, and matching information such as the degree of signal attenuation to a specific point after adding a target, the fingerprint-based matching positioning method and shell Yessian estimation algorithm, etc., infer the location information of the target object. The current technology achieves pre-training, which increases the difficulty of technical application, hinders the promotion, and is easily disturbed by the complex and changeable indoor environment, resulting in a decrease in positioning accuracy. Therefore, how to achieve reliable and high-precision indoor positioning in the field of device-independent passive positioning technology without prior training has become an important problem that we need to solve.
技术解决方案technical solutions
在此处键入技术解决方案描述段落。Type a technical solution description paragraph here.
有益效果beneficial effect
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附图说明Description of drawings
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本发明的最佳实施方式BEST MODE FOR CARRYING OUT THE INVENTION
在此处键入本发明的最佳实施方式描述段落。Type the best mode description paragraph of the invention here.
本发明的实施方式Embodiments of the present invention
在此处键入本发明的实施方式描述段落。Type the paragraphs describing embodiments of the invention here.
工业实用性Industrial Applicability
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序列表自由内容Sequence Listing Free Content
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Claims (3)

  1. 一种与设备无关的视距路径识别室内定位方法,其特征在于:包括如下步骤:步骤一:将监测区域划分为若干小方格,每个方格的初始值为0;步骤二:判断接收端间的通信链路是否为视距路径;步骤三:若非视距路径则计算该链路的菲涅耳区域,将菲涅耳区域内的所有方格值加1;步骤四:遍历所有通信链路,拥有最大值的方格,则该方格位置为目标对象最可能的位置;有多个方格,则取多个方格位置的中心。A device-independent line-of-sight path identification indoor positioning method, comprising the following steps: step 1: dividing a monitoring area into several small squares, and the initial value of each square is 0; step 2: judging the receiving Whether the communication link between the ends is a line-of-sight path; Step 3: If it is not a line-of-sight path, calculate the Fresnel area of the link, and add 1 to all the grid values in the Fresnel area; Step 4: Traverse all communications Link, the square with the maximum value, the square position is the most likely position of the target object; if there are multiple squares, the center of the multiple square positions is taken.
  2. 所述步骤一包括:1a:在监测区域部署多组无线收发设备,任意一组收发节点间都可以互相通且监测区域划分成若干个大小相同的小方格;1b:当有目标出现在一组收发设备的直线上时,认定此时的通信链路为非视距;1c:通过两条非视距的通信链路,找出这两条非视距路径经过的重叠区域,可以确定目标位置;步骤二包括:2a:利用无线设备多天线的相位差信息来实现视距路径识别;2b:接收端在接收信号的过程中会产生相位偏移测量误差,可通过双天线相位差来消除相位测量误差,设置一个能够分离出视距与非视距路径的阈值,用二元假设检验来判断该相位差属于视距或非视距的相位差范围;步骤三包括:3a:每个信道状态信息由各个子载波的振幅和相位的测量值表示;3b:在视距与非视距的两种环境下,由于非视距受到目标对象的阻碍,其信号传播路径比视距更随机,可以通过相位和振幅的不同判断视距;3c: 是两根天线实际相位差;δ是接收端的时延;β是未知相位偏移;Z表示监测噪音;而k和Ν表示第i个子载波的序列和快速傅里叶变化的长度,δ是两根天线的采样差,信道稳定时δ保持不变。 The first step includes: 1a: deploying multiple groups of wireless transceivers in the monitoring area, any group of transceiver nodes can communicate with each other, and the monitoring area is divided into several small squares of the same size; 1b: when a target appears in a When the group of transceivers is in a straight line, it is determined that the communication link at this time is non-line-of-sight; 1c: Through two non-line-of-sight communication links, find the overlapping area where the two non-line-of-sight paths pass through, and the target can be determined position; Step 2 includes: 2a: use the phase difference information of the multiple antennas of the wireless device to realize the line-of-sight path identification; 2b: the receiving end will generate a phase offset measurement error in the process of receiving the signal, which can be eliminated by the dual-antenna phase difference Phase measurement error, set a threshold that can separate line-of-sight and non-line-of-sight paths, and use binary hypothesis testing to determine that the phase difference belongs to the range of line-of-sight or non-line-of-sight phase differences; Step 3 includes: 3a: Each channel The state information is represented by the measured values of the amplitude and phase of each sub-carrier; 3b: In the two environments of line-of-sight and non-line-of-sight, since the non-line-of-sight is obstructed by the target object, the signal propagation path is more random than the line-of-sight, The viewing distance can be judged by the difference in phase and amplitude; 3c: is the actual phase difference between the two antennas; δ is the time delay at the receiving end; β is the unknown phase offset; Z represents the monitoring noise; The sampling difference of the root antenna, δ remains unchanged when the channel is stable.
  3. β是两根天线的常数相位差,由载波造成的部分已被抵消,其余的可通过相位的平移操作来消除; 3d:通过获取M个数据包的一系列信道状态信息样本,利用ρ因子表示相位的变化值:       ;3e:利用二元假设检验视距(H0)和非视距(H1),即:H0:ρ<ρik 与H1:ρ>ρik ,其中ρik为设定值;3f: 菲涅耳区域是收发天线之间,由电波的直线路径与折线路径的行程差折点形成、以收发天线位置为焦点、以直线路径为轴的椭球面区域;3g: 当目标对象位于收发端链路的菲涅耳区域内时,当接收端与目标距离与发射端与目标之间距离之和 < 接收端与发射端距离+直线路径与折现路径行程差的一半之和时,权值为1,否则为0;步骤四包括:4a:遍历所有通信链路,拥有最大值的方格,则该方格位置为目标对象最可能的位置;4b:有多个方格,则取多个方格位置的中心为目标对象最可能的位置。 β is the constant phase difference of the two antennas, the part caused by the carrier has been cancelled, and the rest can be cancelled by the phase shift operation; 3d: By obtaining a series of channel state information samples of M data packets, use the ρ factor to represent the change value of the phase:   ; 3e: Use binary hypothesis to test line-of-sight (H0) and non-line-of-sight (H1), namely: H0: ρ<ρik and H1: ρ>ρik, where ρik is the set value; 3f: The Fresnel area is the transmission and reception area Between the antennas, the ellipsoid area is formed by the travel difference between the straight path of the radio wave and the polyline path, with the position of the transceiver antenna as the focus and the straight path as the axis; 3g: When the target object is located at the Fresnel of the transceiver link In the area, when the sum of the distance between the receiver and the target and the distance between the transmitter and the target < the sum of the distance between the receiver and the transmitter + half of the distance between the straight path and the discounted path, the weight is 1, otherwise it is 0 ; Step 4 includes: 4a: traverse all communication links, and the square with the maximum value, then the square position is the most likely position of the target object; 4b: if there are multiple squares, then take the center of the multiple square positions the most likely location of the target object.
PCT/CN2021/076658 2021-02-15 2021-02-15 Line-of-sight path recognition based indoor positioning method independent of device WO2022170634A1 (en)

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Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN107911863A (en) * 2017-11-20 2018-04-13 太原理工大学 A kind of method that malice AP positions are determined based on simple gesture
EP3554138A1 (en) * 2016-12-26 2019-10-16 Huawei Technologies Co., Ltd. Method for determining candidate line-of-sight path, and wireless local area network device
CN110426040A (en) * 2019-07-08 2019-11-08 中国人民解放军陆军工程大学 Indoor pedestrian's localization method with non line of sight identification function
CN111521969A (en) * 2020-04-17 2020-08-11 西北工业大学 Passive indoor positioning method based on Wi-Fi

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP3554138A1 (en) * 2016-12-26 2019-10-16 Huawei Technologies Co., Ltd. Method for determining candidate line-of-sight path, and wireless local area network device
CN107911863A (en) * 2017-11-20 2018-04-13 太原理工大学 A kind of method that malice AP positions are determined based on simple gesture
CN110426040A (en) * 2019-07-08 2019-11-08 中国人民解放军陆军工程大学 Indoor pedestrian's localization method with non line of sight identification function
CN111521969A (en) * 2020-04-17 2020-08-11 西北工业大学 Passive indoor positioning method based on Wi-Fi

Non-Patent Citations (2)

* Cited by examiner, † Cited by third party
Title
PIRZADA NASRULLAH; NAYAN M YUNUS; FADZIL M; SUBHAN FAZLI: "A testbed for device free indoor localization system", 2015 INTERNATIONAL SYMPOSIUM ON MATHEMATICAL SCIENCES AND COMPUTING RESEARCH (ISMSC), IEEE, 19 May 2015 (2015-05-19), pages 116 - 120, XP032980938, DOI: 10.1109/ISMSC.2015.7594038 *
YAN SHUPING, DUAN GUI-HUA, ZHANG SHI-GENG: "A Device-free Indoor Localization Algorithm based on Line-of-sight Path Identification", COMPUTER ENGINEERING AND SCIENCE, GUOFANG KEJI DAXUE JISUANJI XUEYUAN, CN, vol. 40, no. 8, 31 August 2018 (2018-08-31), CN , pages 1412 - 1419, XP055957966, ISSN: 1007-130X *

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