# The method of determining the location of a mobile subscriber

(57) Abstract:

The invention relates to radar systems and can be used in cellular communication systems to determine the location of a mobile station (MS). Achievable technical result of the invention is to improve the accuracy of the positioning of the MS for each of the N base stations. A distinctive feature of the proposed method is that it determines the range of possible values of error in the estimated propagation time of the signal location and density functions the probability distribution of these values of the error transform of the correlation metric, integrating it over the domain of possible values of the error with a weight equal to the density of the probability distribution of the values of the error, and forming the transformed correlation metric, determine the weight of the transformed correlation metric, and for evaluating the location of the MS take the point the most likely location for which the weighted sum of values of the transformed correlation metrics corresponding to the time of signal propagation between this point and the corresponding base station has a maximum. The simulation results show that prejorative relates to the field of radar and can be used in cellular communication systems to determine the location of the mobile station.The constant expansion of services in cellular mobile communication makes it relevant to the decision problem of determining the location of the subscriber mobile station (MS). Standards for modern cellular communication system include requirements for the accuracy of locations. For example, in 1998, for American standards has established a requirement to ensure the accuracy not worse than 125 meters in 67% of cases. Currently, these requirements tend to increase. In this context, the task of developing more accurate methods of location is particularly important.In many situations, an effective method of radar object is Dalnerechensky, in which the distances between the MS and each of the multiple base stations (BS) are valued at the time of signal propagation. Estimates of these distances and the known coordinates of each of the BS make it possible to calculate the coordinates of the MC. Examples of such methods location can serve as the methods described in patents WO # 98/14018: Method and system for mobile location estimation, M. Wylie, 2 April 1998; US # 5732354: Method and apparatus for determining the location of mobile telephone, March 24, 1998; US # 5736964: Method and apparatus for location finding in a CDMA system. April 7, 1997.A serious problem of location errors are location, to resort to a higher power the increase in the duration of the transmitted signal locations, as well as to the transfer signal sequence locations instead of one, and the use of special algorithms of data processing. An example is the method described in patent US # 5736964: Method and apparatus for location finding in a CDMA system. April 7, 1997, aims to develop a cheap method of locating a mobile subscriber. The method is based on the evaluation of the propagation time of the signal between the MS and each of the multiple base stations. This assessment is done by the signal being modulated with a pseudo-random sequence. This determines the arrival time of the front fronts of each elementary symbol (chip) from a group of predefined chip pseudo-random sequence.This method is patented in several versions, which include the use of signals from only the forward or reverse channel communication systems, as well as the location of the signals transmitted in two directions - forward and reverse.In the case of locations on the backward channel all active BS immediately after receiving the command locations begin receiving and storing information about the rooms of the reference chip signal caller and the time of their arrival. Pairings chip/time with informatie position of the subscriber.The disadvantage of this method is to reduce the accuracy of the location in terms of fading, multipath and high noise level. For high accuracy location requires a high ratio of signal power to interference power, the significant duration of the transmitted signal locations, and the transfer signal sequence locations instead of one. Under conditions of cellular communication systems such measures lead to more traffic, increase the level of intra-system interference and system capacity reduction.Closest to the claimed solution is the way described in the book "Wireless Location in CDMA Cellular Radio Systems" by James J. Gaffery Jr. /University of Cincinnati/ Cincinnati, OH, USA./ Kluwer Academic Publishers. 2000./ Electronic Services: http://www.wkap.nl, Sections 1.3.1, 2.1.This way the location is the following:- perform receiving location signals propagating between the MS and each of the 3 sites,

- for each signal location form a metric based on the correlation function of this signal locations with a reference signal, with the mutual time delay corresponding to the possible values of the estimated propagation time of the signal locations,

- determine the time and spread the trick is maximum, and thus form a set of 3 estimates of times of distribution,

- lot of 3 ratings time distribution form many estimates of the distances between the MS and each of the 3 sites,

- on the set of points of the proposed location of the MS building line provisions, each of which represents a circle with center at the point of location of the corresponding BS and a radius equal to the corresponding value of the distance

- select all possible pairs of lines of position, and for each pair build a new line position,

- as a straight line passing through the intersection point, if the lines of the provisions of this pair intersect,

- total tangent, if the lines of the provisions of this couple touch each other,

- a straight line, equidistant from the closest to each other of points, lines provisions of this couple, if they have no common points,

- form estimation of the MS location as the point of intersection of new lines of situation.The disadvantage of this method is a significant reduction in the accuracy of the location in terms of noise, fading, intra-system interference. Thus the correlation function of the signal location is seriously distorted. The result of such distortions are large errors in the estimates of time is assumed possible to achieve arbitrarily high accuracy potential measurements at high signal-to - the obstacle. However, this assumption is usually not performed. For example, the system clock, which measured the times of transmission and reception signals of a location, have a certain error, which can be quite significant. Any error hours, typical even for systems with synchronous BS, will lead to additional locations errors.The objective of the present invention is to increase the accuracy of the positioning of the MS.To solve this problem in the method of determining the location of a mobile subscriber, namely, that shall receive location signals propagating between the MS and each of the N base stations, each signal location form a correlation metric based on the correlation function of this signal locations with a reference signal, with the mutual time delay corresponding to the possible values of the estimated propagation time of the signal locations, form the estimate of the MS location,

added the following operations: for each of the N base stations

- determine the range of possible values of error in the estimated propagation time of the signal locations and the density function of raspredeleniya weight, equal to the density of the probability distribution of the values of the error, thus forming a transformed metric

- determine the weight of the converted metric

for the estimation of the MS location take the point the most likely location for which the weighted sum of values of the transformed metrics corresponding to the time of signal propagation between this point and the corresponding base station has a maximum.And the point of signal reception location can be MS, and the points - a lot of BS, or, conversely, point signal transmission location is MS, and the reception points is a lot of BS.The correlation metric form, for example, as a module or unit square of the correlation function between the signal location and a reference signal, and the correlation function can be formed as a sequence of correlation values between the input and reference signals at a mutual time delay corresponding to the sequence of possible values of the estimated propagation time of the signal location.The density function of the probability distribution of the error in the estimated propagation time of the signal locations are determined and the maximum values of mutual error of the system clock MS and BS, or on the basis of the analysis of the input signal and the generated metrics.The weight ratio of the transformed correlation metric is determined depending on the power ratio signal location to the interference power in the relevant distribution channel, for example, is proportional to the ratio of signal to noise.To find the point the most probable location of the MS on the set of points of the proposed location of the MS determine the area of the most probable location of the MS, from the region of the most probable location of the MS form many test points, evenly covering the entire area, so that neighboring points are at a distance not exceeding the permissible error of estimate of the location for each point from the set of test points form the total metric as a weighted sum of the values of the transformed metrics corresponding to the time of signal propagation between this point and the corresponding base station, for evaluating location take the test point with the maximum value of the total metric.Comparative analysis of the way location Mobitec as improves the accuracy of locating and determining the location of a mobile subscriber.Comparative analysis of the proposed method with other technical solutions in this field of technology is not allowed to reveal the characteristics stated in the characterizing part of the claims. Therefore, the inventive method of determining the location of a mobile subscriber meets the criteria of "novelty", "technical solution", "significant differences" and has the obviousness of the solution.Graphic materials explaining the invention

Fig. 1 is an example of the correlation metrics generated for the three base stations.Fig.2 - examples of the probability density distribution of error values.Fig. 3 is an example of the combined correlation metrics generated for the three base stations.Fig.4 - determination of the maximum total correlation metric.Fig.5 is a block diagram of the device location.Fig.6 is an example implementation of the quadrature demodulator.Fig.7 is an example of the execution of a block forming a correlation metric.Fig.8 is an example of the execution of a block transform of the correlation metrics.Fig.9 - the algorithm of the processing unit estimates the coordinates.Fig. 10 is an exemplary algorithm forms the of the total metric.Fig.12 - comparative characteristics of the claimed method, location and method of the prototype.The proposed method consists in the following:

- perform receiving location signals propagating between the MS and each of the N base stations,

- for each signal location form a correlation metric based on the correlation function of this signal locations with a reference signal, with the mutual time delay corresponding to the possible values of the estimated propagation time of the signal locations,

for each of the N base stations

- determine the range of possible values of error in the estimated propagation time of the signal location and function of the density of the probability distribution of these values, error,

- converts metric, integrating it over the domain of possible values of the error with a weight equal to the density of the probability distribution of the values of the error; thus form a transformed metric;

- determine the weight of the converted metric;

for the estimation of the MS location take the point the most likely location for which the weighted sum of values of the transformed metrics corresponding to the time distribution of signali is MS, and by points - the set of N base stations and, on the contrary, point signal transmission location is MS, and the points of acceptance - many N BS;

- correlation metric form as a module or unit square of the correlation function between the signal location and a reference signal;

- function correlation form as a sequence of correlation values between the input and reference signals at a mutual time delay corresponding to the sequence of possible values of the estimated propagation time of the signal location;

the density function of the probability distribution of the error in the estimated propagation time of the signal location is determined on the basis of a priori data about the source of these errors, such as the density function of the probability distribution of the error in the estimated propagation time of the signal locations define uniform in the region between the minimum and maximum values of mutual error of the system clock MS and BS, or on the basis of the analysis of the input signal and the generated metrics,

- the weight of the transformed metric is determined depending on the power ratio signal location to the interference power in the relevant distribution channel, Napanee MS on the set of points of the proposed location of the MS determine the area of the most probable location of the MS, from the area of the most probable location of the MS form many test points, evenly covering the entire area, so that neighboring points are at a distance not exceeding the permissible error of estimate of the location for each point from the set of test points form the total metric as a weighted sum of the values of the transformed metrics corresponding to the time of signal propagation between this point and the corresponding base station, for evaluating location take the test point with the maximum value of the total metric.According to the claimed method shall receive location signals propagating between the MS and each of the N base stations. Thus there are two options. First, when the location signals transmitted by multiple signal sources and received MS. Signal sources can be a base station of a modern cellular communication systems or satellites of the GPS system (Global Positioning System). In the second embodiment, the MS transmits a signal location, which is adopted by several base stations. This method eliminates the complexity of equipment MS, as the most complex operations are performed on the BS.Admission to each is rnym signal, in mutual time delay corresponding to the possible values of the estimated propagation time of the signal locations. It is also called the correlation metric. Usually, as a correlation metric using the module or the square of the modulus of the correlation function between the signal location and a reference signal. Sometimes the correlation metric form as the sum of squares of modules of the correlation function, formed by successive time intervals of the input signal.In digital receivers correlation function form as a sequence of digital values of correlation between the input and reference signals at a mutual time delay corresponding to the sequence of possible values of the estimated propagation time of the signal locations. An example of the correlation metrics formed on each of the 3 BS shown in Fig.1.The first direction to increase the accuracy in the inventive solution is joint processing of the correlation metrics generated by signals of different locations BS.In traditional methods, locations, including the method prototype, perform an independent assessment of the propagation time of the signal nama evaluation times of the signal propagation is not possible to achieve the best efficiency locations since any deviation of the correlation metrics due to noise or fading cause location errors.In accordance with the first direction in the present method is proposed for each point of the area of the proposed location of the MS to sum independent of the correlation metric, corresponding to different base stations.This summation can improve accuracy through compensation of random deviations of the correlation of metrics in their summation. Thus, the threshold decreases the required signal-to-noise ratio, which allows to lower the signal strength, location and, consequently, the level of intra-system interference.The second direction of increasing the accuracy of the locations used in the inventive solution, it is the optimal use of information about possible errors of measurement associated with, for example, a possible misalignment of the system clock or with no direct beam propagation. When the generated correlation metric M(t) and the available information about the probability density of the error W

_{ER}(t) the probability density function of different values of the propagation time of the signal is proportional to the metric, converted as follows:

< / BR>

Here M(t) - correlation metric, W

_{ER}(

_{0}) is the discrete probability density function of the error,

_{0}- step changes in time estimates.The range of possible values of error (

_{min},

_{max}) can be identified, for example, on the basis of information about the error of the system clock. Examples of density functions the probability distribution of the errors is shown in Fig.2. The bottom graph corresponds to the case of no measurement errors, the average uniform density, which presents many of the same probability values distributed in the range from

_{min}to

_{maxk}can be selected, for example, proportional or equal to

_{k}(k=1,... N).Thus, for each point in the area of the proposed location of the MS can be determined cumulative metric:

< / BR>

The example is formed of a metric M

_{SUM}(x, y) shown in Fig. 3. To determine the location you want to find the point with the maximum metric value M

_{SUM}(x, y).This total metric is generated for each point of the proposed location, allows you to use information about the distribution channels contained in the input implement and correlation metrics, as well as information about possible measurement errors and, hence, increase the efficiency of locations.Then the problem of estimating the location of the MS is reduced to the determination of the maximum of the function M

_{SUM}(x, y). Obviously, there are many ways of determining the maximum value of a function of two variables

_{SUM}and the set of points of the proposed location of the MS determine the area of the most probable location of MS.First, for each BS determines the most probable value propagation time T, for example, as the minimum time value, wherein the value metric has a local maximum, exceeding a certain threshold. On the basis of this assessment form the point of the initial estimate of the location. An initial assessment of the location determine, for example, by the method proposed in the prototype Wireless Location in CDMA Cellular Radio Systems" by James J. Gaffery Jr./University of Cincinnati/ Cincinnati, OH, USA. / Kluwer Academic Publishers. 2000./ Electronic Services: http: //www.wkap.nl, Sections 1.3.1, 2.1.To a lot of the most likely estimates of times of distribution of T

_{1}, T

_{2},... T

_{n}signal to each of the N BS form many relevant estimates of distances;

on many points the estimated location of the MS build N position line, each of which represents a circle with center at the point of location of the corresponding BS and a radius equal to the corresponding value of the distance

choose various pairs of lines of position, and for each pair build a new line position as a straight line,

a) passing through the intersection point, if the lines of the provisions of this pair intersect,

b) General kastelic other points of the lines of the provisions of this pair, if they have no common points;

from all points of intersection of new lines of position form the point with coordinates equal to the average of the coordinate values, and take the point of the initial estimate of the location.Then determine the area of the most probable location of the MS as at some point the initial estimate of the location and the size of the neighborhood is determined a priori data about the possible measurement errors.From the area of the most probable location of the MS form many test points, evenly covering the entire area, so that neighboring points are at a distance not exceeding the value of the allowable error of the estimate propagation time of the signal. For example, points can be located at the nodes of a square grid (see Fig.4).For each point of the formed sets determine the time t

_{k}(x, y) (k=1... N) of signal propagation between this point and the corresponding base station, and then form the total value of the metric M

_{SUM}(t

_{k}(x, y)) (3). For the assessment of location take the point with the maximum value of the total metric.The inventive method l the AI base stations,

2 - quadrature demodulator,

3 - the block of formation of the correlation metrics,

4 - block formation probability density error,

5 is a block transform of the correlation metrics,

6 - the evaluation unit of the signal-to-noise ratio,

7 is a block generate estimates of coordinates.The device contains N blocks location 1, corresponding to each of the N base stations (BS), at the input of each of which receives the signal locations treated in antenna and RF receiver paths of the corresponding BS. The signal location is a signal with a direct expansion of the spectrum of a pseudo-random sequence (SRP), such as in modern communication systems cdma2000. Unit location 1 each BS includes sequentially connected quadrature demodulator 2, the entrance of which is an input unit location 1, the set of correlation metrics 3, the conversion unit correlation metric 5, a second input connected to the output of the shaping unit density error 4, and the output is the first output of each unit location 1. The output processing unit correlation metric 3 is connected also to the input of the evaluation unit of the signal-to-interference 6, the output of which is stazioni metrics 5 and the output of the evaluation unit of the signal-to-interference 6) of each base station is connected to the inputs of the processing unit estimates a coordinate 7, the output which is the output device.The location signals s

_{1}(t), s

_{2}(t),... s

_{N}(t) are the blocks location 1-1 to 1-N, respectively, each of the N base stations. In each block location 1 received signal in the quadrature demodulator 2, which converts the signal, which leads to the transfer of its spectrum in the region of videocasts, an embodiment of which is shown in Fig.6, where indicated:

8 - generator frequency reference

9 - Phaser,

10 - the first multiplier,

11 - the first filter,

12 - second multiplier,

13 - the second filter.Quadrature demodulator operates as follows. Input signal is supplied to two multiplier 10 and 12. In the multiplier 10 samples of the signal are multiplied by a harmonic signal with a frequency equal to the frequency of the input signal generated in the oscillator frequency reference 8 and the multiplier 12 is on the same reference signal shifted in phase by 90 degrees. With multiplier products signal is supplied to the filters, which filter the zero-frequency region of the spectrum. Thus forming the in-phase I and quadrature Q components of the demodulated signal.Both components of the signal postmarriage correlation metric 3, where indicated:

14 - generator integrated reference signal,

15 - node control delay,

16 - node memory,

17 is a complex multiplier,

18 - the first integrator,

19 - the first squarer,

20 - second integrator,

21 - second squarer,

22 - adder.The set of correlation metrics is as follows. Node 15 control delay sets a certain amount of delay of the reference signal relative to come demodulated signal. The magnitude of potential delays are based on a priori knowledge about the possible time of arrival of a signal. The generator 14 generates two reference signal, which is a video dubs in-phase (I) and quadrature (Q) component of the useful signal. In the complex multiplier 17 is the multiplication of the in-phase and quadrature components of the input signal with the same components of the reference signal by the rules of multiplication of complex numbers. In this case, I and Q components of each of the signals are represented as real and imaginary components of the complex values. The integrators 18 and 20 produce a summation of samples of the real and imaginary parts of the resulting prosum on the output of the adder 22 is formed quadratic correlation value between the input and reference signals. This value with the appropriate value of the delay reference signal is a reference metric and is recorded by the memory node 16, in parallel to the node 16 receives the delay value that is mapped to this reference metric. Next, the control unit delay 15 sets the new value of the delay and the computation of the next count metric. The operation will continue for all possible delay in time of arrival of a signal.Formed in the block 3, the metric entered in block 6 evaluation of the signal-to-noise ratio, which measures the power ratio of the signal to interference power generated by the correlation metric, the unit runs on standard schemes. Formed the metric of the unit 3 is also provided in block 5 transformation of the correlation metrics, there are times the density of the error probability of block 4, which in General is a block of memory in which are recorded the discrete density values of the error probability on the basis of data on the possible source of these errors, as in the examples above (see Fig.2). In block 5, the samples of the correlation metric is converted in accordance with formula (2).In Fig. 8 presents the and,

24 - delay line,

25 - adder,

the 26 - node memory.The conversion unit of the correlation metric is as follows. Every visitor count generated metric is delay line 24 with taps. Delayed signals from the taps of the delay line is coming to the multiplier products 23-1 to 23-m, multiplied by the density of probability of the errors corresponding to the time delay of this tap delay line. The resulting works are added by the adder 25, and then written to the host memory 26. Thus formed all times, the converted metric according to the formula (2).Sets of samples transformed correlation metrics and evaluation of the signal-to-interference from all the BS go on the block generate estimates of coordinates that generates a score for the location of the MS, the algorithm of its operation is shown schematically in Fig.9.First sets of samples transformed correlation metrics M

_{1}, M

_{2}, ... M

_{n}received from each of the N base stations, the formation of the most likely estimates of times of distribution of the respective location signals. An example of this operation is shown schemat is the value determined by the threshold kM

_{max}where k is a factor. Then is determined by the earliest

_{min}the value of the delay time at which the level of the metric exceeds the threshold. In the vicinity of a

_{min}t

_{c}(t

_{c}- the duration of elementary symbol-chip - SRP) is determined by the local maximum. The appropriate time

_{e}

_{e}is the most likely time estimate signal propagation locations.In accordance with estimates of the time distribution is the formation of the initial estimate of the location. This can be done by any known method, for example as described above prototype.Initial assessment of the location is the formation of many test points as described above and illustrated in Fig.4. Then select the test point, for which the total metric has a maximum, which is taken as the estimate of the MS location.To assess the performance of the proposed algorithm locations was conducted computer modeling. The results are illustrated in Fig.12. In Fig. 12-a shows the location of base stations used in the simulation. In Fig. 12-b - dependence of the RMS oshibana: Gaussian noise, Rayleigh fading; Ec/lo is the ratio of the energy of the chip signal to the spectral power of the noise for the most remote BS; number of experiments 500; position MS was chosen randomly inside the dashed rectangle. The results show that the proposed method has the advantage in efficiency of approximately 4 dB. 1. The method of determining the location of the subscriber mobile station, namely, that carry the signal receiving locations, extending between a subscriber's mobile station and each of the N base stations, each signal location at the point of admission form of the correlation metric based on the correlation function of this signal locations with a reference signal, with the mutual time delay corresponding to the possible values of the estimated propagation time of the signal locations, form the estimate of the location of the subscriber mobile station, characterized in that for each of the N base stations determine the range of possible values of error in the estimated propagation time of the signal location and function of the density of the probability distribution of these values of the error transform of the correlation metric, integrating it over the area in the formed correlation metric, determine the weight of the transformed correlation metric for evaluating the location of the subscriber mobile station take the point the most likely location for which the weighted sum of values of the transformed correlation metrics corresponding to the time of signal propagation between this point and the corresponding base station has a maximum.2. The method according to p. 1, characterized in that the point of signal reception location is the subscriber's mobile station, and transfer points - the set of N base stations.3. The method according to p. 1, characterized in that the signal transmission location is the subscriber's mobile station, and the reception points is the set of base stations.4. The method according to p. 1, characterized in that the metric form as a module or unit square of the correlation function between the signal location and a reference signal.5. The method according to p. 1, characterized in that the correlation function is formed as a sequence of correlation values between the input and reference signals at a mutual time delay corresponding to the sequence of possible values of the estimated propagation time of the signal location.7. The method according to p. 1, characterized in that the density function of the probability distribution of the error in the estimated propagation time of the signal locations define uniform in the region between the minimum and maximum values of mutual error of the system clock of the subscriber mobile station and the base station.8. The method according to p. 1, characterized in that the density function of the probability distribution of the error in the estimated propagation time of the signal location is determined on the basis of the analysis of the input signal and the generated metrics.9. The method according to p. 1, characterized in that the weight ratio of the transformed metric is determined depending on the power ratio signal location to the interference power in the relevant distribution channel, for example, is proportional to the ratio of signal to noise.10. The method according to p. 1, characterized in that to find the point the most probable location of the subscriber mobile station in the set of points of the proposed location of the subscriber mobile station determines the region of the most probable location of the mobile station, from the region of the most probable location of the subscriber mobile station pohoata at a distance, not exceeding the size of the allowable error of the estimate of the location for each point from the set of test points form the total metric as a weighted sum of the values of the transformed metrics corresponding to the time of signal propagation between this point and the corresponding base station, for evaluating location take the test point with the maximum value of the total metric.

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