CN112394321A - Multi-base-station real-time positioning method and system based on Bluetooth signals - Google Patents

Multi-base-station real-time positioning method and system based on Bluetooth signals Download PDF

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Publication number
CN112394321A
CN112394321A CN202110078642.3A CN202110078642A CN112394321A CN 112394321 A CN112394321 A CN 112394321A CN 202110078642 A CN202110078642 A CN 202110078642A CN 112394321 A CN112394321 A CN 112394321A
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signal
base station
representing
real
base
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CN112394321B (en
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魏强
吴川
嵇寿江
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Panchip Microelectronics Co ltd
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Panchip Microelectronics Co ltd
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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
    • G01S5/02—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

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Abstract

The invention relates to the field of Bluetooth signal positioning, in particular to a multi-base-station real-time positioning method and system based on Bluetooth signals. The multi-base-station real-time positioning method comprises the following steps: step S1, acquiring signal receiving intensity, azimuth angle, pitch angle and spatial spectrum peak value of all base station receiving signals at the current moment; step S2, screening the signal receiving intensity, the azimuth angle, the pitch angle and the spatial spectrum peak value; step S3, acquiring a first predicted position of the signal at the current moment; and step S4, determining the real-time positioning result of the current time according to the first predicted position and the second predicted position. The technical scheme of the invention has the beneficial effects that: the method and the system are applied to a plurality of base stations, azimuth angles and pitch angles which are not accurate enough and can cause misjudgment are screened out, and real-time positioning results of signals are obtained according to the screened signal receiving intensity, the screened azimuth angles, the screened pitch angles and spatial spectrum peak values.

Description

Multi-base-station real-time positioning method and system based on Bluetooth signals
Technical Field
The invention relates to the field of Bluetooth signal positioning, in particular to a multi-base-station real-time positioning method and system based on Bluetooth signals.
Background
The GPS, i.e. global positioning system, is a positioning system of high-precision radio navigation based on air satellite, it can provide accurate geographical position, vehicle speed and accurate time information anywhere in the world and in the near-earth space, the distribution of the satellite can make more than 4 satellites be observed anywhere in the world and anytime, and can maintain the geometry of good positioning resolving precision, thus providing continuous global navigation capability in time. However, the GPS system relies on line-of-sight transmission between the satellites and the receiver, and buildings attenuate GPS satellite signals greatly, so that the results of indoor positioning cannot be obtained accurately.
Disclosure of Invention
In view of the above problems in the prior art, a method and a system for multi-base-station real-time positioning based on bluetooth signals are provided.
The multi-base-station real-time positioning method based on the Bluetooth signals is applied to a plurality of base stations, and all the base stations synchronously receive a signal; the multi-base-station real-time positioning method comprises the following steps:
step S1, acquiring the signal receiving intensity, azimuth angle, pitch angle and spatial spectrum peak value of the signal received by all the base stations at the current moment;
step S2, screening the signal reception intensity, the azimuth angle, the pitch angle, and the spatial spectrum peak;
step S3, performing combined positioning according to the filtered signal receiving intensity, the azimuth angle, the pitch angle and the spatial spectrum peak value to obtain a first predicted position of the signal at the current moment;
step S4, determining a second predicted position of the current time according to the real-time positioning result of the previous time, and determining the real-time positioning result of the current time according to the first predicted position and the second predicted position.
Preferably, the step S1 includes:
step S11, acquiring the signal received by the base station at the current time;
step S12, acquiring the corresponding signal receiving strength according to the energy in the signal;
step S13, obtaining a corresponding spatial spectrum according to orthogonality between the noise subspace in the signal and the array manifold vector, performing peak search on the spatial spectrum to obtain a spatial spectrum peak value and a corresponding angle, and using the corresponding angle as the azimuth angle and the pitch angle at which the base station receives the signal.
Preferably, the step S2 includes:
step S21, obtaining a mean value and a standard deviation of the signal reception intensity at the current time;
step S22, presetting a coefficient;
step S23, sequentially determining whether the difference between the received signal strength and the mean is greater than the product of the coefficient and the standard deviation:
if yes, the signal reception strength is screened out, and then the step S24 is carried out;
if not, the signal receiving strength is retained, and then the step S24 is carried out;
step S24, determining whether all the signal reception intensities have been filtered:
if yes, go to step S25;
if not, returning to the step S23;
step S25, screening the azimuth angle, the pitch angle, and the spatial spectrum peak corresponding to the signal reception intensity according to the screened signal reception intensity.
Preferably, the step S3 includes:
step S31, acquiring the position information of all the base stations;
step S32, sequentially obtaining a first tangent value and a second tangent value according to the position information of each base station and the azimuth angle and the pitch angle at which the base station receives the signal, and respectively constructing a first matrix and a second matrix according to the position information, the first tangent value and the second tangent value;
step S33, obtaining a corresponding weight matrix according to the spatial spectrum peak value of the signal received by each base station;
step S34, obtaining the first predicted position according to the first matrix, the second matrix and the weight matrix.
Preferably, the first tangent value and the second tangent value are expressed by the following formulas:
Figure 686810DEST_PATH_IMAGE001
wherein the content of the first and second substances,
Figure DEST_PATH_IMAGE002
for representing the qth of said first tangent, where q is used to represent the ranking number of said base station among all base stations,
Figure 414070DEST_PATH_IMAGE003
for indicating the azimuth angle at which the q-th base station receives the signal;
Figure DEST_PATH_IMAGE004
for representing the second tangent value, wherein
Figure 521703DEST_PATH_IMAGE005
Said pitch angle representing the reception of said signal by the qth of said base station;
x is used to represent the abscissa in a first predicted position of the signal;
Figure DEST_PATH_IMAGE006
an abscissa for representing position information of the q-th base station;
y is used to represent the ordinate in a first predicted position of the signal;
Figure 261120DEST_PATH_IMAGE007
ordinate in position information for representing q-th base station；
Z is used to represent the vertical coordinate in a first predicted location of the signal;
Figure DEST_PATH_IMAGE008
for representing the vertical coordinate in the location information of the q-th base station.
Preferably, the first matrix is expressed by the following formula:
Figure 137809DEST_PATH_IMAGE009
wherein the content of the first and second substances,
Figure DEST_PATH_IMAGE010
for representing the qth of said first tangent, where q is used to represent the ranking number of said base station among all base stations,
Figure 429113DEST_PATH_IMAGE011
for indicating the azimuth angle at which the q-th base station receives the signal;
Figure DEST_PATH_IMAGE012
for representing the second tangent value, wherein
Figure 774775DEST_PATH_IMAGE013
Said pitch angle representing the reception of said signal by the qth of said base station;
l is used to indicate the number after screening.
Preferably, the second matrix is expressed by the following formula:
Figure DEST_PATH_IMAGE014
wherein the content of the first and second substances,
Figure 301571DEST_PATH_IMAGE015
for representing the qth of said first tangent, where q is used to represent the ranking number of said base station among all base stations,
Figure DEST_PATH_IMAGE016
for indicating the azimuth angle at which the q-th base station receives the signal;
Figure 173712DEST_PATH_IMAGE017
for representing the second tangent value, wherein
Figure DEST_PATH_IMAGE018
Said pitch angle representing the reception of said signal by the qth of said base station;
x is used to represent the abscissa in a first predicted position of the signal;
Figure 245705DEST_PATH_IMAGE019
an abscissa for representing position information of the q-th base station;
y is used to represent the ordinate in a first predicted position of the signal;
Figure DEST_PATH_IMAGE020
an ordinate in the position information for representing the q-th base station;
z is used to represent the vertical coordinate in a first predicted location of the signal;
Figure 327930DEST_PATH_IMAGE021
a vertical coordinate for representing position information of the q-th base station;
l is used to indicate the number after screening.
Preferably, the weight is expressed as:
Figure DEST_PATH_IMAGE022
wherein the content of the first and second substances,
Figure 533784DEST_PATH_IMAGE023
is used for representing the q-th weight, wherein q is used for representing the sequence number of the base station in all the base stations;
Figure DEST_PATH_IMAGE024
the spatial spectrum peak used for representing the q base station receiving the signal;
l is used to indicate the number after screening.
Preferably, the weight matrix is represented as:
Figure 100002_DEST_PATH_IMAGE025
wherein the content of the first and second substances,
Figure DEST_PATH_IMAGE026
is used for representing the q-th weight, wherein q is used for representing the sequence number of the base station in all the base stations;
Figure 100002_DEST_PATH_IMAGE027
the numbers after screening are indicated.
Preferably, the first predicted position is expressed by the following formula:
Figure DEST_PATH_IMAGE028
wherein the content of the first and second substances,
Figure 100002_DEST_PATH_IMAGE029
the first predicted position is used for representing the current time, wherein K is used for representing the current time;
m is used to represent the first matrix;
w is used to represent the weight matrix;
n is used to represent the second matrix.
Preferably, the step S4 includes:
preferably, the step S4 includes:
step S41, constructing a prediction state equation, and obtaining a second prediction position of the current time according to the real-time positioning result of the previous time and the prediction state equation;
step S42, determining the real-time positioning result of the current time according to the first predicted position and the second predicted position.
A multi-base station real-time positioning system based on Bluetooth signals is applied to a plurality of base stations, and all the base stations synchronously receive a signal; the multi-base-station real-time positioning system comprises:
the acquisition module is used for acquiring the signal receiving intensity, azimuth angle, pitch angle and spatial spectrum peak value of the signals received by all the base stations at the current moment;
the screening module is connected with the acquisition module and is used for screening the signal receiving intensity, the azimuth angle, the pitch angle and the spatial spectrum peak value;
the prediction module is connected with the screening module and used for carrying out combined positioning according to the screened signal receiving intensity, the azimuth angle, the pitch angle and the spatial spectrum peak value to obtain a first prediction position of the signal at the current moment;
and the filtering module is connected with the prediction module and used for determining a second prediction position of the current moment according to a real-time positioning result of the previous moment and determining a real-time positioning result of the current moment according to the first prediction position and the second prediction position.
The technical scheme has the following advantages or beneficial effects: the method and the system are applied to a plurality of base stations, azimuth angles and pitch angles which are not accurate enough and can cause misjudgment are screened out, and real-time positioning results of signals are obtained according to the screened signal receiving intensity, the screened azimuth angles, the screened pitch angles and spatial spectrum peak values.
Drawings
Fig. 1 is a schematic flowchart of a multi-base-station real-time positioning method based on bluetooth signals according to a preferred embodiment of the present invention;
fig. 2 is a schematic diagram of multiple base stations receiving bluetooth signals in a preferred embodiment of the present invention;
FIG. 3 is a schematic flow chart of step S1 according to the preferred embodiment of the present invention;
FIG. 4 is a schematic flow chart of step S2 according to the preferred embodiment of the present invention;
FIG. 5 is a schematic flow chart of step S3 according to the preferred embodiment of the present invention;
FIG. 6 is a schematic flow chart of step S4 according to the preferred embodiment of the present invention;
fig. 7 is a schematic structural diagram of a multi-base-station real-time positioning system based on bluetooth signals in a preferred embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention, and it is apparent that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be obtained by a person skilled in the art without any inventive step based on the embodiments of the present invention, are within the scope of the present invention.
In addition, the embodiments of the present invention and the features of the embodiments may be combined with each other without conflict.
The invention is further described with reference to the following drawings and detailed description, but is not intended to be limited thereto.
As shown in fig. 1, a multi-base-station real-time positioning method based on bluetooth signals is applied to a plurality of base stations, and as shown in fig. 2, all the base stations synchronously receive a signal; the multi-base-station real-time positioning method comprises the following steps:
step S1, acquiring signal receiving intensity, azimuth angle, pitch angle and spatial spectrum peak value of all base station receiving signals at the current moment;
step S2, screening the signal receiving intensity, the azimuth angle, the pitch angle and the spatial spectrum peak value;
step S3, performing combined positioning according to the filtered signal receiving intensity, azimuth angle, pitch angle and spatial spectrum peak value to obtain a first predicted position of the signal at the current moment;
and step S4, determining a second predicted position of the current time according to the real-time positioning result of the previous time, and determining the real-time positioning result of the current time according to the first predicted position and the second predicted position.
Specifically, the method for positioning multiple base stations in real time based on the Bluetooth signal is provided in consideration of the fact that indoor real-time positioning cannot be accurately performed in the prior art, and is applied to multiple base stations, a first predicted position of a signal emission source is analyzed, and a real-time positioning result is obtained according to filtering. Moreover, considering that the accuracy of the azimuth angle and the pitch angle of the received signal of the base station obtained through the space spectrum search is reduced along with the increase of the distance between the signal emission source and the base station, if the real-time positioning result is obtained according to all the azimuth angles and the pitch angles, the precision of the real-time positioning result is reduced, and the occupancy rate of the operation resource is increased. Therefore, the method also obtains the signal receiving intensity and the spatial spectrum peak value, the signal receiving intensity is used as the basis for judging the accuracy of the azimuth angle, the pitch angle and the spatial spectrum peak value, the azimuth angle and the pitch angle which are not accurate enough and can cause misjudgment are screened out according to the numerical value of the signal receiving intensity, the resource utilization rate is improved, the spatial spectrum peak value has the corresponding relation with the azimuth angle and the pitch angle, in the process of determining the azimuth angle and the pitch angle, the spatial spectrum search is usually needed, the angle corresponding to the spectrum peak value of the spatial spectrum is used as the azimuth angle and the pitch angle, therefore, the spatial spectrum peak value is also used as the basis for judging the accuracy of different azimuth angles and pitch angles, the spatial spectrum peak value corresponding to the screened azimuth angle and pitch angle is obtained, the corresponding weight is set according to the spatial spectrum peak value, and the weight is weighted to, And the pitch angle further improves the positioning accuracy.
Furthermore, the positioning is carried out based on the Bluetooth signals, so that the deployment is convenient, the positioning accuracy is improved, the power consumption is low, the cost is low, the protocol is simple, and the integration into other systems is convenient.
Wherein, in order to accurately express the signal receiving strength, azimuth angle and pitch angle of the received signals of different base stations, the base stations are numbered as
Figure DEST_PATH_IMAGE030
。
In a preferred embodiment of the present invention, as shown in fig. 3, step S1 includes:
step S11, acquiring the signal received by the base station at the current moment;
step S12, acquiring corresponding signal receiving strength according to the energy in the signal;
step S13, obtaining a corresponding spatial spectrum according to the orthogonality of the noise subspace in the signal and the array manifold vector, performing peak search on the spatial spectrum to obtain a spatial spectrum peak value and a corresponding angle, and using the corresponding angle as an azimuth angle and a pitch angle of the signal received by the base station.
Specifically, the antenna arrays on all the base stations receive a signal synchronously through the synchronization header information of the signal, and therefore, in step S11, the signals received by the antennas on the base stations can be specifically expressed as:
Figure 14093DEST_PATH_IMAGE031
wherein the content of the first and second substances,
Figure DEST_PATH_IMAGE032
for signals received by antennas at the base station denoted as qNumber;
Figure 771834DEST_PATH_IMAGE033
an array manifold vector for representing antennas at the qth base station;
s (t) for representing signals incident to the base station;
n (t) is a noisy data vector where the antenna noise is white noise and its variance is
Figure DEST_PATH_IMAGE034
Noise is statistically independent of signal.
Then, in step S12, the following formula can be used to obtain the signal reception strength of the corresponding base station according to the energy in the signal:
Figure 92088DEST_PATH_IMAGE035
wherein the content of the first and second substances,
Figure DEST_PATH_IMAGE036
for indicating the signal reception strength of the q-th base station;
Figure DEST_PATH_IMAGE037
for representing a signal and T for representing the period of the signal.
Finally, in step S13, the following formula can be used to obtain the corresponding spatial spectrum according to the orthogonality between the noise subspace of the signal and the array manifold vector:
Figure DEST_PATH_IMAGE038
wherein the content of the first and second substances,
Figure 163949DEST_PATH_IMAGE039
for representing the spatial spectrum of the q-th base station, wherein
Figure DEST_PATH_IMAGE040
For the purpose of indicating the azimuth angle,
Figure 886048DEST_PATH_IMAGE041
for representing pitch angle;
Figure DEST_PATH_IMAGE042
an array manifold vector for representing antennas at the qth base station;
Figure 424477DEST_PATH_IMAGE043
for representing a feature vector of the noise subspace orthogonal to the array manifold vector at the qth base station.
Spatial spectrum to the q base station
Figure DEST_PATH_IMAGE044
And searching to obtain a space spectrum peak value and an angle corresponding to the space spectrum peak value, and taking the angle corresponding to the peak value as an azimuth angle and a pitch angle of the base station for receiving the signal.
Since the specific location information of each base station is different and the signal reception strength, the azimuth angle and the pitch angle of different base stations receiving signals synchronously are also different when the method is applied to a plurality of base stations, the signal reception strength, the azimuth angle, the pitch angle and the spatial spectrum peak corresponding to each base station are obtained by steps S11-S13 for each base station.
In a preferred embodiment of the present invention, as shown in fig. 4, step S2 includes:
step S21, obtaining the mean value and standard deviation of the signal receiving intensity at the current moment;
step S22, presetting a coefficient;
step S23, sequentially determining whether the difference between the received signal strength and the mean is greater than the product of the coefficient and the standard deviation:
if yes, the signal reception strength is screened out, and then the process goes to step S24;
if not, the signal receiving strength is retained, and then the step S24 is proceeded to;
step S24, determining whether all signal reception strengths have been screened:
if yes, go to step S25;
if not, returning to the step S23;
and step S25, screening the azimuth angle, the pitch angle and the spatial spectrum peak value corresponding to the signal receiving intensity according to the screened signal receiving intensity.
Specifically, inaccurate azimuth angles, elevation angles and spatial spectrum peaks can be screened out by using the signal receiving strength, and the screening process can be set correspondingly based on different screening rules.
Here, in step S21-step S25:
step S21, obtaining the signal receiving strength of N base stations
Figure 746874DEST_PATH_IMAGE045
,
Figure DEST_PATH_IMAGE046
,…,
Figure 901387DEST_PATH_IMAGE047
Mean value of
Figure DEST_PATH_IMAGE048
And standard deviation, wherein, mean value
Figure 602627DEST_PATH_IMAGE048
The following formula can be used to represent:
Figure 233329DEST_PATH_IMAGE049
wherein the content of the first and second substances,
Figure 652809DEST_PATH_IMAGE048
mean value for signal reception strength of all base stations, N forIndicates the number of all base stations,
Figure DEST_PATH_IMAGE050
for indicating the signal reception strength of the q-th base station.
Wherein, standard deviation
Figure 613943DEST_PATH_IMAGE051
The following formula can be used to represent:
Figure DEST_PATH_IMAGE052
wherein the content of the first and second substances,
Figure 435268DEST_PATH_IMAGE051
for indicating the standard deviation of the signal reception strengths of all base stations, N for indicating the number of all base stations,
Figure 971292DEST_PATH_IMAGE050
for indicating the signal reception strength of the q-th base station.
Step S22, presetting a coefficient
Figure 143647DEST_PATH_IMAGE053
：
Figure DEST_PATH_IMAGE054
Wherein the content of the first and second substances,
n is used to indicate the number of all base stations.
Steps S23-S24, sequentially determining the received signal strength and the mean value of each signal
Figure 642893DEST_PATH_IMAGE048
Whether the difference is greater than the coefficient
Figure 584304DEST_PATH_IMAGE053
And standard deviation of
Figure 556808DEST_PATH_IMAGE051
And according to the judgment result, the corresponding signal receiving strength is screened out or reserved, namely the signal receiving strength of the q-th base station meets the requirement
Figure 950880DEST_PATH_IMAGE055
If not, all the signal receiving strength after screening is expressed as
Figure DEST_PATH_IMAGE056
,
Figure 519396DEST_PATH_IMAGE057
,⋯
Figure DEST_PATH_IMAGE058
。
Step S25, according to the filtered signal receiving strength, expressing as
Figure 784155DEST_PATH_IMAGE056
,
Figure 927560DEST_PATH_IMAGE057
,⋯
Figure 808929DEST_PATH_IMAGE058
Screening and signal receiving strength
Figure 571348DEST_PATH_IMAGE056
,
Figure 88350DEST_PATH_IMAGE057
,⋯
Figure 12443DEST_PATH_IMAGE058
Corresponding azimuth angle
Figure 505742DEST_PATH_IMAGE059
,
Figure DEST_PATH_IMAGE060
,⋯
Figure 540694DEST_PATH_IMAGE061
And a pitch angle
Figure DEST_PATH_IMAGE062
,
Figure 920991DEST_PATH_IMAGE063
,⋯
Figure DEST_PATH_IMAGE064
。
Further, in step S2, different filtering rules may be preset, and different filtering is performed on the spatial spectrum peak, the azimuth angle, and the pitch angle according to the different filtering rules. Specifically, in the screening process, the grubbs criterion construction step S2 may be further applied to obtain the spatial spectrum peak value, the azimuth angle and the pitch angle after the screening.
In a preferred embodiment of the present invention, as shown in fig. 5, step S3 includes:
step S31, acquiring the position information of all base stations;
step S32, respectively acquiring a first tangent value and a second tangent value according to the position information of each base station and the azimuth angle and the pitch angle of the signals received by the base stations, and respectively constructing a first matrix and a second matrix according to the position information, the first tangent value and the second tangent value;
step S33, acquiring a corresponding weight matrix according to the spatial spectrum peak of each base station received signal;
in step S34, a first predicted position is obtained according to the first matrix, the second matrix and the weight matrix.
In a preferred embodiment of the present invention, the first tangent value and the second tangent value are expressed by the following formulas:
Figure 609461DEST_PATH_IMAGE065
wherein the content of the first and second substances,
Figure DEST_PATH_IMAGE066
for representing the qth first tangent value, where q is used to represent the base station's ranking number among all base stations,
Figure 199842DEST_PATH_IMAGE067
for indicating the azimuth angle of the q base station receiving signal;
Figure DEST_PATH_IMAGE068
for representing a second tangent value, wherein
Figure 913851DEST_PATH_IMAGE069
A pitch angle for representing a signal received by the q-th base station;
x is used to represent the abscissa in a first predicted location of the signal;
Figure DEST_PATH_IMAGE070
an abscissa for representing position information of the q-th base station;
y is used to represent the ordinate in a first predicted position of the signal;
Figure 132343DEST_PATH_IMAGE071
an ordinate in the position information for representing the q-th base station;
z is used to represent the vertical coordinate in a first predicted location of the signal;
Figure DEST_PATH_IMAGE072
for indicating the vertical coordinates in the location information of the q-th base station.
Considering the position information, the acquired signal reception strength, the azimuth angle, and the pitch angle for only one base station, a numerical relationship with the first predicted position may be constructed:
Figure 742447DEST_PATH_IMAGE073
and (3) sorting to obtain a first predicted position:
Figure DEST_PATH_IMAGE074
thus, from the position information of the plurality of base stations, the acquired signal reception strength, the azimuth angle, and the pitch angle, a numerical relationship with the first predicted position can be constructed:
Figure 820125DEST_PATH_IMAGE075
wherein the content of the first and second substances,
h is used to represent a first predicted position;
m is used to represent a first matrix;
w is used to represent a weight matrix;
n is used to represent the second matrix.
Specifically, the first matrix is represented by the following formula:
Figure DEST_PATH_IMAGE076
wherein the content of the first and second substances,
Figure 321513DEST_PATH_IMAGE077
for representing the qth first tangent value, where q is used to represent the base station's ranking number among all base stations,
Figure DEST_PATH_IMAGE078
for indicating the azimuth angle of the q base station receiving signal;
Figure 407893DEST_PATH_IMAGE079
for representing a second tangent value, wherein
Figure DEST_PATH_IMAGE080
A pitch angle for representing a signal received by the q-th base station;
l is used to indicate the number after screening.
Specifically, the second matrix is represented by the following formula:
Figure 579112DEST_PATH_IMAGE081
wherein the content of the first and second substances,
Figure DEST_PATH_IMAGE082
for representing the qth first tangent value, where q is used to represent the base station's ranking number among all base stations,
Figure 3140DEST_PATH_IMAGE083
for indicating the azimuth angle of the q base station receiving signal;
Figure DEST_PATH_IMAGE084
for representing a second tangent value, wherein
Figure 58952DEST_PATH_IMAGE085
A pitch angle for representing a signal received by the q-th base station;
x is used to represent the abscissa in a first predicted location of the signal;
Figure DEST_PATH_IMAGE086
an abscissa for representing position information of the q-th base station;
y is used to represent the ordinate in a first predicted position of the signal;
Figure 986456DEST_PATH_IMAGE087
an ordinate in the position information for representing the q-th base station;
z is used to represent the vertical coordinate in a first predicted location of the signal;
Figure DEST_PATH_IMAGE088
a vertical coordinate for representing the location information of the q-th base station;
l is used to indicate the number after screening.
Specifically, the weight matrix is represented as:
Figure 594155DEST_PATH_IMAGE089
wherein the content of the first and second substances,
Figure DEST_PATH_IMAGE090
is used for representing the q weight, wherein q is used for representing the sequence number of the base station in all the base stations;
Figure 256212DEST_PATH_IMAGE091
the numbers after screening are indicated.
In a preferred embodiment of the invention, the weights are expressed as:
Figure DEST_PATH_IMAGE092
wherein the content of the first and second substances,
Figure 833824DEST_PATH_IMAGE093
is used for representing the q weight, wherein q is used for representing the sequence number of the base station in all the base stations;
Figure DEST_PATH_IMAGE094
spatial spectrum peaks representing the q base station received signal;
l is used to indicate the number after screening.
In this regard, considering that the accuracy of the azimuth angle and the pitch angle of the received signal of the base station obtained through the spatial spectrum search decreases with the increase of the distance between the signal emission source and the base station, the weight of the base station is determined according to the spatial spectrum peak value of the received signal of each base station and a weight matrix is constructed, so that the ratio of the spatial spectrum peak value, the azimuth angle and the pitch angle corresponding to different base stations is different in the process of obtaining the first predicted position, and the influence of the insufficiently accurate azimuth angle and pitch angle on the first predicted position is avoided.
In a preferred embodiment of the present invention, as shown in fig. 6, step S4 includes:
step S41, constructing a prediction state equation, and obtaining a second prediction position at the current moment according to the real-time positioning result at the previous moment and the prediction state equation;
and step S42, determining the real-time positioning result of the current time according to the first predicted position and the second predicted position.
Specifically, the first predicted position at the current time can be obtained according to the steps S1-S3, and in the real-time obtaining process, the position of the signal emission source changes, and the change speed and the change path are different, and the first predicted positions obtained by the plurality of base stations are likely to be interfered to generate errors, so that step S4 is set, and the real-time positioning result at the current time is obtained according to the real-time positioning result at the previous time and the first predicted position obtained in step S3 through comprehensive analysis.
Step S41, a prediction state equation is constructed, and a second prediction position at the current time is obtained according to the real-time positioning result at the previous time and the prediction state equation:
Figure 22360DEST_PATH_IMAGE095
wherein the content of the first and second substances,
Figure DEST_PATH_IMAGE096
for indicating a second predicted position of the current time, whichIn
Figure 410747DEST_PATH_IMAGE097
For representing the current time;
Figure DEST_PATH_IMAGE098
the system is used for representing the real-time positioning result at the previous moment;
Figure 74946DEST_PATH_IMAGE099
for representing
Figure DEST_PATH_IMAGE100
A transformation matrix under a state, namely a basis for predicting a variable with a changed position;
Figure 944332DEST_PATH_IMAGE101
for representing the transformation matrix, in most cases without control gain;
Figure DEST_PATH_IMAGE102
the control gain for indicating the current time is generally set to 0.
Step S42, determining a real-time positioning result of the current time according to the first predicted position and the second predicted position, which may include:
in step S421, the covariance of the current time is obtained according to the covariance of the previous time, and can be represented by the following formula:
Figure 252953DEST_PATH_IMAGE103
wherein the content of the first and second substances,
Figure DEST_PATH_IMAGE104
a covariance matrix for representing a current time, wherein K is used to represent the current time;
Figure 61509DEST_PATH_IMAGE105
for representing the covariance of the previous time instant, wherein
Figure DEST_PATH_IMAGE106
For representing the current time;
Figure 432579DEST_PATH_IMAGE107
the covariance used to represent the noise can be set according to the actual situation.
Step S422, acquiring kalman gain according to the covariance of the current time, which may be expressed by the following formula:
Figure DEST_PATH_IMAGE108
wherein the content of the first and second substances,
Figure 492939DEST_PATH_IMAGE109
for representing a kalman gain;
Figure DEST_PATH_IMAGE110
for representing observation matrices, i.e. different types of position variations of the signal emission sources, such as linear variations, or non-linear variations, along a straight line;
Figure 515122DEST_PATH_IMAGE111
the covariance matrix used for representing the observation noise can be regarded as the observation mean value and can be configured according to the actual situation.
Step S423, obtaining a real-time positioning result of the current time according to the first predicted position, the second predicted position and the kalman gain, and using the following formula to represent:
Figure DEST_PATH_IMAGE112
wherein the content of the first and second substances,
Figure 245311DEST_PATH_IMAGE113
the real-time positioning result is used for representing the current moment;
Figure DEST_PATH_IMAGE114
for representing the first predicted position.
In addition, a process of updating the covariance equation may be included, and the covariance at the current time is obtained according to step S42, which may be expressed by the following formula:
Figure 618524DEST_PATH_IMAGE115
accordingly, a second predicted position at the next time can be obtained according to the covariance at the current time and the real-time positioning result.
A multi-base station real-time positioning system, as shown in fig. 7, is applied to a plurality of base stations 1,2 ⋯ q ⋯, n, all of which receive a signal synchronously; the multi-base station real-time positioning system comprises:
an obtaining module a1, configured to obtain signal receiving intensities, azimuth angles, pitch angles, and spatial spectrum peak values of all base station received signals at the current time;
the screening module A2 is connected with the acquisition module A1 and is used for screening the signal receiving intensity, the azimuth angle, the pitch angle and the spatial spectrum peak value;
the prediction module A3 is connected with the screening module A2 and is used for performing combined positioning according to the screened signal receiving intensity, azimuth angle, pitch angle and spatial spectrum peak value to obtain a first prediction position of the signal at the current moment;
and the filtering module A4 is connected to the predicting module A3 and is used for determining a second predicted position at the current moment according to the real-time positioning result at the previous moment and determining the real-time positioning result at the current moment according to the first predicted position and the second predicted position.
Specifically, in view of the fact that the prior art cannot accurately perform indoor real-time positioning, a multi-base-station real-time positioning system is provided, which is applied to a plurality of base stations, analyzes a first predicted position of a signal emission source, and obtains a real-time positioning result according to filtering, specifically, the real-time positioning method is clear from the above description, and the real-time positioning result is determined and then output through an output module a 5.
The first embodiment is as follows:
when a signal transmitting end is arranged at a fixed position of a space coordinate (20, 30, 25), three base stations are adopted for joint positioning, wherein the distance between one base station and the signal transmitting end is far compared with the distance between the other two base stations, and when the pitch angle and the azimuth angle obtained by the base station are not accurate enough, the final positioning result is as follows:
means for Positioning result
Comparative example 1: considering only pitch and azimuth （21.6，26.8，24.7）
Comparative example 2: considering only the signal reception strength （16.2，39.1，30.4）
The invention （19.8，29.6，25.0）
As can be seen from the table, through steps S1-S4 of the present invention, joint positioning is performed according to the filtered signal received strength, azimuth angle, pitch angle and spatial spectrum peak value, and the numerical value of the signal received strength is used as a basis for determining the accuracy of the azimuth angle and pitch angle, so as to screen out the azimuth angle and pitch angle which are not accurate enough and may cause erroneous judgment, and the finally determined real-time positioning result is (19.8, 296, 25.0). In comparative example 1, only the pitch angle and the azimuth angle are considered, or in comparative example 2, only the signal receiving strength is considered, and the positioning result obtained by adopting the method is closest to the correct position. Furthermore, even when the positioning results of comparative examples 1 and 2 are combined, the maximum value, the minimum value or the average value cannot be obtained, so that more accurate positioning results than those of the present invention cannot be obtained.
Example two:
when a signal transmitting end is arranged at a fixed position of a space coordinate (5, 15, 20), three base stations are adopted for joint positioning, wherein the distance between one base station and the signal transmitting end is far compared with the distance between the other two base stations, and when the pitch angle and the azimuth angle obtained by the base station are not accurate enough, the final positioning result is as follows:
means for Positioning result
All base stations adopt the same weight （5.8，13.1，15.9）
Setting different weights by signal strength （4.7，14.2，16.4）
The invention （4.9,14.3,18.9）
It can be seen from the table that the present invention determines the weight of the base station according to the spatial spectrum peak of the received signal of each base station, so that the numerical ratios of the received signal strength, the azimuth angle and the pitch angle of different base stations are different, and the finally determined real-time positioning result is (4.9, 14.3, 18.9). The method comprises the steps that the numerical value occupation ratios of the signal receiving strength, the azimuth angle and the pitch angle corresponding to different base stations are the same, the finally determined real-time positioning result is (5.8, 13.1, 15.9), and when the numerical value occupation ratios of the signal receiving strength, the azimuth angle and the pitch angle corresponding to different base stations are determined by the weight values corresponding to the signal receiving strength, the finally determined real-time positioning result is (4.7, 14.2, 16.4).
The technical scheme has the following advantages or beneficial effects: the method and the system are applied to a plurality of base stations, azimuth angles and pitch angles which are not accurate enough and possibly cause misjudgment are screened out, and real-time positioning results of signals are obtained according to the screened signal receiving intensity, the screened azimuth angles and the screened pitch angles.
While the invention has been described with reference to a preferred embodiment, it will be understood by those skilled in the art that various changes in form and detail may be made therein without departing from the spirit and scope of the invention.

Claims (12)

1. A multi-base station real-time positioning method based on Bluetooth signals is applied to a plurality of base stations and is characterized in that all the base stations synchronously receive signals; the multi-base-station real-time positioning method comprises the following steps:
step S1, acquiring the signal receiving intensity, azimuth angle, pitch angle and spatial spectrum peak value of the signal received by all the base stations at the current moment;
step S2, screening the signal reception intensity, the azimuth angle, the pitch angle, and the spatial spectrum peak;
step S3, performing combined positioning according to the filtered signal receiving intensity, the azimuth angle, the pitch angle and the spatial spectrum peak value to obtain a first predicted position of the signal at the current moment;
step S4, determining a second predicted position of the current time according to the real-time positioning result of the previous time, and determining the real-time positioning result of the current time according to the first predicted position and the second predicted position.
2. The multi-base-station real-time positioning method according to claim 1, wherein said step S1 includes:
step S11, acquiring the signal received by the base station at the current time;
step S12, acquiring the corresponding signal receiving strength according to the energy in the signal;
step S13, obtaining a corresponding spatial spectrum according to orthogonality between the noise subspace in the signal and the array manifold vector, performing peak search on the spatial spectrum to obtain a spatial spectrum peak value and a corresponding angle, and using the corresponding angle as the azimuth angle and the pitch angle at which the base station receives the signal.
3. The multi-base-station real-time positioning method according to claim 1, wherein said step S2 includes:
step S21, obtaining a mean value and a standard deviation of the signal reception intensity at the current time;
step S22, presetting a coefficient;
step S23, sequentially determining whether the difference between the received signal strength and the mean is greater than the product of the coefficient and the standard deviation:
if yes, the signal reception strength is screened out, and then the step S24 is carried out;
if not, the signal receiving strength is retained, and then the step S24 is carried out;
step S24, determining whether all the signal reception intensities have been filtered:
if yes, go to step S25;
if not, returning to the step S23;
step S25, screening the azimuth angle, the pitch angle, and the spatial spectrum peak corresponding to the signal reception intensity according to the screened signal reception intensity.
4. The multi-base-station real-time positioning method according to claim 1, wherein said step S3 includes:
step S31, acquiring the position information of all the base stations;
step S32, sequentially obtaining a first tangent value and a second tangent value according to the position information of each base station and the azimuth angle and the pitch angle at which the base station receives the signal, and respectively constructing a first matrix and a second matrix according to the position information, the first tangent value and the second tangent value;
step S33, obtaining a corresponding weight matrix according to the spatial spectrum peak value of the signal received by each base station;
step S34, obtaining the first predicted position according to the first matrix, the second matrix and the weight matrix.
5. A multi-base-station real-time positioning method as claimed in claim 4, wherein said first tangent value and said second tangent value are expressed by the following formulas:
Figure DEST_PATH_IMAGE001
wherein the content of the first and second substances,
Figure 657608DEST_PATH_IMAGE002
for representing the qth of said first tangent, where q is used to represent the ranking number of said base station among all base stations,
Figure DEST_PATH_IMAGE003
for indicating the azimuth angle at which the q-th base station receives the signal;
Figure 534297DEST_PATH_IMAGE004
for representing the second tangent value, wherein
Figure DEST_PATH_IMAGE005
Said pitch angle representing the reception of said signal by the qth of said base station;
x is used to represent the abscissa in a first predicted position of the signal;
Figure 700968DEST_PATH_IMAGE006
an abscissa for representing position information of the q-th base station;
y is used to represent the ordinate in a first predicted position of the signal;
Figure DEST_PATH_IMAGE007
an ordinate in the position information for representing the q-th base station;
z is used to represent the vertical coordinate in a first predicted location of the signal;
Figure 295897DEST_PATH_IMAGE008
for representing the vertical coordinate in the location information of the q-th base station.
6. The multi-base-station real-time positioning method according to claim 4, wherein the first matrix is expressed by the following formula:
Figure DEST_PATH_IMAGE009
wherein the content of the first and second substances,
Figure 698060DEST_PATH_IMAGE010
for representing the qth of said first tangent, where q is used to represent the ranking number of said base station among all base stations,
Figure DEST_PATH_IMAGE011
for indicating the azimuth angle at which the q-th base station receives the signal;
Figure 177058DEST_PATH_IMAGE012
for representing the second tangent value, wherein
Figure DEST_PATH_IMAGE013
Said pitch angle representing the reception of said signal by the qth of said base station;
l is used to indicate the number after screening.
7. The multi-base-station real-time positioning method according to claim 4, wherein the second matrix is expressed by the following formula:
Figure 763897DEST_PATH_IMAGE014
wherein the content of the first and second substances,
Figure DEST_PATH_IMAGE015
for representing the qth of said first tangent, where q is used to represent the ranking number of said base station among all base stations,
Figure 987068DEST_PATH_IMAGE016
for indicating the azimuth angle at which the q-th base station receives the signal;
Figure DEST_PATH_IMAGE017
for representing the second tangent value, wherein
Figure 802708DEST_PATH_IMAGE018
Said pitch angle representing the reception of said signal by the qth of said base station;
x is used to represent the abscissa in a first predicted position of the signal;
Figure DEST_PATH_IMAGE019
an abscissa for representing position information of the q-th base station;
y is used to represent the ordinate in a first predicted position of the signal;
Figure 388411DEST_PATH_IMAGE020
an ordinate in the position information for representing the q-th base station;
z is used to represent the vertical coordinate in a first predicted location of the signal;
Figure DEST_PATH_IMAGE021
a vertical coordinate for representing position information of the q-th base station;
l is used to indicate the number after screening.
8. The multi-base-station real-time positioning method according to claim 4, wherein the weight is expressed as:
Figure 896883DEST_PATH_IMAGE022
wherein the content of the first and second substances,
Figure DEST_PATH_IMAGE023
is used for representing the q-th weight, wherein q is used for representing the sequence number of the base station in all the base stations;
Figure 341771DEST_PATH_IMAGE024
the spatial spectrum peak used for representing the q base station receiving the signal;
l is used to indicate the number after screening.
9. The multi-base-station real-time positioning method according to claim 4, wherein the weight matrix is expressed as:
Figure DEST_PATH_IMAGE025
wherein the content of the first and second substances,
Figure 210370DEST_PATH_IMAGE026
is used for representing the q-th weight, wherein q is used for representing the sequence number of the base station in all the base stations;
Figure DEST_PATH_IMAGE027
the numbers after screening are indicated.
10. The multi-base-station real-time positioning method according to claim 4, wherein the first predicted position is expressed by the following formula:
Figure 932470DEST_PATH_IMAGE028
wherein the content of the first and second substances,
Figure DEST_PATH_IMAGE029
the first predicted position is used for representing the current time, wherein K is used for representing the current time;
m is used to represent the first matrix;
w is used to represent the weight matrix;
n is used to represent the second matrix.
11. The multi-base-station real-time positioning method according to claim 1, wherein said step S4 includes:
step S41, constructing a prediction state equation, and obtaining a second prediction position of the current time according to the real-time positioning result of the previous time and the prediction state equation;
step S42, determining the real-time positioning result of the current time according to the first predicted position and the second predicted position.
12. A multi-base station real-time positioning system based on Bluetooth signals is applied to a plurality of base stations and is characterized in that all the base stations synchronously receive a signal; the multi-base-station real-time positioning system comprises:
the acquisition module is used for acquiring the signal receiving intensity, azimuth angle, pitch angle and spatial spectrum peak value of the signals received by all the base stations at the current moment;
the screening module is connected with the acquisition module and is used for screening the signal receiving intensity, the azimuth angle, the pitch angle and the spatial spectrum peak value;
the prediction module is connected with the screening module and used for carrying out combined positioning according to the screened signal receiving intensity, the azimuth angle, the pitch angle and the spatial spectrum peak value to obtain a first prediction position of the signal at the current moment;
and the filtering module is connected with the prediction module and used for determining a second prediction position of the current moment according to a real-time positioning result of the previous moment and determining a real-time positioning result of the current moment according to the first prediction position and the second prediction position.
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