CN1645967A - Positioning method based on communicating network - Google Patents
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Abstract
By using the method, the current mobile communication network doesn't need to rebuild. Through combining theoretical prediction of signal coverage and on spot test, or comparing the input data at the time of locating with pre-collected data, the high precise location and fast calculating speed can be implemented.
Description
Technical field
The present invention relates to a kind of localization method, especially a kind of localization method based on GSM network or cdma network signal overlay model based on electromagnetic wave signal propagation forecast model.
Background technology
At present, GSM network or cdma network cover district in all parts of the country substantially, and GSM network or cdma network communication have become the main flow of current mobile communication technology, utilize communication network to realize that the location technology of travelling carriage emerges in an endless stream, and conclusion is got up, and has following several:
1. cellular cell technology (COO or CELL-ID)
COO, the CELL-ID technology is compared with other technology, and its precision is minimum.The cellular cell at place, mobile network base station (BTS) is as being positioned object, and like this, positioning accuracy just must depend on the size of sub-district.Response speed is very fast, needs about 3 seconds.
2. strengthen observation time difference technology (E-OTD)
The E-OTD technology is to realize the location by location measurement unit.Each location measurement unit all has an accurate timing source (atomic clock), when location measurement unit (can be to have E-OTD functional mobile phone or terminal) receives from least 3 base station signals, the time difference that arrives mobile phone and location measurement unit from each base station will be calculated, these differences can be used to produce several groups of intersection hyperbolas, and estimate the position thus.The E-OTD scheme can provide than COO, the positioning accuracy that CELL-ID is much higher.But its response speed is slower.In addition, it need improve mobile phone.
3. the technology time of advent (TOA/TA)
Similar with E-OTD, the TOA technology also obtains positional information by signal calculated from the transmission time difference of mobile device to 3 base station.Different is, does not have the use location measuring unit in the TOA system, but the realizing synchronously of wireless network by GPS or atomic clock have been installed on the base station.The positioning accuracy that the TOA system provides in the urban district can be better than COO, but it need be than COO or longer response time of E-OTD.
4. arrive angle technology (AOA)
The prevailing version of AOA technology is called as " small gap direction finding ", it need place 4～12 groups aerial array on each cellular cell website, these antenna array is worked together, thereby can determine that mobile device sends the angle of signal with respect to cellular basestation.When several cellular basestations had all been found the angle of this signal source, they drew ray from the base station along the angle that draws respectively so, and the intersection point of these rays has been exactly the position of mobile phone.This Technology Need carries out upgrading to existing network, especially having relatively high expectations to antenna for base station.
Summary of the invention
The objective of the invention is at the deficiencies in the prior art, provide a kind of need not that existing communication network is transformed, the only theoretical prediction and field test match mutually that covers by signal, the data of being imported in the time of maybe will locating are inquired about comparison with the data of gathering in advance, just can realize the network positions algorithm of higher positioning accuracy and very fast computational speed.
The objective of the invention is to be achieved through the following technical solutions: a kind of localization method based on communication network may further comprise the steps:
(1) network data on the spot of the representative subregion of collection;
(2) set up model algorithm according to collecting data, algorithm is made up of theoretical model algorithm and comparison query algorithm;
(3) locator data of input anchor point;
(4) if network data acquisition has on the spot been carried out in this zone, adopt the comparison query algorithm to calculate, its result is as the result of this localization method; If network data acquisition is not on the spot carried out in this zone, then adopt the theoretical model algorithm to calculate, its result is as the result of this localization method.
Further, the locator data of the network data on the spot of described step (1) and described step (3) includes and is not higher than seven groups cell parameter, and every group of parameter comprises the Timing Advance of area code, cell id, main plot and the signal strength signal intensity that antenna for base station sent of respective cell.
The present invention has following technique effect:
1, positioning function is utilized the present technique invention, can realize the location to travelling carriage in the scope that communication network covers, and positioning accuracy covers relevant with the accuracy of propagation forecast model with the signal of communication network.
2, data statistics function, present technique invention can be added up drive test data on the spot, and adjusts parameter automatically, so that the propagation forecast model is more realistic.
3, the evaluation function that data evaluation analysis, present technique invention are adopted can by searching the algorithm of extreme point, be oriented the longitude and latitude of terminal position to the evaluation of comparing of mobile station signal intensity data dative point data.
Description of drawings
Fig. 1 is an overview flow chart of the present invention;
Fig. 2 is a theoretical model algorithm flow chart of the present invention;
Fig. 3 is a comparison query algorithm flow chart of the present invention;
Fig. 4 is the theoretical model algorithm matched curve figure of the embodiment of the invention;
Fig. 5 is the theoretical model algorithm grid chart of the embodiment of the invention;
Fig. 6 is the comparison query algorithm respective cell grid chart of the embodiment of the invention;
Fig. 7 is the linear blank map of the comparison query algorithm grid signal strength signal intensity of the embodiment of the invention.
Embodiment
The final result calculated of the present invention is a latitude and longitude value, and is used on the digital computer and calculates.For versatility and the accuracy of taking into account algorithm, to having or not two kinds of situations of network data acquisition on the spot, the present invention adopts two kinds of different algorithms to calculate.Be theoretical model algorithm and comparison query algorithm, these two kinds of algorithms have detailed introduction in following examples explanations, and the comparison query arithmetic accuracy is higher, but need gather data on the spot, and the theoretical model algorithm need not to carry out data acquisition on the spot, but precision is relatively poor.Therefore the present invention adopts query method to calculate earlier, if the comparison query algorithm does not have result of calculation, then uses the theoretical model algorithm computation instead.
The realization of theoretical model algorithm is at first to set up a grid with certain-length and width in current service cell, length can be made as 10～15m, and (present embodiment length is 0.0001 latitude, be about 11.1m), width can be made as 9～12m (the present embodiment width is 0.0001 latitude, is about 9.59m).The distance of lattice point and each base station is just decided like this, and, signal strength signal intensity by peripheral base station that travelling carriage obtains, theoretical prediction model according to the network signal covering, the parameter of theoretical prediction model can suitably be adjusted according to actual test data, parameter calculated by the measured data in representative zone and draws, and these parameters are used for the communication network of different regions, signal strength signal intensity can be converted into the distance of travelling carriage to the base station; Then, just can set up evaluation function, the actual range of each lattice point and each base station in the evaluation region and the distance of coming that converts according to signal strength signal intensity are done an overall assessment, get a similarity preferably the lattice point longitude and latitude export as result of calculation.In addition, evaluation region determines that the i.e. distribution of grid will be determined according to the cell parameter of network.
The realization of comparison query algorithm is that first communication grid to the specific region carries out data acquisition, and will collect data and insert grid, grid is corresponding one by one with the sub-district, length can be made as 10～15m, and (present embodiment length is 0.0001 latitude, be about 11.1m), width can be made as 9～12m (the present embodiment width is 0.0001 latitude, is about 9.59m).When data are inserted the grid lattice point, the signal strength signal intensity of all lattice points is carried out the linearity filling according to the signal strength signal intensity of collection point and the position relation of collection point and lattice point.When the location, the signal strength signal intensity of input and the signal strength signal intensity of respective cell lattice point are compared, find out qualified lattice point set, the longitude and latitude mean value of the lattice point that all are found out is as a result of exported again.
Describe specific embodiments of the invention below with reference to the accompanying drawings in detail.
As shown in Figure 1, the embodiment of the invention mainly comprises following step (wherein first and second step is the algorithm establishment step, and third and fourth step is the algorithm computation process steps) from the last positioning result output of being established to of algorithm model.
The first step: earlier network data acquisition is on the spot carried out in representative subregion, if the cell parameter of the network of the data owner locality that is collected comprises the signal strength signal intensity that antenna for base station sent of area code (LAC), cell id (CID), Timing Advance (TA) and corresponding CID.
Second step: set up model algorithm according to collecting data, algorithm is made up of theoretical model algorithm and comparison query algorithm two parts.The process of setting up of present embodiment theoretical model algorithm is exactly according to the electromagnetic wave propagation characteristic, with the process of the data fitting theoretical model algorithm parameter that collects; The foundation of present embodiment comparison query algorithm is that the data based provincial characteristics that will collect is earlier classified, and according to the power of the signal strength signal intensity of collection point and latitude and longitude value the lattice point in the whole zone is carried out linearity again and fills.
So far, algorithm has been set up and has been finished, and below is the computational process of algorithm.
The 3rd step: the locator data input of present embodiment.The data of input also comprise area code (LAC), cell id (CID), Timing Advance (TA), and the signal strength signal intensity that antenna for base station sent of corresponding CID, with set up model algorithm data format be the same.
The 4th step: present embodiment adopts comparison query algorithm computation longitude and latitude earlier, if there are area grid lattice point data in the specific region, then the comparison query arithmetic result is as the result of calculation of present embodiment; If, do not have area grid lattice point data on the spot because does not gather the specific region, then to use the theoretical model algorithm instead and calculate, the theoretical model arithmetic result is as the result of this location algorithm.
As shown in Figure 2, if 1. the of present embodiment theoretical model algorithm goes on foot the cell parameter of the network of the data owner locality that data acquisition step collected on the spot, comprise area code (LAC), cell id (CID), and the signal strength signal intensity that antenna for base station sent of corresponding CID.
After data acquisition is arrived on the spot, just can carry out and 2. go on foot work,, determine the model parameter of local real network environment these data and theoretical model match.Curve fit figure shown in the accompanying drawing 4 is the model parameter fitted figure in the urban district, before curve fit, earlier test point is divided into three types, promptly shadow region and the third special circumstances direct projection situation, urban district in simulate the also definite parameter of three formula according to these three kinds of situations in the urban district in.Formula and parameter are as follows, also are (y represents the signal strength signal intensity received, and x represents to have the potential range of the point of this signal strength values apart from the base station) shown in the accompanying drawing 4:
Direct projection situation: y=-12.111Ln (x)+122.97 in the urban district
Shadow region in the urban district: y=-18.346Ln (x)+151.28
The third special circumstances: y=-13.95Ln (x)+109.54
3. the of present embodiment theoretical model algorithm goes on foot the locator data input step and is meant that model is in operation, the input of the external data when just calculating longitude and latitude, the data owner that this step obtained will comprise the signal strength signal intensity that antenna for base station sent of LAC, CID, corresponding CID and the Timing Advance (TA) of main plot.At present, most mobile module can both obtain the signal strength signal intensity that is sent of 7 CID respective base station antennas on every side from network.
4. the of present embodiment theoretical model algorithm goes on foot work, and the formula that utilizes match to come out exactly converts 7 signal strength values (y) that reality obtains to 7 distance values (x).The formula that match is come out has three, generally presses following criterion when selecting formula.
Direct projection region decision standard:
If signal strength signal intensity, thinks that this signal strength signal intensity belongs to the direct projection area type greater than 60dbm.
If several antennas are arranged in same geographical position, analyze the signal of these several co-located antennas; If wherein the signal strength signal intensity of all the other co-located antennas of the signal intensity ratio of a certain antenna all is higher than 8dbm, think that the signal strength signal intensity of this antenna belongs to the direct projection area type.
If an antenna does not have other antenna of same geographic location, think that the signal strength signal intensity of this antenna belongs to the direct projection area type.
The criterion of shadow region and other regional criterion:
If several antennas are arranged in same geographical position, analyze the signal of these several co-located antennas, if the signal strength signal intensity of arbitrary antenna all is higher than 8dbm unlike the signal strength signal intensity of all the other antennas, think that the highest aerial signal intensity belongs to the shadow region type; Remaining is other area type.
Determine to utilize the distance of fitting formula compute location point behind the affiliated area of collection point apart from the base station.
Present embodiment theoretical model algorithm the 5. the step be exactly according to actual conditions, set up network.Can utilize LAC, CID and TA parameter earlier, determine evaluation region, in evaluation region, set up grid again.The grid length that present embodiment theoretical model algorithm is set up is 0.0001 latitude (being about 11.1m), and width is 0.0001 longitude (being about 9.59m).The net region of setting up is according to the difference of antenna type and difference: in the urban district, the general employing of each network base station three secondary dual polarization transmitting antennas are for this situation, after knowing the deflection of antenna, can set up grid shown in accompanying drawing 5, wherein, the O point is the position of base station; The OA direction is a direct north; The OB direction be antenna towards; Angle beta is the deflection of antenna; Apart from d is the rough distance of travelling carriage apart from the base station, and by formula d=500 * TA calculates, and unit is a rice; Angle [alpha] is about 150 degree.If in the suburb or the rural area, what the communication network antenna for base station adopted is omnidirectional antenna, and then angle [alpha] is got 360 degree, and promptly the net region of being set up is an annulus.After setting up network, lattice to around the distance of all base stations just decide.
Present embodiment theoretical model algorithm the 6. the step be to set up appraisement system, most important is exactly to choose evaluation function.The evaluation function of present embodiment theoretical model algorithm picks is:
Wherein,
λ
iBe weight, be taken as signal strength signal intensity.The evaluation function result calculated is called quality, has reflected the relative deviation of this point and ideal point.
Present embodiment theoretical model algorithm the 7. the step utilize the 6. go on foot selected evaluation function with the 4. 7 distance values being converted to of step and the 5. go on foot in the grid of being set up all lattice points and estimate apart from the gauged distance value of corresponding base station, after all grid lattice point evaluations are finished, quality summation near nine some zones each lattice point, search for extreme point then, determine the best 5-10 of a quality extreme point, and their longitude and latitude and quality are as a result of exported.
In addition, because existing network has adopted dual-frequency network mostly, promptly adopted two frequency ranges to communicate, communication frequency is high more, and the rate of decay of signal is fast more.The error that causes for the difference of revising owing to operating frequency, so, if the working frequency range of network using is 935MHz-960MHz, calculate apart from the time, calculate after intensity deducted 1.5dbm; If the working frequency range that adopts is that 1805MHz-1877MHz is an operating frequency, calculate apart from the time, calculate after intensity added 2dbm.
So far the declarative description of theoretical model algorithm finishes, below the algorithm of beginning descriptive statistics model.
As shown in Figure 3, if 1. the of present embodiment comparison query algorithm goes on foot the cell parameter of the network of the data owner locality that data acquisition step collected on the spot, comprise area code (LAC), cell id (CID), and the signal strength signal intensity that antenna for base station sent of corresponding CID.
2. the step is exactly to set up network to present embodiment comparison query algorithm the.The grid length of setting up is 0.0001 latitude (being about 11.1m), and width is 0.0001 longitude (being about 9.59m).Setting up the net region is to need to use statistical model positioned area, the zone that just needs to carry out data acquisition.
Present embodiment comparison query algorithm the 3. the step be that the data that collect are inserted grid, make it corresponding one by one with lattice point.As shown in Figure 6, before inserting, determine the physical location of collection point earlier according to the longitude and latitude of collection point A, B, C.LAC, CID according to collection point A, B, C classifies signal strength signal intensity again, and be existing for algorithm is described, supposes that the data of collection point A, B, C contain the signal strength signal intensity of same LAC, CID, and all just be on the grid point.
If the signal strength signal intensity at A place is 60dbm, the signal strength signal intensity at B place is 80dbm, and the signal strength signal intensity at C place is 50dbm, then to being in linear successively filling of grid point d, e, f, g, h, i, j, k, l, m, n, o in the triangle ABC, as shown in Figure 7.All lattice points to the grid in each CID are all inserted signal strength signal intensity by this algorithm, till the data processing of all collections is intact.
4. the step is the input of locator data to present embodiment comparison query algorithm the, the data that this step is imported and the theoretical model algorithm the 3. data imported of step is the same, the input of the external data when just calculating longitude and latitude, the data owner that is obtained will comprise the signal strength signal intensity that antenna for base station sent of 7 groups of LAC, CID and corresponding CID.
Present embodiment comparison query algorithm the 5. the step be the main plot CID that is imported during according to the location, determine the respective cell grid of coupling.
Present embodiment comparison query algorithm the 6. the step be that the signal strength signal intensity of input contrasts with the signal strength signal intensity of inserting this CID grid during with the location, find out the point that difference in signal strength all is not more than 5dbm, again the mean value of the longitude and latitude of the point of finding out is as a result of exported.。
The foregoing description is used for the present invention that explains, rather than limits the invention, and in the protection range of spirit of the present invention and claim, any modification and change to the present invention makes all fall into protection scope of the present invention.
Claims (5)
1. the localization method based on communication network is characterized in that, may further comprise the steps:
(1) gathers the network data on the spot of representative subregion.
(2) set up model algorithm according to collecting data, algorithm is made up of theoretical model algorithm and comparison query algorithm.
(3) locator data of input anchor point.
(4) if network data acquisition has on the spot been carried out in this zone, adopt the comparison query algorithm to calculate, its result is as the result of this localization method; If network data acquisition is not on the spot carried out in this zone, then adopt the theoretical model algorithm to calculate, its result is as the result of this localization method.
2. according to the described localization method of claim 1, it is characterized in that, the locator data of the network data on the spot of described step (1) and described step (3) includes and is not higher than seven groups cell parameter, and every group of parameter comprises the Timing Advance of area code, cell id, main plot and the signal strength signal intensity that antenna for base station sent of respective cell.
3. according to the described localization method of claim 1, it is characterized in that in the described step (2), described theoretical model algorithm comprises following step:
(1) test zone is divided into direct projection zone, shadow region and other regional three parts, these three kinds of zones are simulated three formula and determine parameter, formula is as follows:
Direct projection zone: y=-12.111Ln (x)+122.97
Shadow region: y=-18.346Ln (x)+151.28
Other zone: y=-13.95Ln (x)+109.54
Wherein, y represents the signal strength signal intensity received, and x represents to have the distance of the point of this signal strength values apart from the base station;
(2) gather the locator data of any point, locator data comprises and is not higher than seven groups cell parameter that every group of parameter comprises the Timing Advance of area code, cell id, main plot and the signal strength signal intensity that antenna for base station sent of respective cell;
(3) judge collection point affiliated area and compute location point distance apart from the base station:
Direct projection region decision standard:
If 1. signal strength signal intensity is greater than 60dbm, think that this signal strength signal intensity belongs to the direct projection area type;
If 2. several antennas are arranged in same geographical position, analyze the signal of these several co-located antennas; If wherein the signal strength signal intensity of all the other co-located antennas of the signal intensity ratio of a certain antenna all is higher than 8dbm, think that the signal strength signal intensity of this antenna belongs to the direct projection area type
If 3. an antenna does not have other antenna of same geographic location, think that the signal strength signal intensity of this antenna belongs to the direct projection area type;
The criterion of shadow region and other regional criterion:
If several antennas are arranged in same geographical position, analyze the signal of these several co-located antennas,
If the signal strength signal intensity of arbitrary antenna all is higher than 8dbm unlike the signal strength signal intensity of all the other antennas, think that the highest aerial signal intensity belongs to the shadow region type; Remaining is other area type;
Determine to utilize the distance of fitting formula compute location point behind the affiliated area of collection point apart from the base station;
(4) utilize the Timing Advance of area code, cell id and main plot to determine evaluation region, in evaluation region, set up grid again; After setting up grid, lattice point to around the distance of all base stations just decide;
(5) set up appraisement system, choose evaluation function
Wherein,
λ
iBe signal strength signal intensity.The evaluation function result calculated is called quality, has reflected
The relative deviation of this point and ideal point.
(6) utilize in the grid that selected evaluation function of (5) step set up for (4) step all lattice points to estimate apart from the gauged distance value of corresponding base station, after all grid lattice point evaluations are finished, quality summation near nine some zones each lattice point, search for extreme point then, determine the best 5-10 of a quality extreme point, and their longitude and latitude and quality are as a result of exported.
4. localization method according to claim 3, it is characterized in that, in described step (1) and the step (5), used signal strength values is handled by the following method: if the working frequency range of network using is 935MHz-960MHz, signal strength signal intensity is deducted 1.5dbm; If the working frequency range of network using is 1805MHz-1877MHz, signal strength signal intensity is added 2dbm.
5. localization method according to claim 1 is characterized in that, in the described step (2), described comparison query algorithm comprises following step:
(1) set up grid according to the network data on the spot that collects, the grid length of foundation is 10～15m, and width is 9～12m:
The network data on the spot that (2) will collect is inserted grid, makes it corresponding one by one with lattice point;
(3), determine the respective cell grid of coupling according to cell id.
(4) signal strength signal intensity with input contrasts with the signal strength signal intensity of inserting this CID grid, finds out the point that difference in signal strength all is not more than 5dbm, the mean value of the longitude and latitude of the point of finding out is as a result of exported again.
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Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102186238A (en) * | 2011-04-07 | 2011-09-14 | 北京邮电大学 | Positioning method and device based on electronic map |
| CN101588594B (en) * | 2008-05-22 | 2011-12-14 | 中国移动通信集团上海有限公司 | Method and device for positioning test point and corresponding test point to test data |
| CN102300151A (en) * | 2010-06-24 | 2011-12-28 | 无锡中星微电子有限公司 | Method of positioning prompt and mobile terminal |
| CN103179658A (en) * | 2011-12-22 | 2013-06-26 | 华为技术有限公司 | Method for positioning by using wireless signals and positioning server |
| CN103942916A (en) * | 2014-03-27 | 2014-07-23 | 上海理工大学 | Automobile danger automatic alarming device |
| CN104602339A (en) * | 2014-12-29 | 2015-05-06 | 三维通信股份有限公司 | Localization refinement method of network edge node of wireless sensor |
| WO2016150084A1 (en) * | 2015-03-24 | 2016-09-29 | 中兴通讯股份有限公司 | Method and apparatus for computing distance from mobile station to cell |
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| FI105596B (en) * | 1996-05-27 | 2000-09-15 | Nokia Networks Oy | A method for determining the location of a mobile station |
| FI109839B (en) * | 2000-08-22 | 2002-10-15 | Nokia Corp | A method for locating a mobile station |
| ES2257477T3 (en) * | 2001-04-20 | 2006-08-01 | Lg Electronics Inc. | ESTIMATION OF THE POSITION OF A MOBILE COMMUNICATION TERMINAL THROUGH THE COMBINATION OF INTERCHANGED SIGNAL MEASURES BETWEEN THE MOBILE TERMINAL AND BASE STATIONS. |
| CN100461871C (en) * | 2002-08-16 | 2009-02-11 | 中兴通讯股份有限公司 | Mobile positiong method used for raising precision of defining mobile station position |
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| CN101588594B (en) * | 2008-05-22 | 2011-12-14 | 中国移动通信集团上海有限公司 | Method and device for positioning test point and corresponding test point to test data |
| CN102300151A (en) * | 2010-06-24 | 2011-12-28 | 无锡中星微电子有限公司 | Method of positioning prompt and mobile terminal |
| CN102186238B (en) * | 2011-04-07 | 2014-06-04 | 北京邮电大学 | Positioning method and device based on electronic map |
| CN102186238A (en) * | 2011-04-07 | 2011-09-14 | 北京邮电大学 | Positioning method and device based on electronic map |
| CN103179658B (en) * | 2011-12-22 | 2017-04-12 | 华为技术有限公司 | Method for positioning by using wireless signals and positioning server |
| CN103179658A (en) * | 2011-12-22 | 2013-06-26 | 华为技术有限公司 | Method for positioning by using wireless signals and positioning server |
| WO2013091580A1 (en) * | 2011-12-22 | 2013-06-27 | 华为技术有限公司 | Wireless signal positioning method and positioning server |
| US10306415B2 (en) | 2011-12-22 | 2019-05-28 | Huawei Technologies Co., Ltd. | Method for positioning using wireless signal and positioning server |
| CN103942916A (en) * | 2014-03-27 | 2014-07-23 | 上海理工大学 | Automobile danger automatic alarming device |
| CN104602339B (en) * | 2014-12-29 | 2018-07-10 | 三维通信股份有限公司 | A kind of positioning refinement method of wireless sensor network fringe node |
| CN104602339A (en) * | 2014-12-29 | 2015-05-06 | 三维通信股份有限公司 | Localization refinement method of network edge node of wireless sensor |
| CN106162862A (en) * | 2015-03-24 | 2016-11-23 | 中兴通讯股份有限公司 | Calculate the mobile station method and device to community distance |
| WO2016150084A1 (en) * | 2015-03-24 | 2016-09-29 | 中兴通讯股份有限公司 | Method and apparatus for computing distance from mobile station to cell |
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