CN1953610A  A method to position the mobile station  Google Patents
A method to position the mobile station Download PDFInfo
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 CN1953610A CN1953610A CNA2006101278522A CN200610127852A CN1953610A CN 1953610 A CN1953610 A CN 1953610A CN A2006101278522 A CNA2006101278522 A CN A2006101278522A CN 200610127852 A CN200610127852 A CN 200610127852A CN 1953610 A CN1953610 A CN 1953610A
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 ms
 described
 value
 position coordinates
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 238000000034 methods Methods 0.000 claims description 15
 230000001413 cellular Effects 0.000 claims description 11
 238000007476 Maximum Likelihood Methods 0.000 claims description 3
 238000004364 calculation methods Methods 0.000 description 1
 238000004088 simulation Methods 0.000 description 1
Abstract
Description
Technical field
The present invention relates to wireless communication field, relate in particular to a kind of method that travelling carriage is positioned.
Background technology
The main flow communication service provider overwhelming majority adopts cellular network at present.Cellular network is exactly that the service of MS (travelling carriage) difference is divided into orthohexagonal one by one subarea, and a base station is established in each subdistrict, has formed the structure that shape exactly likes " honeycomb ".Common cellular network type has: networks such as GSM (global system for mobile communications) network, CDMA (code division multiple access) network, 3G (3G (Third Generation) Moblie) network.
The localization method of cellular network is according to the used parameter difference in location, can be divided into SSOA (field strength measurement method), ESSOA (enhancement mode field strength measurement method)/FingerPrint (multipath fingerprint technique), AOA (arrival angular measurement), TOA/TDOA (time of advent/time difference measurements method) and hybrid parameter localization method etc.The principle schematic of the localization method based on TOA of the prior art as shown in Figure 1, concrete processing procedure is: at first measure the relative distance between a plurality of BS (base station) and the MS (travelling carriage), then, with known BS position coordinates is the center of circle, with relative distance between the BS that measures and MS is that radius is done circle, a plurality of BS carry out same operation can obtain one group of circle that intersects, at last by a certain special algorithm (as: criterion of least squares algorithm, maximumlikelihood criterion algorithms etc.) calculate the intersection point of the circle that this group intersects, this intersection point is the estimated value of MS position coordinates.
The shortcoming based on the localization method of TOA of abovementioned prior art is: this method is independently considered the distance estimations between each BS and MS, the redundant information that do not make full use of between each BS, topological structure provided between BS and MS.The precision of the estimated value of the MS position coordinates that this method measures is not high.
Summary of the invention
In view of abovementioned existing in prior technology problem, the purpose of this invention is to provide a kind of method that travelling carriage is positioned, thereby can improve the positioning accuracy of MS, MS is compared accurate localization.
The objective of the invention is to be achieved through the following technical solutions:
A kind of method that travelling carriage is positioned comprises step:
A, obtain the estimated value of the position coordinates of MS according to the distance estimations value between mobile station MS and each base station BS; By iterative process the estimated value of the position coordinates of the distance estimations value between described MS and each base station BS, MS is repeatedly upgraded;
B, when the mean value of the difference between the estimated value of the position coordinates of a plurality of MS of described acquisition during less than the numerical value set, the estimated value of the position coordinates of the MS of described last acquisition is defined as the final estimated value of the position coordinates of MS.
Described steps A specifically comprises:
A1, utilization arrive the distance estimations value between time T OA method of measurement acquisition MS and each BS; Obtain the estimated value information of the position coordinates of MS by set algorithm according to the distance estimations value between this MS and each BS;
A2, the distance estimations value between described MS and each BS is upgraded, and the estimated value of the position coordinates of described MS is upgraded according to MS after upgrading and the distance estimations value between each BS according to the estimated value of the position coordinates of described MS.
Described steps A 2 specifically comprises:
A21, according to the estimated value of the position coordinates of described MS and the location coordinate information of each BS, MS after obtaining to upgrade and the distance estimations value between each BS;
A22, with the distance estimations value between the MS after the described renewal and each BS and the MS before upgrading and the distance estimations value between each BS carry out arithmetic average,, the estimated value of the position coordinates of described MS is upgraded by set algorithm according to the distance estimations value between the MS that obtains after the arithmetic average and each BS;
A23, once more the distance estimations value between described MS and each BS is upgraded, and by described set algorithm the estimated value of the position coordinates of described MS is upgraded once more according to the estimated value of the position coordinates of the MS after the described renewal; Repeat said process by iterative process.
Described set algorithm specifically comprises: criterion of least squares algorithm or maximumlikelihood criterion algorithm.
Described step B specifically comprises:
When the mean value of the difference between the estimated value of the position coordinates of a plurality of MS of described acquisition during, stop described iterative process less than predefined numerical value; The estimated value of the position coordinates of the MS of described last acquisition is defined as the final estimated value of the position coordinates of MS, the MS of described last acquisition and the distance estimations value between each BS are defined as final estimated value between MS and each BS.
Described method is applicable to cellular network.
Described cellular network comprises: global system for mobile communications GSM network or Code Division Multiple Access (CDMA) network or 3G (Third Generation) Moblie 3G network.
As seen from the above technical solution provided by the invention, the present invention is by taking all factors into consideration the network overall topology of the positional information that comprises BS and MS, utilization statistics correlation theory, and a kind of method that MS is positioned of novel iterative manner proposed based on the criterion of least squares algorithm, thereby can improve the positioning accuracy of MS in the cellular network, MS in the cellular network is compared accurate localization.The present invention carries out analog computation by the algorithm of setting, and can save the resource of BS.
Description of drawings
Fig. 1 is the principle schematic based on the localization method of TOA;
Fig. 2 is the principle schematic of the embodiment of the method for the invention;
Fig. 3 is the concrete process chart of the embodiment of the method for the invention;
Fig. 4 be among the embodiment of the method for the invention MS site error and iterations concern schematic diagram.
Embodiment
The invention provides a kind of method that travelling carriage is positioned.
Describe the method for the invention in detail below in conjunction with accompanying drawing, the principle schematic of the embodiment of the method for the invention as shown in Figure 2, the concrete handling process of this embodiment comprises the steps: as shown in Figure 3
Step 31: obtain first kind distance estimations value Ri between BS and MS by the TOA ranging technology.
In this embodiment, the number of the locating base station that is without loss of generality is got 5, be respectively BSi (i=1,2 ... 5).
Suppose base station BS i (i=1,2 ... 5) position coordinates be (xi, yi), mobile station MS actual position coordinate be (x, y).
At first, utilize the existing TOA ranging technology of cellular localization network obtain respectively BSi (i=1,2 ... 5) and MS between apart from estimated value Ri (i=1,2 ... 5), the present invention with this Ri (i=1,2 ... 5) be referred to as first kind direct range and estimate.
Step 32: by the criterion of least squares algorithm, utilize Ri to obtain the middle estimated value MS ' of MS position coordinates, obtain the second class distance estimations value between MS ' and BS once more.
Utilize the first kind direct range of abovementioned acquisition estimate Ri (i=1,2 ... 5) and each BS and MS between the position relation, continue to obtain extra locating information by the criterion of least squares algorithm.Such as, the middle estimated value MS ' of acquisition MS position coordinates (x ', y '), and the second class distance estimations value between MS ' and BS.
Introducing the specific algorithm of abovementioned criterion of least squares algorithm below, is example with BS1, if consider to use all estimated value Ri (i=1,2 ... 5) calculate the MS position coordinates, the computing formula of then calculating MS position coordinates MS ' (x ', y ') is:
According to the MS position coordinates MS ' that calculates (x ', y ') and known base station BS i (i=1,2 ... 5) position coordinates be (xi, yi), can obtain the second class distance estimations value Ri ' between MS ' and BSi= MS 'BSi.
Step 33, utilize arithmetic average to handle two class estimated values, obtain between the MS ' that upgrades and BSi apart from estimated value.
Have between the first kind distance estimations value of abovementioned acquisition, the second class distance estimations value and add up independently characteristic, according to the statistics correlation theory as can be known, the mathematic(al) mean of getting a plurality of independent sample values in the random sample space can reduce the variance that sample value distributes.Therefore, the drift rate of the arithmetic mean of the abovementioned two class distance estimations values that obtain is littler, and relative two class distance estimations values are itself more near the actual distance value.
Therefore, calculate the arithmetic mean Ri of the first kind distance estimations value and the second class distance estimations value of abovementioned acquisition ^{*}=Ri+Ri '/2, (i=1,2 ... 5), with the Ri that obtains ^{*}As between MS ' that upgrades and BSi apart from estimated value.
Step 34: by the criterion of least squares algorithm, recomputate the MS position coordinates apart from estimated value between the MS ' of the renewal that utilization obtains and BS, tend towards stability up to the MS position coordinates.
Distance estimations value Ri with the renewal of abovementioned acquisition ^{*}(i=1,2 ... 5) be updated in the abovementioned formula 1, recalculate the estimated value of MS position coordinates, the estimated value of this MS position coordinates will make moderate progress on precision.
Then, according to the estimated value of the MS position coordinates that recalculates and known base station BS i (i=1,2, ... 5) position coordinates is (xi, yi), recomputate the distance estimations value between MS ' and BSi, continue to recomputate the estimated value of MS position coordinates again, promptly pass through the estimated value of iterative process repeated calculation MS position coordinates.
When the renewal of the estimated value of MS position coordinates changes when tending towards stability, when promptly the mean value of the difference between the estimated value of the position coordinates of a plurality of MS of Huo Deing was less than predefined numerical value, iterative algorithm arrived its convergence point, stopped abovementioned iterative process.And the estimated value of the position coordinates of the MS that will obtain at last is defined as the final estimated value of the position coordinates of MS, and the MS of described last acquisition and the distance estimations value between each BS are defined as final estimated value between MS and each BS.
The invention provides an embodiment an of the method for the invention, this embodiment is the simulation result on the MATLAB platform.
In this embodiment, the TOA evaluated error is set and gets 100,150,200 and 250m respectively ^{2}Normal distribution.Five location BS are evenly distributed on around the MS, and the average distance between MS is 1000m.
In this embodiment MS site error and iterations concern schematic diagram as shown in Figure 4, the emulation evaluation criteria is to calculate under the TOA of varying strength noise jamming.With the TOA noise variance is 250m ^{2}/ C ^{2}(C is expressed as the light velocity) is example, after using the handling process of the described method of the invention described above, can reach the convergence of algorithm point by four iteration, the mean error of the estimated value of MS position coordinates (ALE) drops to about 210m about by original 250m, maximum improvement ratio is about 16%, verifies that thus the method for the invention can improve the positioning accuracy of MS in the cellular network significantly.
The above; only for the preferable embodiment of the present invention, but protection scope of the present invention is not limited thereto, and anyly is familiar with those skilled in the art in the technical scope that the present invention discloses; the variation that can expect easily or replacement all should be encompassed within protection scope of the present invention.Therefore, protection scope of the present invention should be as the criterion with the protection range of claim.
Claims (7)
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Cited By (6)
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CN101437287B (en) *  20071115  20110119  展讯通信（上海）有限公司  Method and system for wireless localization through assistant base station update 
WO2012016355A1 (en) *  20100805  20120209  Telefonakietolaget Lm Ericsson (Publ)  Method of and system for locating the position of user equipment 
CN102612137A (en) *  20120118  20120725  北京邮电大学  Postdisaster search and rescue terminal positioning method and life detecting device 
CN103257336A (en) *  20120215  20130821  北京乐富科技有限责任公司  Aftercalamity searchandrescue cluster locating method based on assist of air pressure and height measurement 
WO2014047824A1 (en) *  20120927  20140403  Telefonaktiebolaget L M Ericsson (Publ)  Detecting multipath and determining positioning measurement uncertainty 
CN104125639A (en) *  20140721  20141029  醴陵恒茂电子科技有限公司  Wireless positioning method and device 
Family Cites Families (3)
Publication number  Priority date  Publication date  Assignee  Title 

GB1262223A (en) *  19700626  19720202  Mullard Ltd  Improvements in or relating to location systems 
US6505122B1 (en) *  20010625  20030107  Qualcomm, Incorporated  Method and apparatus for providing accurate position estimates in instances of severe dilution of precision 
CN1235430C (en) *  20021107  20060104  华为技术有限公司  Method for eveluating position 

2006
 20060922 CN CNB2006101278522A patent/CN100461969C/en not_active IP Right Cessation
Cited By (8)
Publication number  Priority date  Publication date  Assignee  Title 

CN101437287B (en) *  20071115  20110119  展讯通信（上海）有限公司  Method and system for wireless localization through assistant base station update 
WO2012016355A1 (en) *  20100805  20120209  Telefonakietolaget Lm Ericsson (Publ)  Method of and system for locating the position of user equipment 
CN102612137A (en) *  20120118  20120725  北京邮电大学  Postdisaster search and rescue terminal positioning method and life detecting device 
CN102612137B (en) *  20120118  20140910  北京邮电大学  Postdisaster search and rescue terminal positioning method and life detecting device 
CN103257336A (en) *  20120215  20130821  北京乐富科技有限责任公司  Aftercalamity searchandrescue cluster locating method based on assist of air pressure and height measurement 
WO2014047824A1 (en) *  20120927  20140403  Telefonaktiebolaget L M Ericsson (Publ)  Detecting multipath and determining positioning measurement uncertainty 
US9467803B2 (en)  20120927  20161011  Telefonaktiebolaget Lm Ericsson (Publ)  Detecting multipath and determining positioning measurement uncertainty 
CN104125639A (en) *  20140721  20141029  醴陵恒茂电子科技有限公司  Wireless positioning method and device 
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