CN114578283A - NLOS transmission base station identification and positioning method based on angle residual error - Google Patents

NLOS transmission base station identification and positioning method based on angle residual error Download PDF

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CN114578283A
CN114578283A CN202210172296.XA CN202210172296A CN114578283A CN 114578283 A CN114578283 A CN 114578283A CN 202210172296 A CN202210172296 A CN 202210172296A CN 114578283 A CN114578283 A CN 114578283A
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base station
angle
nlos
positioning
base stations
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华惊宇
闻建刚
王家乐
倪郑威
王安定
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Zhejiang Gongshang University
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO 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
    • G01S5/00—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations
    • G01S5/01—Determining conditions which influence positioning, e.g. radio environment, state of motion or energy consumption
    • G01S5/011—Identifying the radio environment
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO 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
    • G01S5/00—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations
    • G01S5/02—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations using radio waves
    • G01S5/0205—Details
    • G01S5/021—Calibration, monitoring or correction
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO 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
    • G01S5/00—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations
    • G01S5/02—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations using radio waves
    • G01S5/04—Position of source determined by a plurality of spaced direction-finders
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO 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
    • G01S5/00—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations
    • G01S5/02—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations using radio waves
    • G01S5/06—Position of source determined by co-ordinating a plurality of position lines defined by path-difference measurements
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W64/00—Locating users or terminals or network equipment for network management purposes, e.g. mobility management
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
    • Y02D30/00—Reducing energy consumption in communication networks
    • Y02D30/70—Reducing energy consumption in communication networks in wireless communication networks

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Abstract

An NLOS transmission base station identification and positioning method based on angle residual error includes firstly grouping N base stations in pairs, the number of groups is
Figure DDA0003517853810000011
Then, obtaining a calculated angle value by utilizing cosine theorem according to the obtained TOA and AOA estimated values, then obtaining a difference value between the calculated angle value and the measured AOA value, taking the difference value as an angle residual error, and simultaneously obtaining an angle threshold value; the NLOS transmission base station and the LOS transmission can be identified by comparing the residual error with the thresholdAnd (4) transmitting the base station, and finally performing position estimation on the MS by using the parameter measurement value of the LOS transmission base station, wherein the estimation algorithm adopts a two-step weighted least square algorithm. The invention provides an NLOS transmission base station identification and positioning method based on angle residual error, which can effectively reduce errors and improve positioning accuracy.

Description

NLOS transmission base station identification and positioning method based on angle residual error
Technical Field
The invention relates to the technical field of wireless positioning, and aims at a base station identification and positioning method in an NLOS transmission environment, an NLOS transmission base station and an LOS transmission base station can be identified, and the LOS transmission base station is utilized to position an MS.
Background
Wireless positioning refers to a technique for estimating the position of a mobile terminal using parameters such as angle and distance included in a received signal. In recent years, due to economic development and the demand of people's life, the technology has been widely used, can provide services including emergency call, travel information service, vehicle management and the like, is also applied to a charging system and an intelligent transportation system based on position information, and is an important component of the internet of things.
In an actual wireless transmission environment, a signal sent by a sending end cannot be transmitted along a straight line all the time due to the existence of an obstacle, the obstacle enables the signal to reach a receiving end through scattering and diffraction, and information such as a distance and an angle obtained by the receiving end contains large errors, so that the accuracy of a wireless positioning algorithm is remarkably reduced. Accordingly, in the practical application of wireless positioning technology, it is very necessary to reduce or even reduce the error caused by non-line-of-sight (NLOS) transmission. Based on field measurements of motorola and ericsson pairs, NLOS errors tend to increase with increasing linear distance between the Mobile Station (MS) and the base station or Base Station (BS), which further exacerbates the impact on the accuracy of conventional positioning algorithms.
Disclosure of Invention
In order to overcome the defects of larger error and lower positioning precision of the existing wireless positioning mode, the invention provides the angle residual error-based NLOS transmission base station identification and positioning method which effectively reduces the error and improves the positioning precision.
The technical scheme adopted by the invention for solving the technical problems is as follows:
an NLOS transmission base station identification and positioning method based on angle residual errors comprises the following steps:
1) the transmission of the mobile station MS is received by a plurality of base stations, assuming that the time of arrival TOA and angle of arrival AOA information in the signal have been estimated, while these estimated information and the coordinates of the base stations BS involved in the positioning are available in the positioning master base station.
2) Every two base stations are divided into a group, and if N base stations participate in positioning, the group can be divided into
Figure BDA0003517853790000021
The method comprises the following steps that (1) group, BS coordinates in each group and corresponding distance measurement and angle measurement information are extracted from a positioning main base station, wherein the distance measurement information is equivalent to TOA, and the angle measurement information is equivalent to AOA;
3) for each group, the positioning main base station calculates included angles between the two BSs and the target MS based on a trigonometric geometry method, and then calculates a difference value between the measured angle and the calculated angle, so as to obtain an angle residual error of each group;
4) comparing the magnitude relation between the residual value and the threshold, if the magnitude relation is smaller than the threshold, the group of base stations are LOS transmission base stations, otherwise, judging that NLOS transmission base stations exist in the group of base stations;
5) repeating the threshold comparison processing in the step 4) on all base station groups, and integrating the identification results to obtain all NLOS transmission base stations and LOS transmission base stations;
6) extracting the LOS transmission base station in the step 5), and constructing a positioning equation set by using the corresponding TOA and AOA information according to the positioning geometric relation;
7) carrying out linearization processing on the positioning equation set;
8) the MS coordinates are estimated using a two-step weighted least squares algorithm.
Further, in step 3), assuming that in the topology diagram formed by the two BSs and 1 MS, the point a and the point B respectively represent the positions of the two BSs, and the point C represents the position of one MS, the cosine value of the included angle between the line segment AB and the line segment BC obtained by the trigonometric geometric method is:
Figure BDA0003517853790000022
in the formula, a, b, c, theta2' denotes the values of the BS measured distance of B → C, the BS measured distance of A → C, the inter-BS distance of A → B, and the calculated angle of &, respectively, since the BS coordinates are known, C can be calculated in advance. Similarly, the cosine value of the included angle between the line segment BA and the line segment AC can be calculated and obtained:
Figure BDA0003517853790000023
wherein theta is1' represents the calculated angle value of ≈ BAC.
According to the AOA information obtained by measurement and the angle value obtained by calculation, defining the angle residual error as
δ1＝|θ1-θ1'|,δ2＝|θ2-θ2'| (3)
Assuming AB is the X-axis, then θ1、θ2Namely the measured angle of arrival of the base station a and the base station B. If there is no NLOS transmission in the localization environment, δ1And delta2Are small otherwise their values may be large due to NLOS errors.
Selecting an appropriate residual variable greatly affects the identification accuracy of NLOS transmission, and in the above process, angle measurement and distance measurement are two parameters that affect each other, but angle measurement is more easily affected by NLOS errors than distance measurement, and the influence on positioning performance is stronger. Therefore, the invention researches that residual errors are defined through measurement and calculation analysis of angle variables, so as to establish an NLOS transmission base station identifier based on the angle residual errors:
Figure BDA0003517853790000031
formula (4) shows that when two angle residual values obtained in grouping are both smaller than a set threshold value, the group of BSs is determined as LOS transmission, otherwise, at least one BS is influenced by NLOS transmission.
Still further, in the step 4), according to the positioning geometric relationship and the residual errorDisturbance analysis, defining a threshold TH2Is composed of
Figure BDA0003517853790000032
Wherein sigmar,σaRespectively representing the standard deviation of the distance measurement noise and the angle measurement noise, which are estimated by multiple measurements, theta2' represents the calculated value of the included angle ABC, wherein cos theta2' see formula 1,
Figure BDA0003517853790000033
defining TH similarly1Is composed of
Figure BDA0003517853790000034
Wherein, theta1' represents the calculated value of the included angle BAC, wherein cos theta1In the case of the' see formula 2,
Figure BDA0003517853790000035
meanwhile, the value of the parameter lambda directly influences the judgment result of the threshold, and the judgment result is determined by computer simulation.
Furthermore, in the step 5), after the LOS transmission base station is correctly identified, the MS is subjected to position estimation by using the measured values of the LOS transmission base station; firstly, according to the information obtained from the positioning main base station, defining the coordinate of MS as (x, y) and the coordinate of ith BS as (x)i,yi) The ranging and angle measurement values between the ith BS and MS are set to riAnd thetaiIn the steps 6) and 7), a linear positioning equation set is constructed according to the geometric meanings of the measured distance and the arrival angle:
Y＝AX (7)
wherein R ═ x2+y2，
Figure BDA0003517853790000041
In the base station identification phase, riCorresponding to the respective a or b,m in the formula (7) represents the number of the LOS transmission base stations screened out in the base station identification stage in the step 4), and the value of M is less than or equal to N.
In the step 8), firstly, according to a least square criterion, obtaining:
Figure BDA0003517853790000042
will measure distance riR for the true linear distancei 0Expressed, the corresponding error vector can be expressed as:
Figure BDA0003517853790000043
wherein ei,αjThe measurement errors of the distance and angle with respect to their true values are represented respectively, the T operator represents a matrix transpose, and the above equation (9) is expressed in matrix form, which yields:
ψ＝2Bz (10)
wherein
Figure BDA0003517853790000044
z＝[e1,e2,...,eM,α1,α2,...,αM]TDiag {. is said to mean a diagonal matrix with bracketed elements as diagonal elements, and the covariance matrix of B is as follows
Ψ＝E[ψψT]＝4BQB (11)
In the formula
Figure BDA0003517853790000045
The variances of the measured distance and the measured angle of arrival at the ith BS are respectively represented.
In the step 8), a solution of X is obtained by using a least square algorithm:
Figure BDA0003517853790000046
Figure BDA0003517853790000047
the covariance matrix of (a) is:
Figure BDA0003517853790000048
since the three elements of the WLS estimation described above are not actually independent, a 2 nd least squares estimation is performed, assuming
Figure BDA0003517853790000049
The errors of the three elements are respectively s1,s2And s3Then, then
Figure BDA0003517853790000051
Thus, another set of error vectors is defined as:
ψ'＝b'-A'X' (15)
wherein
Figure BDA0003517853790000052
Is pushed from the above formula
Figure BDA0003517853790000053
The covariance matrix of the vector ψ' is then
Figure BDA0003517853790000054
In the step 8), obtaining the solution of X' again according to the WLS algorithm
Figure BDA0003517853790000055
The possible position of the MS is finally obtained
Figure BDA0003517853790000056
And selecting the solution in (19) that is closest (12) to the result as the final estimate.
The technical conception of the invention is as follows: and deleting the base stations with NLOS transmission paths in the base stations participating in positioning, only keeping the measurement information of the LOS transmission base station for processing, and applying the measurement information to MS coordinate estimation. Here, los (nlos) transmission base station means that the propagation path of the MS to the base station is los (nlos). The more LOS base stations participating in MS positioning, the smaller the error influence brought by NLOS transmission, and the accuracy of MS positioning can be realized, so the NLOS base station identification technology is very important in improving the accuracy of MS positioning. The method is characterized in that residual definition and threshold determination are required by base station identification, residual definition and calculation are carried out by utilizing angle variables which are more sensitive to NLOS error change in wireless positioning, and the LOS transmission base station is identified through comparison of the threshold and the residual. The invention optimizes the traditional residual error calculation mode, and simultaneously improves the NLOS identification precision due to the sensitivity of the angle residual error to the NLOS error change and the comparison with the side length residual error. After obtaining the LOS base station, the MS location can be estimated using various classical trilateration methods.
The invention has the following beneficial effects: after obtaining the distance (equivalent to TOA) between the BS and the MS and the estimated value of the arrival angle, grouping the base stations, and calculating two calculated angle values and an angle residual value by each group of base stations through ranging information. And obtaining an angle threshold value of the NLOS transmission base station identifier according to the positioning geometric relation and the disturbance analysis and simulation of the residual error, wherein the angle residual error can obtain a more accurate result because the angle variable is more sensitive to the error change of the NLOS. By comparing the threshold with each set of angle residual calculation values, the NLOS transmission base station and the LOS transmission base station can be identified. The MS position estimation is carried out according to the obtained LOS transmission base station measurement information, the estimation algorithm can be an LS method or a two-step WLS method and any other traditional methods, and the performance is illustrated by taking the LS method and the two-step WLS method as examples. The invention has high identification accuracy, and adopts a two-step WLS algorithm with higher precision to estimate the position of the MS after identification, so that the invention has high positioning precision in an NLOS/LOS transmission environment.
Description of the drawings:
fig. 1 is a processing step diagram of an NLOS transmission base station identification and positioning method based on angle residual.
Fig. 2 is a schematic view of the positioning geometry.
FIG. 3 is a schematic diagram showing the effect of the angle standard deviation on the Root Mean Square Errors (RMSE) of each algorithm, wherein (a) is 2LOS-BS, (b) is 3LOS-BS, and (c) is 4 LOS-BS. The horizontal scale in the figure is the angular standard deviation (in degrees) and the vertical scale in RMSE (in meters).
FIG. 4 is a diagram showing the effect of the standard deviation of the range on the mean square error of each algorithm, wherein (a) is 2LOS-BS, (b) is 3LOS-BS, and (c) is 4 LOS-BS. The horizontal coordinate in the figure is the standard deviation of the distance measurement (in meters) and the vertical coordinate is the RMSE (in meters).
In the above figure, nLOS-BS means that the number of actual LOS base stations is N, and the simulation adopts a classical 5-base-station topology with a cell radius of 1000 meters, that is, N is 5.
The comparison algorithm used in the above simulation diagram is shown in table 1:
TABLE 1
Algorithm Description of the invention
NI-TS-WLS-A The method of the invention
RWGH Residual error weighting method
CLS Constrained least squares method
PR-TS-WLS Two-step least square method after positioning residual error identification
NI-TS-WLS Two-step least square method after side length residual error identification
NI-LS-A Least square method for base station identification
The ideal NI-TS-WLS Two-step WLS method for known LOS base stations
In table 1, the RWGH method is from document 1: chen P C, an non-line-of-sight interference assignment [ A ], Proc. IEEE Wireless Communications and network Conference WCNC' 99[ C ], New Oreans, 1999: 316-; chen P C, a non-line-of-sight error elimination algorithm in position estimation [ A ],1999 IEEE Wireless communication and network International conference discourse [ C ], New Orleans,1999: 316-. CLS methods are from Wang X, A TOA-based location of reducing the errors from non-line-of-sight (NLOS) propagation [ J ], IEEE Transactions on vehicle Technology,2003,52(1): 112-; wang X, a TOA positioning algorithm [ J ] capable of reducing non-line-of-sight propagation errors, IEEE on-board technical exchange 2003,52(1): 112-. NI-TS-WLS-A is the recognition positioning method of the invention (the positioning part adopts two-step WLS); NI-LS-A is the positioning by the least square algorithm after the base station is identified; the NI-TS-WLS is from Huajingyu, ZhouKai, Lifeng, Xushijiang, Menglimin, a side length residual error-based NLOS transmission base station identification and positioning method [ P ]. Zhejiang: CN105979583A,2016-09-28.PR-TS-WLS from Huajingyu, Li Zhennan, Li Feng, Xushijiang, Lu is Dang. CN106125043A,2016-11-16.The ideal NI-TS-WLS shows that perfectly known LOS base station information is located by using The two-step WLS algorithm, and The performance of The LOS base station information is best shown as a reference for comparison.
Detailed Description
Referring to fig. 1 to 4, a method for identifying and positioning an NLOS transmission base station based on an angle residual includes:
1) the transmission of the mobile station MS is received by a plurality of base stations, assuming that the time of arrival TOA and angle of arrival AOA information in the signal have been estimated, while these estimated information and the coordinates of the base stations BS involved in the positioning are available in the positioning master base station.
2) Every two base stations are divided into a group, and if N base stations participate in positioning, the group can be divided into
Figure BDA0003517853790000071
The method comprises the following steps that (1) group, BS coordinates in each group and corresponding distance measurement and angle measurement information are extracted from a positioning main base station, wherein the distance measurement information is equivalent to TOA, and the angle measurement information is equivalent to AOA;
3) for each group, the positioning main base station calculates included angles between the two BSs and the target MS based on a trigonometric geometry method, and then calculates a difference value between the measured angle and the calculated angle, so as to obtain an angle residual error of each group;
4) comparing the magnitude relation between the residual value and the threshold, if the magnitude relation is smaller than the threshold, the group of base stations are LOS transmission base stations, otherwise, judging that NLOS transmission base stations exist in the group of base stations;
5) repeating the threshold comparison processing in the step 4) on all base station groups, and integrating the identification results to obtain all NLOS transmission base stations and LOS transmission base stations;
6) extracting the LOS transmission base station in the step 5), and constructing a positioning equation set by using the corresponding TOA and AOA information according to the positioning geometric relation;
7) carrying out linearization processing on the positioning equation set;
8) the MS coordinates are estimated using a two-step weighted least squares algorithm.
The NLOS transmission base station identification positioning method based on the angle residual error is further detailed. Without LOSs of generality, it is assumed that points a and B in fig. 2 represent the positions of two base stations, respectively, and point C represents the position of one mobile station MS, and since there is an obstacle between point a and point C, it is considered as NLOS transmission, while between point B and point C, it is LOS transmission. Note that fig. 2 is only a schematic diagram of NLOS transmission, and an actual transmission environment may include a dual LOS transmission base station and a dual NLOS transmission base station. In fig. 2, the base station a is an NLOS transmission base station, and its measurement angle and measurement distance both include NLOS errors, while the base station B is an LOS transmission base station, so its measurement distance and measurement angle are very close to the true values.
According to fig. 2, if base station a and base station B are both LOS transmission, then A, B, C may form a triangle, and the cosine of the included angle between segment AB and segment BC is known according to the geometrical relationship of the triangle:
Figure BDA0003517853790000081
in the formula, a, b, c, theta2' denotes calculated angle values representing the BS measured distance of B → C, the BS measured distance of a → C, the inter-BS distance of a → B, and ≈ ABC, respectively, and since the BS coordinates are known, C can be calculated in advance. Similarly, the cosine value of the included angle between the line segment BA and the line segment AC can be calculated and obtained:
Figure BDA0003517853790000091
in the formula [ theta ]1' respectively denotes the calculated angle value of ≈ BAC.
According to the AOA value and the calculated angle value, defining the angle residual error as
δ1＝|θ1-θ1'|,δ2＝|θ2-θ2'| (3)
Wherein theta is1、θ2Respectively representing the angle of arrival and the straight line measured by base station A and base station B
Figure BDA0003517853790000092
Absolute value of the difference between the included angles with the X axis; assuming AB is the X-axis, then θ1、θ2Namely the arrival angles measured by the base station A and the base station B. If there is no NLOS transmission in the localization environment, δ1And delta2Are small otherwise their values may be large due to the effects of NLOS errors.
Selecting an appropriate residual variable greatly affects the identification accuracy of NLOS transmission, and in the above process, angle measurement and distance measurement are two parameters that affect each other, but angle measurement is more easily affected by NLOS errors than distance measurement, and affects positioning performance more strongly. Therefore, the invention researches that residual errors are defined through measurement and calculation analysis of angle variables, so as to establish an NLOS transmission base station identifier based on the angle residual errors:
Figure BDA0003517853790000093
formula (4) shows that when the angle residual error values obtained in each group are all smaller than the set threshold value, the group of BSs are determined as LOS transmission, otherwise, at least one BS is influenced by NLOS transmission.
Still further, in the step 4), a threshold TH is defined according to the positioning geometric relationship and the disturbance analysis of the residual error2Is composed of
Figure BDA0003517853790000094
Wherein σr,σaThe method respectively represents the standard deviation of distance measurement noise and angle measurement noise, the two values are generally obtained by multiple measurement estimation, the method is provided by external AOA and TOA estimators, and the proposed algorithm does not directly estimate the two parameters. Theta.theta.2' represents the real value of the included angle ABC,where cos θ2' see formula 1,
Figure BDA0003517853790000095
similarly, TH1 is defined as
Figure BDA0003517853790000101
Wherein, theta1' represents the true value of the included angle BAC, wherein cos theta1' see the formula 2, see,
Figure BDA0003517853790000102
meanwhile, the value of the parameter lambda directly influences the judgment result of the threshold, so that the simulation value obtained by the method is 3.1 as determined by computer simulation.
After the step 5) realizes the correct identification of the LOS transmission base station, the MS is subjected to position estimation by using the measurement values of the LOS transmission base station, which is called as a positioning stage in the invention. In said steps 6) and 7), firstly, the coordinates of the MS are defined as (x, y) and the coordinates of the ith BS are defined as (x, y) based on the information acquired in the positioning master base stationi,yi) The ranging and angle measurement values between the ith BS and MS are set to riAnd thetaiAnd constructing a linear positioning equation set according to the geometric meanings of the measuring distance and the arrival angle:
Y＝AX (7)
wherein R ═ x2+y2，
Figure BDA0003517853790000103
In the base station identification phase, riCorresponding to a or b, M in the formula 7) is the number of the LOS transmission base stations screened out in the base station identification stage in the step 4), and the value of M is less than or equal to N.
In the step 8), firstly, according to a least square criterion, obtaining:
Figure BDA0003517853790000104
by r isi 0Is represented by riAnd defines an error vector:
Figure BDA0003517853790000105
wherein ei,αjRespectively representing the measurement error of the distance and angle with respect to their true values, and the T operator represents the matrix transpose. If (9) is converted into a matrix multiplication form, the following results are obtained:
ψ＝2Bz (10)
wherein
Figure BDA0003517853790000106
z＝[e1,e2,...,eM,α1,α2,...,αM]TDiag {. is said to mean a diagonal matrix with bracketed elements as diagonal elements, and the covariance matrix of B is as follows
Ψ＝E[ψψT]＝4BQB (11)
In the formula
Figure BDA0003517853790000111
The variances of the measured distance and the measured angle of arrival at the ith BS are respectively represented.
In the step 8), a WLS algorithm is used to obtain a solution of X:
Figure BDA0003517853790000112
the previous study shows that
Figure BDA0003517853790000113
The covariance matrix of (a) is:
Figure BDA0003517853790000114
since the three elements estimated by the WLS are not actually independent, it is necessary to do soLine 2 least squares estimation. Suppose that
Figure BDA0003517853790000115
The errors of the three elements are respectively s1,s2And s3Then, then
Figure BDA0003517853790000116
Thus, another set of error vectors can be defined as:
ψ'＝b'-A'X' (15)
wherein
Figure BDA0003517853790000117
Is pushed from the above formula
Figure BDA0003517853790000118
The covariance matrix of the vector ψ' is then
Figure BDA0003517853790000119
In the step 7), the solution of X' is obtained again according to the WLS algorithm
Figure BDA00035178537900001110
The possible position of the MS is finally obtained
Figure BDA0003517853790000121
And selecting the solution closest (12) to the result in (19) as the final estimate, referred to as a two-step WLS algorithm since the estimation process employs two WLS solutions.
Fig. 1 mainly describes a specific implementation process of the present invention, which first obtains TOA and AOA estimated values of each base station in a positioning master base station, and then groups base stations participating in positioning, where each group has two base stations. And for each base station group, calculating the corresponding angle residual error and threshold value by using the derivation formula, judging whether the base station group is the LOS transmission base station or not by using the NLOS transmission base station identifier, and finally, integrating judgment results of all the base station groups to distinguish all the LOS transmission base stations and NLOS transmission base stations. Abandoning the base station measurement information including NLOS transmission, constructing a positioning equation set by combining the measurement information of the LOS transmission base station with a positioning geometry principle, carrying out linearization processing on the positioning equation set, and estimating the position of the MS by adopting a two-step WLS algorithm.
Fig. 2 is a schematic diagram of positioning geometry in a group of base stations. Where points a and B represent two BS sites, point C represents one MS, and point D represents an electromagnetic wave reflector on the a-C path. Since the BS location is fixed, therefore the distance
Figure BDA0003517853790000122
The value c may be calculated in advance. The distance and angle measured by BS at point A are b and theta respectively1The distance and angle measured by BS at point B are a and theta, respectively2。θ3The measured angle error of the MS in the presence of the NLOS base station is shown, and is only illustrated here, and does not participate in the calculation process.
Figure 3 plots the effect of the goniometric standard deviation on the Root Mean Square Error (RMSE) of each algorithm, with the range standard deviation fixed at 10 meters. The study is based on the classical five base station topology with (0,0) point as the topological center and the remaining four points being (1000 ), (-1000, -1000), (1000, -1000) respectively, in meters. In the figure, the abscissa represents the AOA measurement standard deviation, the ordinate represents the root mean square error, and nLOS-BS represents n LOS base stations in 5 base stations. It can be seen from the figure that the accuracy of the present invention is lower than the ideal case when the number of LOS base stations is 2, but still better than the traditional positioning algorithm. When The number of LOS base stations is increased to 3 and 4, The curve of The angle residual error identification and positioning algorithm is very close to The ideal NI-TS-WLS curve used as a reference, The trend of stable increase is always kept along with The increase of The angle measurement standard deviation, and compared with The positioning residual error and The side length residual error value, The method has robustness under The condition of ensuring accuracy. In addition, the accuracy of the NI-LS-A is always lower than that of the NI-TS-WLS-A algorithm because the two-step WLS algorithm of the TOA/AOA is not used, which also indicates that the accuracy of the two-step WLS algorithm based on the TOA/AOA mixed parameter is better than that of the traditional least square algorithm in the LOS environment.
Fig. 4 compares the influence of the ranging standard deviation on the root mean square error of each algorithm, the simulation environment is the same as that of fig. 3, the abscissa represents the numerical value of the ranging standard deviation, and the angle standard deviation is fixed to 1 degree. Although the accuracy of the algorithm of the invention is lower than the ideal case when the number of LOS base stations is 2, the algorithm is better than the traditional positioning algorithm. When The number of LOS base stations is increased to 3 and 4, The curve of The angle residual error identification and positioning algorithm is very close to The ideal NI-TS-WLS curve serving as a reference, which shows that The identification accuracy of The algorithm almost reaches 100%. Compared with the positioning residual and the side length residual, the identification accuracy of the angle residual is always superior to that of the positioning residual and the side length residual, and the superiority of the angle variable applied to NLOS transmission identification is reflected. In addition, the accuracy of the NI-LS-A is always lower than that of the NI-TS-WLS-A algorithm because the two-step WLS algorithm of the TOA/AOA is not used, which also indicates that the accuracy of the two-step WLS algorithm based on the TOA/AOA mixed parameter is better than that of the traditional least square algorithm in the LOS environment.

Claims (4)

1. An NLOS base station identification and positioning method of angle residual is characterized by comprising the following steps:
1) receiving the sending signal of the mobile station MS by a plurality of base stations, supposing that the TOA and AOA information in the signal are estimated, and obtaining the estimated information and the BS coordinates participating in positioning in the positioning main base station;
2) every two base stations are divided into a group, if N base stations participating in positioning are provided, the base stations can be divided into the group, and the positioning main base station extracts BS coordinates in each group and corresponding ranging and angle measuring information, wherein the ranging information is equivalent to TOA, and the angle measuring information is equivalent to AOA;
3) for each group, the positioning main base station calculates included angles between the two BSs and the target MS based on a trigonometric geometric method, and then calculates a difference value between the measured angle and the calculated angle, so as to obtain an angle residual error of each group;
4) comparing the magnitude relation between the residual value and the threshold, if the magnitude relation is smaller than the threshold, the group of base stations are LOS transmission base stations, otherwise, judging that NLOS transmission base stations exist in the group of base stations;
5) repeating the threshold comparison processing in the step 4) on all base station groups, and synthesizing the identification results to obtain all NLOS transmission base stations and LOS transmission base stations;
6) extracting the LOS transmission base station in the step 5), and constructing a positioning equation set by using the corresponding TOA and AOA information according to the positioning geometric relation;
7) carrying out linearization processing on the positioning equation set;
8) the MS coordinates are estimated using a two-step weighted least squares algorithm.
2. The method of claim 1 for NLOS base station identification and location of angular residuals, wherein: in the step 3), assuming that in a topological graph formed by two BSs and 1 MS, a point a and a point B respectively represent positions of two base stations, a point C represents a position of one mobile station MS, and a cosine value of an included angle between a line segment AB and a line segment BC is obtained according to a trigonometric geometry method as follows:
Figure FDA0003517853780000011
in the formula, a, b, c, theta2' denotes the values of the BS measured distance of B → C, the BS measured distance of A → C, the inter-BS distance of A → B, and the calculated angle of &, respectively, since the BS coordinates are known, C can be calculated in advance. Similarly, the cosine value of the included angle between the line segment BA and the line segment AC can be calculated and obtained:
Figure FDA0003517853780000021
wherein theta is1' represents the calculated angle value of ≈ BAC.
According to the AOA information obtained by measurement and the angle numerical value obtained by calculation, defining the angle residual error as
δ1＝|θ1-θ1'|,δ2＝|θ2-θ2'| (3)
Assuming AB is the X axis, then θ1、θ2Namely the measured angle of arrival of the base station a and the base station B. If there is no NLOS transmission in the localization environment, δ1And delta2Are small otherwise their values may be large due to NLOS errors.
3. The method of claim 2, wherein the NLOS base station of an angle residual is characterized in that: obtaining a corresponding NLOS transmission base station detector obtained in the step 4):
Figure FDA0003517853780000022
formula (4) shows that when the angle residual error values obtained in each group are all smaller than the set threshold value, the group of BSs are determined as LOS transmission, otherwise, at least one BS is influenced by NLOS transmission.
4. The method for NLOS base station identification and location of angular residual of claim 1 or 2, wherein: in the steps 6) and 7), a linear positioning equation set is constructed according to the geometric meanings of the measured distance and the arrival angle:
Y＝AX (5)
wherein R ═ x2+y2，
Figure FDA0003517853780000023
In the base station identification phase, riCorrespond toCorresponding to a or b, M in the formula (5) represents the number of the LOS transmission base stations screened out in the base station identification stage in the step 4), and the value of M is less than or equal to N.
In the step 8), firstly, according to a least square criterion, obtaining:
Figure FDA0003517853780000024
will measure distance riR for the true linear distancei 0Expressed, the corresponding error vector can be expressed as:
Figure FDA0003517853780000025
wherein ei,αjThe measurement errors of the distance and angle with respect to their true values, respectively, are represented by the T operator, which represents a matrix transposition, and the above equation (7) is expressed in matrix form, which yields:
ψ＝2Bz (8)
wherein
Figure FDA0003517853780000031
z＝[e1,e2,...,eM,α1,α2,...,αM]TDiag {. is said to mean a diagonal matrix with bracketed elements as diagonal elements, and the covariance matrix of B is as follows
Ψ＝E[ψψT]＝4BQB (9)
In the formula
Figure FDA0003517853780000032
Figure FDA0003517853780000033
The variances of the measured distance and the measured angle of arrival at the ith BS are respectively represented.
In the step 8), a solution of X is obtained by using a least square algorithm:
Figure FDA0003517853780000034
Figure FDA0003517853780000035
the covariance matrix of (a) is:
Figure FDA0003517853780000036
since the three elements obtained by the WLS estimation are not actually independent, the 2 nd least squares estimation is performed, assuming
Figure FDA0003517853780000039
The errors of the three elements are respectively s1,s2And s3Then, then
Figure FDA0003517853780000037
Thus, another set of error vectors is defined as:
ψ'＝b'-A'X' (13)
wherein
Figure FDA0003517853780000038
Is pushed from the above formula
Figure FDA0003517853780000041
The covariance matrix of the vector ψ' is then
Figure FDA0003517853780000042
In the step 8), obtaining the solution of X' again according to the WLS algorithm
Figure FDA0003517853780000043
The possible position of the MS is finally obtained
Figure FDA0003517853780000044
And selecting the solution in (17) that is closest to (10) the result as the final estimate.
CN202210172296.XA 2022-02-24 2022-02-24 NLOS transmission base station identification and positioning method based on angle residual error Pending CN114578283A (en)

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* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN115002904A (en) * 2022-08-03 2022-09-02 湖南工商大学 Non-line-of-sight base station identification method based on UWB sensor
CN115988641A (en) * 2023-03-20 2023-04-18 深圳市美力高集团有限公司 Personnel wireless positioning auxiliary system based on depth data
CN116819433A (en) * 2023-08-29 2023-09-29 湘江实验室 UWB non-line-of-sight positioning method based on estimated distance

Cited By (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN115002904A (en) * 2022-08-03 2022-09-02 湖南工商大学 Non-line-of-sight base station identification method based on UWB sensor
CN115002904B (en) * 2022-08-03 2022-10-14 湖南工商大学 Non-line-of-sight base station identification method based on UWB sensor
CN115988641A (en) * 2023-03-20 2023-04-18 深圳市美力高集团有限公司 Personnel wireless positioning auxiliary system based on depth data
CN115988641B (en) * 2023-03-20 2023-06-23 深圳市美力高集团有限公司 Personnel wireless positioning auxiliary system based on depth data
CN116819433A (en) * 2023-08-29 2023-09-29 湘江实验室 UWB non-line-of-sight positioning method based on estimated distance
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