CN102625443A - Method and device for positioning terminal - Google Patents

Abstract

The invention discloses a method and a device for positioning a terminal, wherein the method comprises the steps of: for any cell, setting a first preset number of clustering terminals in a cell, acquiring position data of each clustering terminal: angle of arrival AOA, time of arrival TOA, signal to noise ratio SNR and the physical coordinate, and inputting the position data of each clustering terminal into a historical data base; for any terminal to be positioned, measuring the AOA, the TOA and the SNR of the terminal, based on the AOA, the TOA and the SNR of the terminal to be positioned, searching the historical database for a clustering terminal which matches best to the terminal to be positioned, and determining an initial estimate position of the terminal to be positioned based on the physical coordinate of the clustering terminal; calculating the final position of the terminal to be positioned based on the initial estimate position of the terminal to be positioned and the distance between the terminal to be positioned and other terminals to be positioned. According to the invention, only one base station is needed for positioning a terminal.

Description

Method of locating terminal and device

Technical field

The present invention relates to field of locating technology, be specifically related to method of locating terminal and device.

Background technology

Along with the development of mobile communication, the mobile location service in the GSM more and more receives publicity.3 kinds of localization methods commonly used are arranged at present:

1, based on the localization method of time measurement, as: the time of advent (TOA, Time of Arrival) method, the time of advent poor (TDOA, Time Different Of Arrival) method.Main through the propagation time of detection electric wave from transmitted from transmitter to receiver, calculate the distance of the two, and then through calculating the estimated position of travelling carriage someway.

2, the signal angle of arrival (AOA; Angle of Arrival) method: the AOA that detects travelling carriage emission electric wave through the base station receiver aerial array; This AOA can constitute a radially line from the base station to the travelling carriage, i.e. rhumb line, the AOA measured value that utilizes a plurality of base stations to provide; Many the rhumb line of can drawing, its intersection point is exactly the estimated position of travelling carriage.

3, auxiliary global satellite positioning system (AGPS, Assisted Global Positioning System) positioning mode: a kind of technology that has combined network base station information and GPS information that travelling carriage is positioned.The GPS supplementary that travelling carriage utilizes network to provide receives the GPS primary signal; Obtain GPS pseudorange information through demodulation to primary signal; The supplementary of network based pseudorange information and other positioning equipment is accomplished the GPS information processing, and the position of estimation travelling carriage.

The shortcoming of prior art is following:

Localization method based on time measurement: its positioning accuracy receives the influence of system's timing accuracy, and necessary strict synchronism between the base station cause tangible influence can not for the location result with the timing error of guaranteeing system itself; And the terminal must minimumly be observed three base station signals and could locate.

The signal angle of arrival (AOA) method: the location just can be realized in two base stations, but the base station needs receiving antenna array, and precision receives channel effect bigger, the location difficulty in the building compact district.

The AGPS positioning mode: for positioning requirements receives the signal of four satellites at least, between intensive urban district high building, in building and any area that can only see 4 following satellites, gps system is generally inoperative, can't realize accurate localization.

Summary of the invention

The present invention provides method of locating terminal and device, only needs a base station just can realize the location to the terminal to reach.

Technical scheme of the present invention is achieved in that

A kind of method of locating terminal, this method comprises:

For arbitrary sub-district; First preset number cluster terminal is set in the sub-district; Obtain the position data at each cluster terminal: angle of arrival AOA, the time of advent TOA, signal to noise ratio snr and physical coordinates, the position data at each cluster terminal is put into historical data base;

For arbitrary terminal to be measured; Measure AOA, TOA and the SNR at this terminal to be measured; According to AOA, TOA and the SNR at this terminal to be measured, in historical data base, search the cluster terminal of mating most with this terminal to be measured, confirm the initial estimated location at this terminal to be measured according to the physical coordinates at this cluster terminal;

According to the initial estimated location at terminal to be measured and the distance between this terminal to be measured and other terminal to be measured, calculate the final position at this terminal to be measured.

Said first preset number cluster terminal that in the sub-district, is provided with, obtain the position data at each cluster terminal: angle of arrival AOA, the time of advent TOA, signal to noise ratio snr and physical coordinates,, the position data at each cluster terminal is put into historical data base comprises:

First preset number initial clustering terminal is set in the sub-district, and second preset number sample terminal is set;

Distance according to sample terminal and cluster terminal; Cluster is carried out at all sample terminals; Cluster is accomplished; Obtain first a preset number new cluster terminal, calculate the position data at each new cluster terminal: AOA, TOA, SNR and physical coordinates, the position data at each new cluster terminal is put into historical data base.

Said distance according to sample terminal and cluster terminal, cluster is carried out at all sample terminals comprise:

The initialization iterations is 0;

For each sample terminal; Seek and nearest cluster terminal, this sample terminal; With this sample terminal attaching in this cluster terminal; All sample terminals that belong to same cluster terminal as a cluster crowd, as a new cluster terminal, are calculated the mean square error of the physical coordinates at the physical coordinates at all new cluster terminals that current iteration obtains and all cluster terminals that last iteration obtains with each cluster crowd's barycenter; If mean square error, is then confirmed cluster less than preset value and is accomplished; Otherwise it is said for each sample terminal to return execution, the action at the cluster terminal that searching and this sample terminal are nearest.

Said first preset number initial clustering terminal that in the sub-district, is provided with is:

The sub-district evenly is divided into the first preset number sub regions, with the center of each subregion as position, an initial clustering terminal.

Further comprise after the final position at this terminal to be measured of said calculating:

Behind the final position that calculates this terminal to be measured; With this terminal to be measured as new sample terminal; Carry out cluster with existing sample terminal, cluster is accomplished, and with the position data at each new cluster terminal of obtaining: AOA, TOA, SNR and physical coordinates upgrade historical data base.

AOA, TOA and the SNR at this terminal to be measured of said basis, search the cluster terminal of mating most with this terminal to be measured and comprise in historical data base:

According to AOA, TOA and the SNR at this terminal to be measured, in historical data base, search and the minimum cluster terminal of the Euclidean distance at this terminal to be measured;

Said physical coordinates according to this cluster terminal confirms that the initial estimated location at this terminal to be measured is:

Calculate the difference α of AOA at AOA and the said cluster terminal at said terminal to be measured, with the physical coordinates rotation alpha at this cluster terminal, with the initial estimated location of the physical coordinates that obtains after the rotation as said terminal to be measured.

Said according to the initial estimated location at terminal to be measured and the distance between this terminal to be measured and other terminal to be measured, the final position of calculating this terminal to be measured further comprises before:

Calculate the distance between said terminal to be measured and arbitrary other terminal to be measured through following steps:

Calculate β=AOA _i-AOA _k, wherein, AOA _iBe the AOA at said terminal to be measured, AOA _kAOA for said arbitrary other terminal to be measured;

Calculate the distance of said terminal to be measured and base station

Calculate the distance of said arbitrary other terminal to be measured and base station

Wherein,

For according to SNR _iThe terminal said to be measured that calculates and the distance of base station,

For according to TOA _iThe terminal said to be measured that calculates and the distance of base station,

For according to SNR _kSaid arbitrary other terminal to be measured that calculates and the distance of base station,

For according to TOA _kSaid arbitrary other terminal to be measured that calculates and the distance of base station, SNR _iBe the SNR at said terminal to be measured, TOA _iBe the TOA at said terminal to be measured, SNR _kBe the SNR at said arbitrary other terminal to be measured, TOA _kTOA for said arbitrary other terminal to be measured;

Calculate said terminal to be measured and said arbitrary other terminal room to be measured apart from d _Ik:

$d_{\mathrm{ik}}=\sqrt{d_i^2+d_k^2-{2d}_i{d}_k\·\cos \mathrm{\β}}.$

Said according to the initial estimated location at terminal to be measured and the distance between this terminal to be measured and other terminal to be measured, the final position of calculating this terminal to be measured comprises:

If it is the two-dimentional Gaussian distribution at center that the position distribution at said terminal to be measured is obeyed with the initial estimated location, then confirm the initial position probability distribution at this terminal to be measured according to the initial estimated location at said terminal to be measured;

The initialization iterations is 0;

According to the distance between said terminal to be measured and arbitrary other terminal to be measured, calculate in this iterative process arbitrary other terminal to be measured to the updating value of the position probability distribution at said terminal to be measured;

To the updating value of the position probability distribution at said terminal to be measured, obtain the latest position probability distribution at said terminal to be measured according to other terminal to be measured in the initial position probability distribution at said terminal to be measured and this iterative process;

Whether judge iterations less than pre-determined number, if return and carry out in this iterative process of said calculating arbitrary other terminal to be measured the action of the updating value of the position probability distribution at said terminal to be measured is continued the next iteration process; Otherwise, the latest position probability distribution at terminal to be measured as its final position probability distribution, is calculated the final position at said terminal to be measured according to this final position probability distribution.

Arbitrary other terminal to be measured to the updating value of the position probability distribution at said terminal to be measured is in this iterative process of said calculating:

Calculate $u_{k\→i}^{\left(q\right)}(x,y)=\underset{s,t}{\mathrm{\Σ}}p\left(d_{\mathrm{Ik}}\right|(x,y),(s,t))\·b_k^{(q-1)}(s,t)$

Wherein, K is the sequence number at arbitrary other terminal to be measured; I is the sequence number at said terminal to be measured; Q is the current iteration number of times; be in this iterative process arbitrary other terminal k to be measured to the updating value of the position probability distribution of said terminal i to be measured; (s; T) be the physical coordinates of arbitrary other terminal k to be measured,

be the position probability distribution of arbitrary other terminal k to be measured after last once iteration;

$p\left(d_{\mathrm{ik}}\right|(x,y),(s,t))=\frac{1}{{2\mathrm{\π\σ}}^2}\exp \{-\frac{{(d_{\mathrm{ik}}-\sqrt{{(x-s)}^2+{(y-t)}^2})}^2}{{2\mathrm{\σ}}^2}\}$

The physical significance of this formula is: (in s, t) last time,, said terminal i to be measured was at physical location (x, the probability on y) at physical location as said arbitrary other terminal k to be measured; d _IkBe the distance between said arbitrary other terminal k to be measured and said terminal i to be measured;

Other terminal to be measured is to the updating value of the position probability distribution at said terminal to be measured in said initial position probability distribution and this iterative process according to said terminal to be measured, and the latest position probability distribution that obtains said terminal to be measured is:

Wherein, p _i(x y) is the initial position probability distribution at said terminal to be measured;

Said final position

of calculating said terminal to be measured according to this final position probability distribution is:

${\hat{x}}_i=\underset{x,y}{\mathrm{\Σ}}x\·P_i^{\′}(x,y)$

${\hat{y}}_i=\underset{x,y}{\mathrm{\Σ}}y\·P_i^{\′}(x,y)$

Wherein,

(x, span y) is the overlay area of sub-district.

A kind of terminal positioning device, this device comprises:

First module: for arbitrary sub-district; First preset number cluster terminal is set in the sub-district; Obtain the position data at each cluster terminal: angle of arrival AOA, the time of advent TOA, signal to noise ratio snr and physical coordinates, the position data at each cluster terminal is put into historical data base;

Unit second: for arbitrary terminal to be measured; Measure AOA, TOA and the SNR at this terminal to be measured; AOA, TOA and SNR according to this terminal to be measured; In historical data base, search the cluster terminal of mating most with this terminal to be measured, confirm the initial estimated location at this terminal to be measured, the initial estimated location at this terminal to be measured is sent to Unit the 3rd according to the physical coordinates at this cluster terminal;

Unit the 3rd:, calculate the final position at this terminal to be measured according to the initial estimated location at terminal to be measured and the distance between this terminal to be measured and other terminal to be measured.

Said first module comprises:

First module: first preset number initial clustering terminal is set in the sub-district, and second preset number sample terminal is set;

Second module: the initialization iterations is 0; For each sample terminal; Seek and nearest cluster terminal, this sample terminal; With this sample terminal attaching in this cluster terminal; All sample terminals that belong to same cluster terminal as a cluster crowd, as a new cluster terminal, are calculated the mean square error of the physical coordinates at the physical coordinates at all new cluster terminals that current iteration obtains and all cluster terminals that last iteration obtains with each cluster crowd's barycenter; If mean square error, is then confirmed cluster less than preset value and is accomplished; Otherwise it is said for each sample terminal to return execution, the action at the cluster terminal that searching and this sample terminal are nearest.

Said Unit the 3rd is further used for, and behind the final position that calculates this terminal to be measured, the position data at this terminal to be measured: AOA, TOA, SNR and physical coordinates is sent to first module;

After said first module receives the position data at said terminal to be measured; With this terminal to be measured as new sample terminal; Again cluster is carried out at all sample terminals, cluster is accomplished, and with the position data at each new cluster terminal of obtaining: AOA, TOA, SNR and physical coordinates upgrade historical data base.

Said Unit second comprises:

Three module:, measure AOA, TOA and the SNR at this terminal to be measured for arbitrary terminal to be measured;

Four module: according to AOA, TOA and the SNR at this terminal to be measured; In historical data base, search and the minimum cluster terminal of the Euclidean distance at this terminal to be measured; Calculate the difference α of AOA at AOA and the said cluster terminal at said terminal to be measured; With the physical coordinates rotation alpha at this cluster terminal, with the initial estimated location of the physical coordinates that obtains after the rotation as said terminal to be measured.

Said Unit the 3rd comprises:

The 5th module: calculate the distance of said terminal to be measured and arbitrary other terminal room to be measured, each distance that calculates is sent to the 6th module;

The 6th module: the position distribution obedience of establishing said terminal to be measured is the two-dimentional Gaussian distribution at center with the initial estimated location, then confirms the initial position probability distribution at this terminal to be measured according to the initial estimated location at said terminal to be measured; Initialization number of times repeatly is 0; According to the distance of said terminal to be measured and arbitrary other terminal room to be measured, calculate in this iterative process arbitrary other terminal to be measured to the updating value of the position probability distribution at said terminal to be measured; To the updating value of the position probability distribution at said terminal to be measured, obtain the latest position probability distribution at said terminal to be measured according to other terminal to be measured in the initial position probability distribution at said terminal to be measured and this iterative process; Whether judge iterations less than pre-determined number, if return and carry out in this iterative process of said calculating arbitrary other terminal to be measured the action of the updating value of the position probability distribution at said terminal to be measured is continued the next iteration process; Otherwise, the latest position probability distribution at terminal to be measured as its final position probability distribution, is calculated the final position at said terminal to be measured according to this final position probability distribution.

Said the 5th module comprises:

First submodule: calculate β=AOA _i-AOA _k, wherein, AOA _iBe the AOA at said terminal to be measured, AOA _kBe the AOA at said arbitrary other terminal to be measured, β is sent to the 3rd submodule;

Second submodule: the distance of calculating said terminal to be measured and base station Calculate the distance of said arbitrary other terminal to be measured and base station Wherein,

For according to SNR _iThe terminal said to be measured that calculates and the distance of base station,

For according to TOA _iThe terminal said to be measured that calculates and the distance of base station,

For according to SNR _kSaid arbitrary other terminal to be measured that calculates and the distance of base station,

For according to TOA _kSaid arbitrary other terminal to be measured that calculates and the distance of base station are with d _i, d _kSend to the 3rd submodule;

The 3rd submodule: calculate said terminal to be measured and said arbitrary other terminal room to be measured apart from d _Ik:

$d_{\mathrm{ik}}=\sqrt{d_i^2+d_k^2-{2d}_i{d}_k\·\cos \mathrm{\β}}.$

Said device is positioned on the base station.

Compared with prior art, among the present invention, need not a plurality of base stations and work in coordination with, only need a base station measurement to obtain AOA, TOA and the SNR at terminal to be measured, just can realize location the terminal; And, in the one-time positioning process, can realize location simultaneously to a plurality of terminals; And, do not need the outer supplemental characteristic of existing protocol, just can realize location to the terminal, have compatibility and usability preferably.

Description of drawings

The method of locating terminal flow chart that Fig. 1 provides for the embodiment of the invention;

The method flow diagram of setting up historical data base that Fig. 2 provides for the embodiment of the invention;

Fig. 3 divides sketch map for the sub-district that the embodiment of the invention provides;

The sketch map of the position of the cluster point that Fig. 4 provides for the embodiment of the invention;

Fig. 5 for the embodiment of the invention provide according to the method flow diagram of historical data base to terminal positioning to be measured;

The method flow diagram of the terminal i initial estimated location definite to be measured that Fig. 6 provides for the embodiment of the invention;

The sketch map of terminal location to be measured is confirmed in the position according to coupling cluster point that Fig. 7 provides for the embodiment of the invention;

Initial estimated location and terminal to be measured distance between any two according to terminal to be measured that Fig. 8 provides for the embodiment of the invention adopt sum-product algorithm to obtain the method flow diagram of the final estimated position at terminal to be measured;

The position distribution sketch map at the terminal to be measured that Fig. 9 provides for the embodiment of the invention;

Figure 10 adopts sum-product algorithm to obtain the sketch map of the final estimated position at terminal to be measured for using the initial estimated location and the terminal to be measured distance between any two of the embodiment of the invention according to terminal to be measured;

The composition diagram of the terminal positioning device that Figure 11 provides for the embodiment of the invention.

Embodiment

The method of locating terminal flow chart that Fig. 1 provides for the embodiment of the invention, as shown in Figure 1, its concrete steps are following:

Step 101: for arbitrary sub-district; First preset number sample point is set in the sub-district; According to the position of sample point, all sample points are carried out cluster, obtain second preset number cluster point; Calculate the position data of each cluster point: AOA, TOA, SNR and physical coordinates, the position data of each cluster point is put into historical data base.

Each sample point is a portable terminal that physical coordinates is known.

Step 102: for arbitrary terminal to be measured; The AOA at this terminal to be measured of base station measurement, TOA and SNR; AOA, TOA and SNR according to this terminal to be measured; In historical data base, search the cluster point that matees most with this terminal to be measured, confirm the initial estimated location at this terminal to be measured according to the physical coordinates of this cluster point.

Step 103: calculate the distance between the terminal to be measured in twos,, calculate the final position at this terminal to be measured according to the initial estimated location at terminal to be measured and the distance between this terminal to be measured and other terminal to be measured.

Step 104: will this terminal to be measured as new sample point, carry out cluster with existing sample point, cluster is accomplished, with the position data of each cluster point of obtaining: AOA, TOA, SNR and physical coordinates renewal historical data base.

Below provide the embodiment of above-mentioned steps 101:

The method flow diagram of setting up historical data base that Fig. 2 provides for the embodiment of the invention, as shown in Figure 2, its concrete steps are following:

Step 201: for arbitrary sub-district; The base station evenly is divided into the individual zone of preset number: M (M＞1) with this sub-district; The center that each is regional is as an initial clustering point; Base station initialization iterations l=0; Write down each initial clustering point position

and, the base station is provided with a preset number sample point in this sub-district.

For example: for arbitrary sub-district; Shown in the sub-district among Fig. 30; Earlier this microzonation is divided into 6 equilateral triangles; Then each equilateral triangle is divided into 4 equilateral triangles again; Obtain 24 equilateral triangles; Again each equilateral triangle is divided into 4 equilateral triangles; Like this, this sub-district has comprised M=96 equilateral triangle altogether, with the center of each equilateral triangle in this M equilateral triangle as an initial clustering point; Obtain M initial clustering point altogether; The position of each cluster point is expressed as wherein,

the initial horizontal coordinate of j cluster point of expression,

representes the initial ordinate of j cluster point.

Step 202: for each sample point in this sub-district; Seek and the nearest cluster point of this sample point in M the cluster point that the base station obtains after last once iteration; This sample point is belonged to this cluster point; All sample points that belong to same cluster point as a cluster crowd, are obtained M cluster crowd like this, are D with each cluster group representation _j, j=0,1 ..., M-1.

Step 203: each cluster crowd's barycenter is calculated in the base station; With each barycenter as a new cluster point; Obtain M new cluster point so altogether, the position

of M new cluster point of record

Arbitrary cluster crowd D _jThe computing formula of barycenter following:

$s_j^{l+1}=\frac{1}{\mathrm{num}\left(D_j\right)}\underset{(x_i,y_i)\∈D_j}{\mathrm{\Σ}}{x}_i,$ $t_j^{l+1}=\frac{1}{\mathrm{num}\left(D_j\right)}\underset{(x_i,y_i)\∈D_j}{\mathrm{\Σ}}{y}_i$

Wherein, l+1 is the current iteration number of times, Be the abscissa of j cluster point obtaining after the current iteration,

Be the ordinate of j cluster point obtaining after the current iteration, num (D _j) be the cluster crowd D that obtains after the current iteration _jIn the number of sample point, x _iBe cluster crowd D _jIn the abscissa of i sample point, y _iBe cluster crowd D _jIn the ordinate of i sample point.

Step 204: the mean square error E of the physical coordinates of M the cluster point that obtains after the physical coordinates of M new cluster point of base station calculating and the last iteration:

$E=\frac{1}{M}\underset{j=1}{\overset{M}{\mathrm{\Σ}}}({(s_j^{l+1}-s_j^l)}^2+{(t_j^{l+1}-t_j^l)}^2)$

for the abscissa of j cluster point obtaining after the last iteration,

be the ordinate of j cluster point obtaining after the last iteration

Whether step 205: base station judges E less than predetermined threshold value, if, execution in step 206; Otherwise, return step 202, begin new round iteration promptly, the l+2 time iteration.

Step 206: the cluster completion is confirmed in the base station, according to the position of the M that obtains after dissemination channel model and a current iteration cluster point, obtains the AOA of each cluster point; TOA and SNR, with the AOA of each cluster point, TOA, SNR and physical coordinates (x; Y) as the position data of this cluster point, with (AOA, TOA; SNR, the stored in form of (x, y)) is in historical data base.

The sketch map of the position of the cluster point that Fig. 4 provides for the embodiment of the invention, as shown in Figure 4, establish base station location and be (0,0), then for arbitrary cluster point (x _r, y _r), r=0,1 ..., M-1, cluster point (x _r, y _r) AOA and TOA be:

${\mathrm{AOA}}_r=\arctan \frac{y_r}{x_r}\±\mathrm{\π}$

${\mathrm{TOA}}_r=\frac{\sqrt{x_r^2+y_r^2}}{c}$

Wherein, c is the light velocity.

Fig. 5 for the embodiment of the invention provide according to the method flow diagram of historical data base to terminal positioning to be measured, as shown in Figure 5, its concrete steps are following:

Step 501: for the terminal i arbitrary to be measured in the sub-district, the pilot signal that send according to terminal i to be measured the base station records the measuring position data AOA at this terminal _i, TOA _iAnd SNR _i, in historical data base, search and (AOA _i, TOA _i, SNR _i) position data of the cluster point s of coupling, according to the physical coordinates (x of cluster point s _s, y _s) confirm the initial estimated location (x of terminal i to be measured _Ui, y _Ui).

Step 502: the base station is according to the AOA and the TOA at each terminal to be measured of measuring, calculate between any two terminal i to be measured, the k apart from d _Ik

If the measuring position data of terminal i to be measured, k are respectively (AOA _i, TOA _i, SNR _i), (AOA _k, TOA _k, SNR _k), the distance between terminal i then to be measured, the k can obtain through following process:

Step 01: β=AOA is calculated in the base station _i-AOA _k

Step 02: the base station is calculated the distance

of terminal i to be measured and base station and is calculated the distance

of terminal k to be measured and base station according to the dissemination channel model

Wherein,

For adopting prior art according to SNR _iThe terminal i to be measured that calculates and the distance of base station,

For adopting prior art according to TOA _iThe terminal i to be measured that calculates and the distance of base station,

For adopting prior art according to SNR _kThe terminal k to be measured that calculates and the distance of base station,

For adopting prior art according to TOA _kThe terminal k to be measured that calculates and the distance of base station.

Step 03: the base station utilize the cosine law calculate between terminal i to be measured, k apart from d _Ik:

$d_{\mathrm{ik}}=\sqrt{d_i^2+d_k^2-{2d}_i{d}_k\·\cos \mathrm{\β}}$

Step 503: it is the two-dimentional Gaussian distribution at center that the position distribution of establishing each terminal to be measured all meets with the initial estimated location that obtains in the step 201; Distance between each that obtains in the integrating step 202 terminal to be measured; The base station is adopted and is amassed iterative algorithm, obtains the final estimated position at each terminal to be measured.

Below provide the embodiment of above-mentioned steps 501:

The method flow diagram of the terminal i initial estimated location definite to be measured that Fig. 6 provides for the embodiment of the invention, as shown in Figure 6, its concrete steps are following:

Step 601: establish (AOA _i, TOA _i, SNR _i) be the measuring position data of terminal i to be measured, (AOA _r, TOA _r, SNR _r, (x _r, y _r)) be the position data of r cluster point in the historical data base, the base station is according to the dissemination channel model, through SNR _iAnd TOA _iCalculate the distance of terminal i to be measured and base station

At this moment, the measuring position data of terminal i to be measured are expressed as

In the present embodiment; Measure the close degree of the position data of each cluster point in measuring position data and the historical data base of terminal i to be measured with Euclidean distance, but, can't directly calculate because the dimension of AOA, TOA, SNR is different; Therefore, unification converts each value apart from length into here.

Step 602: for arbitrary cluster point r, the base station is according to the physical coordinates (x of cluster point r _r, y _r), calculate cluster point r and base station apart from d _r, then the position data of cluster point r is expressed as (AOA _r, d _r, d _r).

Because the position of the position of cluster point r and base station is all known, therefore, cluster point r and base station apart from d _rCan calculate.

Step 603: the base station is calculated the AOA distance between terminal i to be measured and the arbitrary cluster point r respectively

$l_{\mathrm{AOA}}^r=|{\mathrm{AOA}}_i-{\mathrm{AOA}}_r|(((d_{{\mathrm{SNR}}_i}+d_{{\mathrm{TOA}}_i})/2+d_r)/2)$

Step 604: the base station is calculated the Euclidean distance between the position data of measuring position data and the arbitrary cluster point r in the historical data base of terminal i to be measured respectively, seeks the minimum cluster point s of Euclidean distance.

The computing formula of the Euclidean distance between the measuring position data of terminal i to be measured and the position data of arbitrary cluster point r is following:

$\mathrm{\ϵ}={l_{\mathrm{AOA}}^r}^2+{(d_{{\mathrm{SNR}}_i}-d_r)}^2+{(d_{{\mathrm{TOA}}_i}-d_r)}^2$

Step 605: the base station makes α=AOA _i-AOA _s, cluster is put the physical coordinates rotation alpha of s, obtain new physical coordinates (x _Ui, y _Ui), be the initial estimated location of terminal i to be measured, wherein:

x _ui＝x _s·cosα-y _s·sinα

y _ui＝x _s·sinα+y _s·cosα

Fig. 7 has provided the sketch map of confirming terminal location to be measured according to the position of coupling cluster point.

In this step 605, the purpose of cluster being put the physical coordinates rotation alpha of s is in order to estimate the initial position of terminal i to be measured more accurate.In practical application, also can be directly with (x _s, y _s) as the initial estimated location of terminal i to be measured.

Below provide the embodiment of above-mentioned steps 503:

Initial estimated location and terminal to be measured distance between any two according to terminal to be measured that Fig. 8 provides for the embodiment of the invention adopt sum-product algorithm to obtain the method flow diagram of the final estimated position at terminal to be measured, and as shown in Figure 8, its concrete steps are following:

Step 801: establish total N terminal to be measured in the sub-district,, establish the position distribution of terminal i to be measured and obey with initial estimated location (x for arbitrary terminal i to be measured _Ui, y _Ui) be the two-dimentional Gaussian distribution at center, the initial position probability distribution P of terminal i to be measured then _i(x y) can be expressed as:

$P_i(x,y)=\frac{1}{2{\mathrm{\π\σ}}^2}\exp \{-\frac{{(x-x_{\mathrm{ui}})}^2+{(y-y_{\mathrm{ui}})}^2}{2{\mathrm{\σ}}^2}\}$

Wherein, the value of σ can be confirmed with experience as required.

For example: the initial estimated location as if terminal i to be measured is (5,8), then the initial position probability distribution P of terminal i to be measured _i(x, y) as shown in Figure 9.

Step 802: base station initialization iterations q=0; For arbitrary terminal i to be measured; The position probability distribution of initialization terminal i to be measured; That is, make

Step 803: arbitrary other terminal k to be measured is to the updating value

of the position probability distribution of terminal i to be measured in this iterative process of base station calculating

$u_{k\→i}^{\left(q\right)}(x,y)=\underset{s,t}{\mathrm{\Σ}}p\left(d_{\mathrm{ik}}\right|(x,y),(s,t))\·b_k^{(q-1)}(s,t)$

Wherein, (s; T) be the physical coordinates of terminal k to be measured, (s, span t) is identical with the coverage of sub-district;

is the position probability distribution after the q-1 time iteration of terminal k to be measured

$p\left(d_{\mathrm{ik}}\right|(x,y),(s,t))=\frac{1}{{2\mathrm{\π\σ}}^2}\exp \{-\frac{{(d_{\mathrm{ik}}-\sqrt{{(x-s)}^2+{(y-t)}^2})}^2}{{2\mathrm{\σ}}^2}\}$

The physical significance of this formula is: (in s, t) last time,, terminal i to be measured was at physical location (x, the probability on y) at physical location as terminal k to be measured.

expression: with the updating value of the position probability distribution after the q-1 time iteration of terminal k to be measured to the position probability distribution of terminal i to be measured.

Step 804: the base station is according to the initial position probability distribution P of terminal i to be measured _i(x, other terminal to be measured obtains the latest position probability distribution of terminal i to be measured to the updating value of the position probability distribution of terminal i to be measured y) and in this iterative process

$b_i^{\left(q\right)}(x,y)=p_i(x,y)\·\underset{k\≠i}{\mathrm{\Π}}{u}_{k\→i}^{\left(q\right)}(x,y)$

Step 805: whether base station judges iterations q less than pre-determined number Q, if, make q=q+1, return step 803, continue the next iteration process; Otherwise, execution in step 806.

The value of Q can rule of thumb be confirmed.

Step 806: the base station determines the final position of the test terminal i probability distribution:

is the ultimate test terminal i estimated position

is:

wherein; (x, span y) is identical with the coverage of sub-district.

After obtaining the final estimated position of terminal i to be measured

; With terminal i to be measured as new sample point; Adopt embodiment illustrated in fig. 2ly, carry out cluster again to upgrade historical data base with existing sample point.

Figure 10 has provided an initial estimated location and a terminal to be measured distance between any two according to terminal to be measured, and the employing sum-product algorithm obtains the sketch map of the final estimated position at terminal to be measured, wherein, and P _i, i=0,1 ..., N-1 is the initial position probability distribution of terminal i to be measured,

Be the position probability distribution of terminal i to be measured after the q time iteration,

Be terminal k to be measured in the q time iterative process

Pass to terminal i to be measured

Updating value.During each iteration, terminal room to be measured in twos transmits such updating value each other, in conjunction with the initial position probability distribution P at each terminal oneself _i, obtain new position probability distribution more accurately.For example: for the terminal to be measured 1 among Figure 10; For the first time during iteration; The updating value that

of other arbitrary terminal k to be measured passes to terminal 1 to be measured for

terminal 1 to be measured so for the first time the position probability distribution

after the iteration not only comprised oneself initial position probability distribution; Comprised that also

at other terminal to be measured passes to its updating value; Thereby can obtain result more accurately; And then carry out the iteration second time; Because the probability distribution

at other terminal to be measured is also more accurate through iteration; The updating value

that passes to terminal 1 to be measured is also more accurate, and it is just more accurate for the first time that the result of terminal to be measured iteration 1 second time compares.So behind the iteration several times, each terminal to be measured can make full use of other terminal information to be measured, obtains result more accurately, thereby reaches the purpose of co-positioned.

The composition diagram of the terminal positioning device that Figure 11 provides for the embodiment of the invention, shown in figure 11, it mainly comprises: historical data is set up unit 111, initial position estimation unit 112, final position estimation unit 113 and historical data library unit 114, wherein:

Historical data is set up unit 111: for arbitrary sub-district; First preset number cluster terminal is set in the sub-district; Obtain the position data at each cluster terminal: AOA, TOA, SNR and physical coordinates, the position data at each cluster terminal is put into historical data library unit 114.

Initial position estimation unit 112: for arbitrary terminal to be measured; Measure AOA, TOA and the SNR at this terminal to be measured; AOA, TOA and SNR according to this terminal to be measured; In historical data library unit 114, search the cluster terminal of mating most with this terminal to be measured, confirm the initial estimated location at this terminal to be measured, the initial estimated location at this terminal to be measured is sent to final position estimation unit 113 according to the physical coordinates at this cluster terminal.

Final position estimation unit 113: the initial estimated location at the terminal to be measured of sending according to initial position estimation unit 112 and the distance between this terminal to be measured and other terminal to be measured, calculate the final position at this terminal to be measured.

In practical application, historical data is set up unit 111 and can be comprised: first module and second module, wherein:

First module: first preset number initial clustering terminal is set in the sub-district, and second preset number sample terminal is set.

Second module: the initialization iterations is 0; For each sample terminal; Seek and nearest cluster terminal, this sample terminal; With this sample terminal attaching in this cluster terminal; All sample terminals that belong to same cluster terminal as a cluster crowd, as a new cluster terminal, are calculated the mean square error of the physical coordinates at the physical coordinates at all new cluster terminals that current iteration obtains and all cluster terminals that last iteration obtains with each cluster crowd's barycenter; If mean square error, is then confirmed cluster less than preset value and is accomplished; Otherwise it is said for each sample terminal to return execution, the action at the cluster terminal that searching and this sample terminal are nearest.

In practical application, final position estimation unit 113 is further used for, and behind the final position that calculates this terminal to be measured, the position data at this terminal to be measured: AOA, TOA, SNR and physical coordinates is sent to historical data set up unit 111;

And; After historical data is set up the position data that unit 111 receives the terminal to be measured that final position estimation unit 113 sends; With this terminal to be measured as new sample terminal; Again cluster is carried out at all sample terminals, cluster is accomplished, and with the position data at each new cluster terminal of obtaining: AOA, TOA, SNR and physical coordinates upgrade the historical data in the historical data library unit 114.

In practical application, initial position estimation unit 112 can comprise: three module and four module, wherein:

Three module: for arbitrary terminal to be measured, measure AOA, TOA and the SNR at this terminal to be measured, AOA, TOA and the SNR at this terminal to be measured sent to four module.

Four module: AOA, TOA and the SNR at the terminal to be measured of sending according to three module; In historical data library unit 114, search and the minimum cluster terminal of the Euclidean distance at this terminal to be measured; Calculate the difference α of AOA at AOA and the said cluster terminal at said terminal to be measured; With the physical coordinates rotation alpha at this cluster terminal, with the initial estimated location of the physical coordinates that obtains after the rotation as said terminal to be measured.

In practical application, final position estimation unit 113 can comprise: the 5th module and the 6th module, wherein:

The 5th module: calculate the distance of terminal to be measured and arbitrary other terminal room to be measured, each distance that calculates is sent to the 6th module.

The 6th module: the initial estimated location at the terminal to be measured that reception initial position estimation unit 112 is sent; If it is the two-dimentional Gaussian distribution at center that the position distribution at said terminal to be measured is obeyed with the initial estimated location, then confirm the initial position probability distribution at this terminal to be measured according to the initial estimated location at said terminal to be measured; Initialization number of times repeatly is 0; According to the distance of said terminal to be measured and arbitrary other terminal room to be measured, calculate in this iterative process arbitrary other terminal to be measured to the updating value of the position probability distribution at said terminal to be measured; To the updating value of the position probability distribution at said terminal to be measured, obtain the latest position probability distribution at said terminal to be measured according to other terminal to be measured in the initial position probability distribution at said terminal to be measured and this iterative process; Whether judge iterations less than pre-determined number, if return and carry out in this iterative process of said calculating arbitrary other terminal to be measured the action of the updating value of the position probability distribution at said terminal to be measured is continued the next iteration process; Otherwise, the latest position probability distribution at terminal to be measured as its final position probability distribution, is calculated the final position at said terminal to be measured according to this final position probability distribution.

Wherein, the 5th module can comprise: first submodule, second submodule and three module, wherein:

First submodule: calculate β=AOA _i-AOA _k, wherein, AOA _iBe the AOA at said terminal to be measured, AOA _kBe the AOA at said arbitrary other terminal to be measured, β is sent to the 3rd submodule.

Second submodule: the distance of calculating said terminal to be measured and base station

Calculate the distance of said arbitrary other terminal to be measured and base station Wherein,

For according to SNR _iThe terminal said to be measured that calculates and the distance of base station,

For according to TOA _iThe terminal said to be measured that calculates and the distance of base station,

For according to SNR _kSaid arbitrary other terminal to be measured that calculates and the distance of base station, For according to TOA _kSaid arbitrary other terminal to be measured that calculates and the distance of base station are with d _i, d _kSend to the 3rd submodule.

The 3rd submodule: calculate said terminal to be measured and said arbitrary other terminal room to be measured apart from d _Ik:

$d_{\mathrm{ik}}=\sqrt{d_i^2+d_k^2-{2d}_i{d}_k\·\cos \mathrm{\β}}.$

Terminal positioning device in the embodiment of the invention can be positioned on the base station.

The above is merely preferred embodiment of the present invention, and is in order to restriction the present invention, not all within spirit of the present invention and principle, any modification of being made, is equal to replacement, improvement etc., all should be included within the scope that the present invention protects.

Claims (16)

1. a method of locating terminal is characterized in that, this method comprises:

For arbitrary sub-district; First preset number cluster terminal is set in the sub-district; Obtain the position data at each cluster terminal: angle of arrival AOA, the time of advent TOA, signal to noise ratio snr and physical coordinates, the position data at each cluster terminal is put into historical data base;

For arbitrary terminal to be measured; Measure AOA, TOA and the SNR at this terminal to be measured; According to AOA, TOA and the SNR at this terminal to be measured, in historical data base, search the cluster terminal of mating most with this terminal to be measured, confirm the initial estimated location at this terminal to be measured according to the physical coordinates at this cluster terminal;

According to the initial estimated location at terminal to be measured and the distance between this terminal to be measured and other terminal to be measured, calculate the final position at this terminal to be measured.

2. method according to claim 1; It is characterized in that; Said first preset number cluster terminal that in the sub-district, is provided with; Obtain the position data at each cluster terminal: angle of arrival AOA, the time of advent TOA, signal to noise ratio snr and physical coordinates,, the position data at each cluster terminal is put into historical data base comprises:

First preset number initial clustering terminal is set in the sub-district, and second preset number sample terminal is set;

Distance according to sample terminal and cluster terminal; Cluster is carried out at all sample terminals; Cluster is accomplished; Obtain first a preset number new cluster terminal, calculate the position data at each new cluster terminal: AOA, TOA, SNR and physical coordinates, the position data at each new cluster terminal is put into historical data base.

3. method according to claim 2 is characterized in that, said distance according to sample terminal and cluster terminal is carried out cluster to all sample terminals and comprised:

The initialization iterations is 0;

For each sample terminal; Seek and nearest cluster terminal, this sample terminal; With this sample terminal attaching in this cluster terminal; All sample terminals that belong to same cluster terminal as a cluster crowd, as a new cluster terminal, are calculated the mean square error of the physical coordinates at the physical coordinates at all new cluster terminals that current iteration obtains and all cluster terminals that last iteration obtains with each cluster crowd's barycenter; If mean square error, is then confirmed cluster less than preset value and is accomplished; Otherwise it is said for each sample terminal to return execution, the action at the cluster terminal that searching and this sample terminal are nearest.

4. method according to claim 2 is characterized in that, said first preset number initial clustering terminal that in the sub-district, is provided with is:

The sub-district evenly is divided into the first preset number sub regions, with the center of each subregion as position, an initial clustering terminal.

5. method according to claim 2 is characterized in that, further comprises after the final position at this terminal to be measured of said calculating:

Behind the final position that calculates this terminal to be measured; With this terminal to be measured as new sample terminal; Carry out cluster with existing sample terminal, cluster is accomplished, and with the position data at each new cluster terminal of obtaining: AOA, TOA, SNR and physical coordinates upgrade historical data base.

6. method according to claim 1 is characterized in that, AOA, TOA and the SNR at this terminal to be measured of said basis search the cluster terminal of mating most with this terminal to be measured and comprise in historical data base:

According to AOA, TOA and the SNR at this terminal to be measured, in historical data base, search and the minimum cluster terminal of the Euclidean distance at this terminal to be measured;

Said physical coordinates according to this cluster terminal confirms that the initial estimated location at this terminal to be measured is:

Calculate the difference α of AOA at AOA and the said cluster terminal at said terminal to be measured, with the physical coordinates rotation alpha at this cluster terminal, with the initial estimated location of the physical coordinates that obtains after the rotation as said terminal to be measured.

7. method according to claim 1 is characterized in that, and is said according to the initial estimated location at terminal to be measured and the distance between this terminal to be measured and other terminal to be measured, and the final position of calculating this terminal to be measured further comprises before:

Calculate the distance between said terminal to be measured and arbitrary other terminal to be measured through following steps:

Calculate β=AOA _i-AOA _k, wherein, AOA _iBe the AOA at said terminal to be measured, AOA _kAOA for said arbitrary other terminal to be measured;

Calculate the distance of said terminal to be measured and base station

Calculate the distance of said arbitrary other terminal to be measured and base station Wherein,

For according to SNR _iThe terminal said to be measured that calculates and the distance of base station,

For according to TOA _iThe terminal said to be measured that calculates and the distance of base station,

For according to SNR _kSaid arbitrary other terminal to be measured that calculates and the distance of base station, For according to TOA _kSaid arbitrary other terminal to be measured that calculates and the distance of base station, SNR _iBe the SNR at said terminal to be measured, TOA _iBe the TOA at said terminal to be measured, SNR _kBe the SNR at said arbitrary other terminal to be measured, TOA _kTOA for said arbitrary other terminal to be measured;

Calculate said terminal to be measured and said arbitrary other terminal room to be measured apart from d _Ik: $d_{\mathrm{Ik}}=\sqrt{d_i^2+d_k^2-{2d}_i{d}_k\·\mathrm{Cos}\mathrm{\β}}.$

8. method according to claim 1 is characterized in that, said according to the initial estimated location at terminal to be measured and the distance between this terminal to be measured and other terminal to be measured, the final position of calculating this terminal to be measured comprises:

If it is the two-dimentional Gaussian distribution at center that the position distribution at said terminal to be measured is obeyed with the initial estimated location, then confirm the initial position probability distribution at this terminal to be measured according to the initial estimated location at said terminal to be measured;

The initialization iterations is 0;

According to the distance between said terminal to be measured and arbitrary other terminal to be measured, calculate in this iterative process arbitrary other terminal to be measured to the updating value of the position probability distribution at said terminal to be measured;

To the updating value of the position probability distribution at said terminal to be measured, obtain the latest position probability distribution at said terminal to be measured according to other terminal to be measured in the initial position probability distribution at said terminal to be measured and this iterative process;

Whether judge iterations less than pre-determined number, if return and carry out in this iterative process of said calculating arbitrary other terminal to be measured the action of the updating value of the position probability distribution at said terminal to be measured is continued the next iteration process; Otherwise, the latest position probability distribution at terminal to be measured as its final position probability distribution, is calculated the final position at said terminal to be measured according to this final position probability distribution.

9. method according to claim 8 is characterized in that, arbitrary other terminal to be measured to the updating value of the position probability distribution at said terminal to be measured is in this iterative process of said calculating:

Calculate $u_{k\→i}^{\left(q\right)}(x,y)=\underset{s,t}{\mathrm{\Σ}}p\left(d_{\mathrm{Ik}}\right|(x,y),(s,t))\·b_k^{(q-1)}(s,t)$

Wherein, K is the sequence number at arbitrary other terminal to be measured; I is the sequence number at said terminal to be measured; Q is the current iteration number of times;

be in this iterative process arbitrary other terminal k to be measured to the updating value of the position probability distribution of said terminal i to be measured; (s; T) be the physical coordinates of arbitrary other terminal k to be measured, be the position probability distribution of arbitrary other terminal k to be measured after last once iteration;

$p\left(d_{\mathrm{ik}}\right|(x,y),(s,t))=\frac{1}{{2\mathrm{\π\σ}}^2}\exp \{-\frac{{(d_{\mathrm{ik}}-\sqrt{{(x-s)}^2+{(y-t)}^2})}^2}{{2\mathrm{\σ}}^2}\}$

The physical significance of this formula is: (in s, t) last time,, said terminal i to be measured was at physical location (x, the probability on y) at physical location as said arbitrary other terminal k to be measured; d _IkBe the distance between said arbitrary other terminal k to be measured and said terminal i to be measured;

Other terminal to be measured is to the updating value of the position probability distribution at said terminal to be measured in said initial position probability distribution and this iterative process according to said terminal to be measured, and the latest position probability distribution that obtains said terminal to be measured is:

Wherein, p _i(x y) is the initial position probability distribution at said terminal to be measured;

Said final position of calculating said terminal to be measured according to this final position probability distribution is:

${\hat{x}}_i=\underset{x,y}{\mathrm{\Σ}}x\·P_i^{\′}(x,y)$

${\hat{y}}_i=\underset{x,y}{\mathrm{\Σ}}y\·P_i^{\′}(x,y)$

Wherein,

(x, span y) is the overlay area of sub-district.

10. a terminal positioning device is characterized in that, this device comprises:

First module: for arbitrary sub-district; First preset number cluster terminal is set in the sub-district; Obtain the position data at each cluster terminal: angle of arrival AOA, the time of advent TOA, signal to noise ratio snr and physical coordinates, the position data at each cluster terminal is put into historical data base;

Unit second: for arbitrary terminal to be measured; Measure AOA, TOA and the SNR at this terminal to be measured; AOA, TOA and SNR according to this terminal to be measured; In historical data base, search the cluster terminal of mating most with this terminal to be measured, confirm the initial estimated location at this terminal to be measured, the initial estimated location at this terminal to be measured is sent to Unit the 3rd according to the physical coordinates at this cluster terminal;

Unit the 3rd:, calculate the final position at this terminal to be measured according to the initial estimated location at terminal to be measured and the distance between this terminal to be measured and other terminal to be measured.

11. device according to claim 10 is characterized in that, said first module comprises:

First module: first preset number initial clustering terminal is set in the sub-district, and second preset number sample terminal is set;

Second module: the initialization iterations is 0; For each sample terminal; Seek and nearest cluster terminal, this sample terminal; With this sample terminal attaching in this cluster terminal; All sample terminals that belong to same cluster terminal as a cluster crowd, as a new cluster terminal, are calculated the mean square error of the physical coordinates at the physical coordinates at all new cluster terminals that current iteration obtains and all cluster terminals that last iteration obtains with each cluster crowd's barycenter; If mean square error, is then confirmed cluster less than preset value and is accomplished; Otherwise it is said for each sample terminal to return execution, the action at the cluster terminal that searching and this sample terminal are nearest.

12. device according to claim 11 is characterized in that, said Unit the 3rd is further used for, and behind the final position that calculates this terminal to be measured, the position data at this terminal to be measured: AOA, TOA, SNR and physical coordinates is sent to first module;

After said first module receives the position data at said terminal to be measured; With this terminal to be measured as new sample terminal; Again cluster is carried out at all sample terminals, cluster is accomplished, and with the position data at each new cluster terminal of obtaining: AOA, TOA, SNR and physical coordinates upgrade historical data base.

13. device according to claim 10 is characterized in that, said Unit second comprises:

Three module:, measure AOA, TOA and the SNR at this terminal to be measured for arbitrary terminal to be measured;

Four module: according to AOA, TOA and the SNR at this terminal to be measured; In historical data base, search and the minimum cluster terminal of the Euclidean distance at this terminal to be measured; Calculate the difference α of AOA at AOA and the said cluster terminal at said terminal to be measured; With the physical coordinates rotation alpha at this cluster terminal, with the initial estimated location of the physical coordinates that obtains after the rotation as said terminal to be measured.

14. device according to claim 10 is characterized in that, said Unit the 3rd comprises:

The 5th module: calculate the distance of said terminal to be measured and arbitrary other terminal room to be measured, each distance that calculates is sent to the 6th module;

The 6th module: the position distribution obedience of establishing said terminal to be measured is the two-dimentional Gaussian distribution at center with the initial estimated location, then confirms the initial position probability distribution at this terminal to be measured according to the initial estimated location at said terminal to be measured; Initialization number of times repeatly is 0; According to the distance of said terminal to be measured and arbitrary other terminal room to be measured, calculate in this iterative process arbitrary other terminal to be measured to the updating value of the position probability distribution at said terminal to be measured; To the updating value of the position probability distribution at said terminal to be measured, obtain the latest position probability distribution at said terminal to be measured according to other terminal to be measured in the initial position probability distribution at said terminal to be measured and this iterative process; Whether judge iterations less than pre-determined number, if return and carry out in this iterative process of said calculating arbitrary other terminal to be measured the action of the updating value of the position probability distribution at said terminal to be measured is continued the next iteration process; Otherwise, the latest position probability distribution at terminal to be measured as its final position probability distribution, is calculated the final position at said terminal to be measured according to this final position probability distribution.

15. device according to claim 14 is characterized in that, said the 5th module comprises:

First submodule: calculate β=AOA _i-AOA _k, wherein, AOA _iBe the AOA at said terminal to be measured, AOA _kBe the AOA at said arbitrary other terminal to be measured, β is sent to the 3rd submodule;

Second submodule: the distance of calculating said terminal to be measured and base station

Calculate the distance of said arbitrary other terminal to be measured and base station

Wherein,

For according to SNR _iThe terminal said to be measured that calculates and the distance of base station, For according to TOA _iThe terminal said to be measured that calculates and the distance of base station, For according to SNR _kSaid arbitrary other terminal to be measured that calculates and the distance of base station,

For according to TOA _kSaid arbitrary other terminal to be measured that calculates and the distance of base station are with d _i, d _kSend to the 3rd submodule;

The 3rd submodule: calculate said terminal to be measured and said arbitrary other terminal room to be measured apart from d _Ik: $d_{\mathrm{Ik}}=\sqrt{d_i^2+d_k^2-{2d}_i{d}_k\·\mathrm{Cos}\mathrm{\β}}.$

16., it is characterized in that said device is positioned on the base station according to the arbitrary described device of claim 10 to 15.

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