CN113613327A - WiFi-RTT positioning processing system and method based on reflection projection model enhancement - Google Patents
WiFi-RTT positioning processing system and method based on reflection projection model enhancement Download PDFInfo
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
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- G01C21/165—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration executed aboard the object being navigated; Dead reckoning by integrating acceleration or speed, i.e. inertial navigation combined with non-inertial navigation instruments
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- H—ELECTRICITY
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Abstract
The invention discloses a WiFi-RTT positioning processing system and method based on reflection projection model enhancement, which comprises a data acquisition system, a data preprocessing system, a reflection projection model system and a positioning resolving system, wherein the data acquisition system acquires and stores data into a data set, and meanwhile, the data acquisition system can adjust database information to obtain the position of a router and add the position of the router into the data set; the data preprocessing system comprises a mode discrimination monitoring system, a multipath removing system and a noise reduction system; the data in the data set passes through a data preprocessing system, multipath effect and noise influence are reduced, whitening data are obtained, and a reflection projection model system processes the whitening data through a reflection projection model to obtain a projection anchor point, a pseudo weight array and a pseudo data set; and finally, obtaining a positioning result by a positioning calculation system and carrying out visual processing. According to the invention, through the introduction of the projection reflection model, the problem of positioning result drift caused by unreasonable distribution of routers is solved, and the positioning resolving precision is improved by 35%.
Description
Technical Field
The invention relates to the technical field of indoor positioning, in particular to a WiFi-RTT positioning processing system and method based on reflection projection model enhancement.
Background
The application of location-based services makes the positioning technology receive more and more attention, and simultaneously, higher requirements are put on the precision of the positioning result. With the popularization and application of smart phones, the mobile phones providing various location-based services will become the main carrier for the high-precision positioning of the masses in the future. Since a Global Navigation Satellite System (GNSS) based navigation signal is hardly received indoors, it cannot be used for indoor positioning. In order to solve the indoor positioning problem, various technical solutions have been proposed, such as those based on WiFi, ultra-wideband, bluetooth, inertial sensor, etc., and compared with other technologies, WiFi receives more attention due to its huge audience and low price. The ranging methods such as ToA and TDoA cause the ranging result to have a serious deviation due to clock errors, so that the methods are unreasonable to be used for positioning. The RTT ranging method can provide a more accurate ranging result due to the elimination of the influence caused by clock error, and a good positioning result cannot be obtained due to the presence of a semi-system error.
Disclosure of Invention
The present invention provides a WiFi-RTT positioning processing system and method based on reflection projection model enhancement, so as to solve the problems in the background art.
In order to achieve the purpose, the invention provides the following technical scheme: a WiFi-RTT positioning processing system based on reflection projection model enhancement comprises: the system comprises a data acquisition system, a data preprocessing system, a reflection projection model system and a positioning resolving system;
the data acquisition system is used for acquiring and storing data into a data set, and meanwhile, the data acquisition system can call database information to obtain the position of a router and add the router position into the data set; the data acquisition system transmits the data set to the data preprocessing system;
the data preprocessing system comprises a mode discrimination monitoring system, a multipath removing system and a noise reduction system; the data in the data set is subjected to the data preprocessing system to obtain data, and compared with the original data, the multipath effect and the noise influence are reduced, and the obtained data is called whitening data; the whitened data is passed by the data pre-processing system to the reflective projection model system;
the reflection projection model system is used for obtaining a projection anchor point, a pseudo weight array and a pseudo data set by utilizing a reflection projection model through calculation; finally, the reflection projection model system transmits all obtained results to the positioning calculation system;
and the positioning calculation system is used for processing the result, obtaining a positioning result and carrying out visual processing.
According to another aspect of the present invention, a WiFi-RTT positioning processing method based on reflection projection model enhancement is provided, which includes the following steps:
and 5, processing the result by the positioning calculation system to obtain a positioning result and performing visual processing.
Further, in step 1, the data set includes RTT ranging results provided by the WiFi signal source, RSSI ranging results, RTT variance, a timestamp, and inertial navigation signals provided by the inertial navigation system.
Further, the specific model building process of the reflection projection model comprises the following steps:
step (3.1), performing position calculation according to the ranging result and the router information by a least square method to obtain a position L1;
step (3.2), constructing a hyperplane S1 through router information, enabling L1 to be on the hyperplane S1, enabling the distance from the router to the hyperplane S1 to be minimum, and meanwhile obtaining a normal vector F1 of the hyperplane S1;
step (3.3), obtaining projection anchor point information SAP1 of each router to the hyperplane S1 through a projection theorem;
step (3.4) constructing a pseudo data set SD1 and a pseudo weight matrix SP1 of the projection anchor point information SAP 1;
step (3.5) establishing a position resolving equation containing the ranging result, the router information, the projection anchor point information SAP1 and the pseudo data set SD1 at the same time to obtain a position L2;
step (3.6) constructing a hyperplane S2 by a normal vector F2 orthogonal to a normal vector F1 of the hyperplane S1, so that L2 is on the hyperplane S2 and is orthogonal to the normal vector F, and simultaneously the distance from the router to the hyperplane S2 is minimized;
step (3.7), obtaining projection anchor point information SAP2 of each original router to the hyperplane S2 and projection anchor point information SAP3 of the projection anchor point information SAP1 to the hyperplane S2 through a projection theorem;
and (3.8) constructing pseudo data sets SD2 and SD3 and pseudo weight arrays SP2 and SP3 of the projection anchor point information SAP2 and SAP 3.
Further, the least square method is weighted least square, an original weight is a weight matrix P determined by the RTT variance in the data set, and weights of the projection anchor point information SAP1, SAP2, and SAP3 are determined by the respective pseudo weight matrices SP1, SP2, and SP3, respectively.
Further, the pseudo weights SP1, SP2, SP3 have a multiple relation with the RTT variance, and are independent of each other.
Furthermore, the multiple relation is called a hierarchical weakening factor, and is only related to the number of projections of the original data, the multiple projections are multiplied by the hierarchical weakening factor corresponding to the multiple projections, the first weakening factor u1 is a, the second weakening factor u2 is B, that is, the multiple relation exists: SP1, SP2, and SP3 are a, B, and P.
Further, compared with the original data, the pseudo data set is added with a column of information as state mark information, the state mark information represents the projection times and the projection time, and the rest information is the same as the original information;
further, the positioning calculation system establishes a position calculation equation including the ranging result, the router information, the projection anchor point information SAP1, SAP2, SAP3, and the pseudo data set SD1, SD2, SD3 to obtain a position L2; each router information and projection anchor point information SAP1, SAP2, SAP3 in the positioning solution system has a respective set of semi-system errors.
Further, all the semi-system errors obey normal distribution, so that a solving equation constructed by the positioning solving system has semi-system error constraint, that is, the sum of all the semi-system errors is 0, and the sum of the semi-system errors under respective semi-system error groups of different projection anchor points is also 0.
Has the advantages that:
compared with the prior art, the method can realize the introduction of the projection anchor points and the data information thereof through the introduction of the projection reflection model, reflects twice, and represents the contribution of different projection anchor points in the final positioning calculation process in a limited weighting mode, so the method preliminarily realizes the strategy for solving the problem of uneven router distribution through the virtual router, preliminarily solves the problem of positioning result drift caused by unreasonable router distribution, and improves the positioning calculation precision by 35%.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings needed in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings without creative efforts.
Fig. 1 is a schematic structural diagram of a data post-processing system based on WiFi-RTT ranging according to an embodiment of the present invention;
fig. 2 is a flow chart of a reflective projection modeling according to an embodiment of the invention.
Reference numerals:
1. a data acquisition system; 2. a data preprocessing system; 3. a reflective projection model system; 4. positioning a resolving system; 5. a data set; 6. RTT ranging result; 7. RSSI ranging result; 8. a variance of RTT; 9. a time stamp; 10. inertial navigation signals provided by an inertial navigation system; 11. a mode discrimination monitoring system; 12. a multipath removal system; 13. a noise reduction system; 14. whitening the data; 15. a reflective projection model; 16. projecting anchor points; 17. a pseudo weight matrix; 18. a pseudo data set.
Detailed Description
The technical solutions in the embodiments of the present invention will be described clearly and completely with reference to the accompanying drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, rather than all embodiments, and all other embodiments obtained by a person skilled in the art based on the embodiments of the present invention belong to the protection scope of the present invention without creative efforts.
Referring to fig. 1-2, according to an embodiment of the WiFi-RTT positioning processing system and method based on the reflective projection model enhancement of the present invention, as shown in fig. 1, the system includes a data acquisition system 1, a data preprocessing system 2, a reflective projection model system 3 and a positioning calculation system 4;
the data acquisition system 1 acquires and stores data into a data set 5, and meanwhile, the data acquisition system 1 can acquire a router position by taking database information and add the router position into the data set 5;
the data acquisition system 1 communicates the data set 5 to the data pre-processing system 2; for the data preprocessing system 2, the data preprocessing system 2 includes a mode discrimination monitoring system 11, a multipath removing system 12, and a noise reduction system 13;
the data obtained by the data preprocessing system 2 from the data in the data set 5 reduces the multipath effect and the noise influence compared with the original data, and the obtained data is called whitening data 14;
the whitened data 14 is passed by the data pre-processing system 2 to the reflective projection model system 3;
the reflective projection model system 3 comprises a reflective projection model 15, and the reflective projection model 15 obtains a projection anchor point 16, a pseudo weight matrix 17 and a pseudo data set 18 through calculation;
and finally, the reflection projection model system 3 transmits all obtained results to the positioning calculation system 4, and for the positioning calculation system 4, the positioning calculation system 4 obtains the positioning results and performs visual processing.
According to an embodiment of the present invention, the data set 5 includes RTT ranging result 6 provided by WiFi signal source, RSSI ranging result 7, RTT variance 8, timestamp 9, inertial navigation signal 10 provided by inertial navigation system.
According to another embodiment of the present invention, a WiFi-RTT positioning processing method based on reflection projection model enhancement is provided, which includes the following steps:
and 5, processing the result by the positioning calculation system to obtain a positioning result and performing visual processing.
Further, in step 1, the data set includes RTT ranging result, RSSI ranging result, RTT variance, timestamp, and inertial navigation signal provided by the inertial navigation system, which are provided by the WiFi signal source
According to an embodiment of the present invention, as shown in fig. 2, a specific modeling process of the reflective projection model 10 is as follows:
s101: performing position calculation by a least square method according to the ranging result and the router information to obtain a position L1;
s102: constructing a hyperplane S1 through router information, so that L1 is on the hyperplane S1, the distance from a router to the hyperplane S1 is minimum, and meanwhile, a normal vector F1 of the hyperplane S1 is obtained;
s103: obtaining the projection anchor point information SAP1 of each router to the hyperplane S1 through a projection theorem;
s104: constructing the pseudo data set SD1 and the pseudo weight matrix SP1 of the projection anchor information SAP 1;
s105: simultaneously establishing a position resolving equation containing the ranging result, the router information, the projection anchor point information SAP1 and the pseudo data set SD1 to obtain a position L2;
s106: constructing a hyperplane S2 with a normal vector F2 orthogonal to a normal vector F1 of said hyperplane S1 such that L2 is on hyperplane S2 and orthogonal to normal vector F while minimizing router-to-hyperplane S2 distance;
s107: obtaining the projection anchor point information SAP2 of the original router pair hyperplane S2 and the projection anchor point information SAP3 of the projection anchor point information SAP1 pair hyperplane S2 by a projection theorem;
s108: constructing the pseudo data sets SD2, SD3 and the pseudo weight arrays SP2, SP3 of the projection anchor information SAP2 and SAP 3;
according to an embodiment of the present invention, the least square method is weighted least square, an original weight is a weight matrix P determined by the RTT variance 8 in the data set, and weights of the projection anchor information SAP1, SAP2, and SAP3 are determined by the respective pseudo weight matrices SP1, SP2, SP 3;
according to one embodiment of the invention, the pseudo weights SP1, SP2, SP3 have a multiple relation with the RTT variance 8, and are independent from each other;
according to an embodiment of the present invention, the multiple relationship is called a hierarchical weakening factor, and is only related to the number of projections of the original data, and the multiple projections correspond to the multiple hierarchical weakening factors, and the first weakening factor u1 is generally equal to 0.8, and the second weakening factor u2 is equal to 0.85, that is, there is a multiple relationship: SP1 ═ 0.8 × P, SP2 ═ 0.85 × P, SP3 ═ 0.8 × 0.85 × P; b is usually greater than A, A is usually 0.8, and B is 0.85.
According to an embodiment of the present invention, compared with the original data, the dummy data set has a new column of information as status flag information, the status flag information represents the number of projections and the projection time, and the rest of information, including all information mentioned in claim 2, is the same as the original information;
according to one embodiment of the present invention, the positioning calculation system 4 establishes a position calculation equation including the ranging result, the router information, the projection anchor information SAP1, SAP2, SAP3, and the pseudo data sets SD1, SD2, SD3 to obtain a position L2;
according to an embodiment of the present invention, each router information and projection anchor point information SAP1, SAP2, SAP3 in the positioning solution system 4 has a respective set of semi-system errors;
according to one embodiment of the invention, all semi-system errors obey normal distribution, so that a solving equation constructed by the positioning solving system (4) has semi-system error constraint, that is, the sum of all semi-system errors is 0, and the sum of the semi-system errors under respective semi-system error groups of different projection anchor points is also 0;
although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that changes, modifications, substitutions and alterations can be made in these embodiments without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents.
Claims (10)
1. A WiFi-RTT positioning processing system based on reflection projection model enhancement is characterized by comprising: the system comprises a data acquisition system, a data preprocessing system, a reflection projection model system and a positioning resolving system;
the data acquisition system is used for acquiring and storing data into a data set, and meanwhile, the data acquisition system can call database information to obtain the position of a router and add the router position into the data set; the data acquisition system transmits the data set to the data preprocessing system;
the data preprocessing system comprises a mode discrimination monitoring system, a multipath removing system and a noise reduction system; the data in the data set is subjected to the data preprocessing system to obtain data, and compared with the original data, the multipath effect and the noise influence are reduced, and the obtained data is called whitening data; the whitened data is passed by the data pre-processing system to the reflective projection model system;
the reflection projection model system is used for obtaining a projection anchor point, a pseudo weight array and a pseudo data set by utilizing a reflection projection model through calculation; finally, the reflection projection model system transmits all obtained results to the positioning calculation system;
and the positioning calculation system is used for processing the result, obtaining a positioning result and carrying out visual processing.
2. A WiFi-RTT positioning processing method based on reflection projection model enhancement is characterized by comprising the following steps:
step 1, the data acquisition system acquires and stores data into a data set, and meanwhile, the data acquisition system can call database information to obtain the position of a router and add the router position into the data set;
step 2, the data acquisition system transmits the data set to the data preprocessing system, the data in the data set is processed by the data preprocessing system, and compared with the original data, the obtained data reduces the multipath effect and the noise influence, and is called as whitening data;
step 3, the whitening data is transmitted to the reflective projection model system by the data preprocessing system, and the reflective projection model system obtains a projection anchor point, a pseudo weight array and a pseudo data set by utilizing a reflective projection model in the reflective projection model system through calculation;
step 4, finally, the reflection projection model system transmits all obtained results to the positioning calculation system;
and 5, processing the result by the positioning calculation system to obtain a positioning result and performing visual processing.
3. The WiFi-RTT positioning processing method based on the reflection projection model enhancement as claimed in claim 2, wherein in step 1, the data set includes RTT ranging result provided by WiFi signal source, RSSI ranging result, RTT variance, timestamp, and inertial navigation signal provided by inertial navigation system.
4. The WiFi-RTT positioning processing method based on the reflection projection model enhancement according to claim 2, wherein the reflection projection model concrete model building process comprises the following steps:
step (3.1), performing position calculation according to the two distance measurement results and the router information by a least square method to obtain a position L1;
step (3.2), constructing a hyperplane S1 through router information, enabling L1 to be on the hyperplane S1, enabling the distance from the router to the hyperplane S1 to be minimum, and meanwhile obtaining a normal vector F1 of the hyperplane S1;
step (3.3), obtaining projection anchor point information SAP1 of each router to the hyperplane S1 through a projection theorem;
step (3.4) constructing a pseudo data set SD1 and a pseudo weight matrix SP1 of the projection anchor point information SAP 1;
step (3.5) establishing a position resolving equation containing the ranging result, the router information, the projection anchor point information SAP1 and the pseudo data set SD1 at the same time to obtain a position L2;
step (3.6) constructing a hyperplane S2 by a normal vector F2 orthogonal to a normal vector F1 of the hyperplane S1, so that L2 is on the hyperplane S2 and is orthogonal to the normal vector F, and simultaneously the distance from the router to the hyperplane S2 is minimized;
step (3.7), obtaining projection anchor point information SAP2 of each original router to the hyperplane S2 and projection anchor point information SAP3 of the projection anchor point information SAP1 to the hyperplane S2 through a projection theorem;
and (3.8) constructing pseudo data sets SD2 and SD3 and pseudo weight arrays SP2 and SP3 of the projection anchor point information SAP2 and SAP 3.
5. The method of claim 4, wherein the least square method is weighted least square, an original weight is a weight matrix P determined by the RTT variance in the data set, and weights of the projection anchor point information SAP1, SAP2 and SAP3 are determined by the respective pseudo weight matrices SP1, SP2 and SP 3.
6. The WiFi-RTT positioning processing method based on the enhancement of the reflective projection model of claim 5, wherein the pseudo weights SP1, SP2, SP3 have a multiple relation with the RTT variance, and are independent of each other.
7. The WiFi-RTT positioning processing method based on the reflection projection model enhancement as claimed in claim 6, wherein the multiple relation is called a level weakening factor, and is only related to the number of projections of the original data, multiple projections are multiplied by the level weakening factor, taking a first weakening factor u1 ═ a and a second weakening factor u2 ═ B, that is, there is a multiple relation: SP1, SP2, and SP3 are a, B, and P.
8. The WiFi-RTT positioning processing method based on the reflection projection model enhancement as claimed in claim 4, wherein a column of information added to the pseudo data set is status flag information compared with original data, the status flag information represents projection times and projection time, and the rest information is the same as the original information.
9. The WiFi-RTT positioning processing method based on the enhanced reflection projection model of claim 2, wherein the positioning solution system establishes a position solution equation containing the ranging result, the router information, the projection anchor point information SAP1, SAP2, SAP3 and the pseudo data set SD1, SD2, SD3 to obtain a position L2; each router information and projection anchor point information SAP1, SAP2, SAP3 in the positioning solution system has a respective set of semi-system errors.
10. The WiFi-RTT positioning processing method based on the reflection projection model enhancement as claimed in claim 9, wherein all the semi-system errors obey normal distribution, therefore, a solving equation constructed by the positioning solving system has a semi-system error constraint, that is, the sum of all the semi-system errors is 0, and the sum of the semi-system errors under respective semi-system error groups of different projection anchor points is also 0.
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Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2014177079A1 (en) * | 2013-10-25 | 2014-11-06 | 中兴通讯股份有限公司 | Virtual anchor point-based wireless locating method, device and terminal |
| WO2015021427A1 (en) * | 2013-08-09 | 2015-02-12 | Qualcomm Incorporated | Systems and methods for floor determination of access points in indoor positioning systems |
| CN105474034A (en) * | 2013-08-21 | 2016-04-06 | 高通股份有限公司 | System and method for selecting a Wi-Fi access point for position determination |
| CN106211079A (en) * | 2016-09-23 | 2016-12-07 | 武汉创驰蓝天信息科技有限公司 | The indoor orientation method of RSSI based on iBeacons node range finding and system |
| CN109819394A (en) * | 2018-12-31 | 2019-05-28 | 上海无线通信研究中心 | Based on the WiFi indoor orientation method mixed with ultrasonic wave and its system |
| CN111683337A (en) * | 2020-06-09 | 2020-09-18 | 展讯通信（上海）有限公司 | Fusion positioning method and system based on Wifi and sensor, electronic device and storage medium |
| CN112399350A (en) * | 2020-09-30 | 2021-02-23 | 中国科学院空天信息创新研究院 | WiFi-RTT (wireless fidelity-round trip time) -based ranging and positioning system and method suitable for realizing indoor positioning of mobile phone |
-
2021
- 2021-08-16 CN CN202110939415.5A patent/CN113613327B/en active Active
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2015021427A1 (en) * | 2013-08-09 | 2015-02-12 | Qualcomm Incorporated | Systems and methods for floor determination of access points in indoor positioning systems |
| CN105474034A (en) * | 2013-08-21 | 2016-04-06 | 高通股份有限公司 | System and method for selecting a Wi-Fi access point for position determination |
| WO2014177079A1 (en) * | 2013-10-25 | 2014-11-06 | 中兴通讯股份有限公司 | Virtual anchor point-based wireless locating method, device and terminal |
| CN106211079A (en) * | 2016-09-23 | 2016-12-07 | 武汉创驰蓝天信息科技有限公司 | The indoor orientation method of RSSI based on iBeacons node range finding and system |
| CN109819394A (en) * | 2018-12-31 | 2019-05-28 | 上海无线通信研究中心 | Based on the WiFi indoor orientation method mixed with ultrasonic wave and its system |
| CN111683337A (en) * | 2020-06-09 | 2020-09-18 | 展讯通信（上海）有限公司 | Fusion positioning method and system based on Wifi and sensor, electronic device and storage medium |
| CN112399350A (en) * | 2020-09-30 | 2021-02-23 | 中国科学院空天信息创新研究院 | WiFi-RTT (wireless fidelity-round trip time) -based ranging and positioning system and method suitable for realizing indoor positioning of mobile phone |
Non-Patent Citations (3)
| Title |
|---|
| 李晨辉;甄杰;祝会忠;孙玉曦;盛坤鹏;: "复杂环境下的超宽带高精度定位算法", 测绘科学, no. 01, 19 January 2020 (2020-01-19) * |
| 郭笑尘: "基于半参数估计的智能手机WiFi-RTT定位方法", 《导航定位与授时》, 12 November 2020 (2020-11-12) * |
| 钱志鸿;孙大洋;LEUNG VICTOR;: "无线网络定位综述", 计算机学报, no. 06 * |
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