MXPA99002935A - Method and system for mobile location estimation - Google Patents

Abstract

The present invention relates to a method and system for mobile location estimation in which range measurements between the mobile station and a base station are discriminated as being either from a base station which is line of sight with the mobile station or a base station that is non-line of sight with the mobile station (22). Non-line of sight error present in range measurements from base stations that are non-line of sight with the mobile station is corrected (24). A reconstructed line of sight range measurement is established from the correction of the non-line of sight error. The reconstructed line of sight range measurements can be used with range measurements of base stations determined to be line of sight for accurately locating the mobile station (26).

Description

METHOD AND SYSTEM FOR ESTIMATING A MOBILE LOCATION This application claims the benefit of the • U.S. Provisional Application No. 60 / 027,453 entitled Off-Line Visual Problem in Estimation of Mobile Location submitted by the Requesters on September 27, 1996, incorporated herein by reference.

BACKGROUND OF THE INVENTION 1. FIELD OF THE INVENTION The present invention relates to a method and a system for estimating the location of a mobile station in which the base stations that are in visual line of the mobile station and the stations can be determined. base that are not in the visual line of the base station. Errors in the base station signals generated from determined off-line base stations are reduced to provide an improved estimate of mobile station location. 2. DESCRIPTION OF THE RELATED TECHNIQUE The mobile location estimate determines a geographic estimate of the location of a mobile station. The mobile location estimate is useful in the handling of groups of mobile stations, information services that depend on # la, location > billing services that depend on the location and location of the 911 Emergency number of a mobile station. The enhanced 911 is designed to automatically transmit a user's number to a public safety answering point (PSAP). By implementing enhanced 911 in a wireless network, wireless service providers provide a two-dimensional vehicle location to the public safety response point (PSAP). The Federal Communications Commission (FCC) has ruled for 2001 that wireless service providers have the ability to locate users in two dimensions within 125 meters 67% of the time. A conventional method for locating a mobile station in two dimensions would use the measurement of the line of sight distance between the mobile station and at least three base stations. U.S. Patent No. 5,365,516 discloses a method for determining the location of a responder unit in which a radio signal is sent by means of a mobile station. The arrival time of the radio signal is measured in each of the three base stations. Each ranging measurement between the mobile station and one of the base stations can be used to generate a circle that is centered on the measuring base station. The circle has a radius that e.s. equal to the distance between the mobile station and the base station. Consequently, three circles are generated, one for each of the base stations. In the absence of any measurement error of the distance between the base stations and the mobile station, the intersection of the three circles unequivocally determines the location of the mobile station. This method has the disadvantage that the measurements. range can be disturbed by noise resulting in errors in determining the location of the mobile station. A conventional solution to provide more accurate position estimates is to reduce the error due to noise with a least squares analysis. Consequently, the minimum quadratic analysis provides a more accurate position estimate. This solution has the limitation of not having the possibility of a lack of a direct path between the base station and the mobile station. For example, in an urban environment, a building or buildings may be in the path between the mobile station and the base station. A propagation signal between the mobile station and the base station can be reflected and subtracted by the object in the trajectory of the mobile station towards the base station resulting in the signal traveling for excessive lengths, of trajectory,. The excess path lengths can be of the order of a hundred meters. The lack of direct path between the mobile station and the base station can be defined as out of line of sight (NLOS - non-line of sight). The importance of detecting and reducing NLOS measurements between a mobile station and a base station is recognized in M.I. Silventoinen, et al., "Mobile Station Locating in GSM", IEEE Wireless Communication System Symposium, Long Island NY, November 1995 and J.L. Caffrey et al., "Radio Location in Urban CDMA Microcells", Proceedings of the Personal, Indoor and Mobile Radio Environment, 1995. U.S. Patent No. 5,365,516 ('516 patent) describes a modality of a location transceiver system that operates in an environment susceptible to multiple path interference. The system includes a responder that can be operated within a prescribed coverage area to transmit a burst of data symbols on a coded carrier pulse. Each base station includes a receiver for detecting and responding to the data symbol at a given time, interrupting the data symbol and rejecting the echoes resulting from the multipath interference. A comparison circuit responds to the receiver to compare respectively given given times and to decorrelate the difference. time to improve the quality of the data. Although the '516 patent is directed to multi-path interference, it does not attempt to detect base stations to reduce the NLOS with mobile, multi-path stations. It is desirable to provide a method and system for providing improved mobile location estimation that is resistant to NLOS error.

SUMMARY OF THE INVENTION Briefly described, the present invention relates to a method and system for estimating a mobile location where the base stations are identified to be either line of sight (LOS) or outside Line of sight (NLOS) with a mobile station. A range measurement is determined as the distance between the base station and the mobile station. The NLOS variable error is corrected by base stations identified to be NLOS with the mobile station reconstructing the LOS measurements. From the range measurements of the base stations identified as LOS and the LOS reconstructed range measurements, the location of the mobile station is estimated. The base station can be identified as NLOS by comparing the standard deviation of the standard measurement noise from. environment to the standard deviation of a smoothed range measurement obtained from range measurements between the base station and the mobile station. The smoothed range measurement can be obtained using a polynomial adjustment of the order Nés? Mo. It has been found that when the standard deviation of the smoothed range measurement is in the order of the standard deviation of the standard measurement noise, the base station corresponds to a LOS environment and when the standard deviation of the smoothed range measurement is greater than the standard deviation due to standard measurement noise, the base station corresponds to an NLOS environment. Alternatively, residuals from the least squares analysis can be used to determine the presence of NLOS range measurements. The NLOS error can be corrected when the noise of the standard measurement dominates the NLOS error and there is predetermined identification of the approximate support of the standard measurement noise around the real axis. A reconstructed LOS range measurement can be determined by graphing a curve of the smoothed range measurements. The maximum deviation point of the smoothed range measurement is determined below the curve. The curve moves down to pass through the maximum deviation point. Subsequently, the curve is shifted upwards by the noise deviation value of the maximum standard measurement from a LOS measurement with negligible noise, thus providing a reconstructed range measurement. The mobile location estimate can be determined using at least three range measurements between the LOS base stations and the mobile station or LOS range measurements reconstructed in a multilateral analysis. In this analysis, a circle is generated from each range measurement. The circle is centered on the base station and the range measurement is the radius of the circle. The estimated intersection of the three circles determines the location of the mobile station. Alternatively, two range measurements and information directed towards the position angle of the mobile station can be used to estimate the location of the mobile station. The present invention has the advantages of accurately determining the location of a mobile station by reducing the NLOS error. In addition, the present invention can provide confidence that in a LOS environment all base stations are LOS with the mobile station. The results indicate that the position range deviation due to the NLOS error can be reduced by several orders of magnitude with the method of the present invention. The _. present 'invention. more will be described, completely referring to the following drawings.

BRIEF DESCRIPTION OF THE DRAWINGS Figure 1A is a schematic diagram of an environment where there is an unobstructed visual line radio signal path between a mobile station and a base station. Figure IB is a schematic diagram of an environment in which there is a non-visual line radio signal path between a mobile station and a base station. Figure 2 is a flow chart of the system and the method for estimating a mobile location, in accordance with the teachings of the present invention. Figure 3 is a schematic diagram of range measurements of a reconstructed visual line base station and the determined line of sight baseline stations. Figure 4 is a flowchart of a method for identifying the base line off-line visuals of the present invention. Figure 5 is a flow chart of an alternative method for identifying base stations off line of sight. Figure 6 is a flow chart of a method for reconstructing a line of sight baseline for off-line visual measurements. Figure 7 is a graph of a comparison of NLOS measurements and reconstructed LOS measurements. Figure 8 is a schematic diagram of a system for implementing the method of the present invention. Figure 9 is a schematic diagram of the placement of base stations used in performance examples of the method of the present invention. Figure 10A is a two-dimensional tracking graph without detection and correction of off-line visual error. Figure 10B is a two-dimensional tracking graph with detection and correction of off-line visual error. Figure HA is a two-dimensional tracking graph without detection and correction of off-line visual error. Figure 11B is a two-dimensional tracking graph with detection and correction of off-line visual error.

Figure 12 is a graph of the fraction of time. in which a base station was declared NLOS using the residual range analysis method.

DETAILED DESCRIPTION OF THE INVENTION During the course of this description, similar numbers will be used to identify similar elements, in accordance with the different figures illustrating the invention. Figure 1A illustrates a schematic diagram of a line of sight (LOS) 10 between a base station 12 and a mobile station 14. The signal 13 can be transmitted from the base station 12 to the mobile station 14 and returned from the mobile station 14 towards the base station 12. Figure IB illustrates a scheme of the non-visual line path (NLOS) between the base station 12 and the mobile station 14. The building 15 is placed between the base station 12 and the mobile station 14 resulting in a signal reflection 16. For example, the signal 13 and the signal 16 may be a radio signal. A range measurement for measuring the distance between the base station 12 and the mobile station 14 can be measured as the time used by a signal sent between a base station 12 and a mobile station 14: r = cT (1) where the measurement range of the mobile station to the - station ba.se is represented.- .. by ^ r, 'c. represents the speed of light that is the same speed of the propagation of radio waves and T represents the travel time in one direction, of the signal. A range measurement of the distance between the mobile station 14 and the base station 12 in Figure 1A and Figure IB can be determined using equation (1) based on the travel time of the signal 13 and the signal 16 , respectively, between the base station 12 and the mobile station 14. The value of r generated from the signal 16 is greater than the value of r generated by the signal 13. Figure 2 is a flow diagram of the system and the method of the present invention for the estimation 20 of a mobile location. In block 21, a range measurement is obtained between the mobile station 14 and the base station 12 using equation (1). In block 22, it is identified that the base station 12 is in line of sight (LOS) or out of line of sight (NLOS) with the mobile station 14. Block 22 is repeated by a plurality of base stations 12 placed in different locations from the mobile station 14. If it is identified that station 12 is in LOS in block 22, the range measurement obtained from block 21 is transmitted to block 26 where the estimation of a mobile location is determined.

If the base station 22 is identified to be NLOS in the block 22, the block 24 is implemented to reduce. the error of the range measurement between the base station 12 and the mobile station 14, thus giving the range measurement between the base station 12 and the mobile station 14 as a reconstructed base station 13 LOS, as shown in Figure 3. In Figure 3, base station 12 labeled EB1 has a range measurement labeled LOS RANGE 1 determined to be LOS. Base station 12 labeled EB2 has a range measurement labeled LOS RANGE 2 determined to be LOS. Base station 13 labeled EB3 has a range measurement labeled NLOS RANGE 3 determined to be NLOS. A range measurement for the rebuilt LOS base station labeled RECONSTRUCTED RANGE 3 is transmitted to block 26. Range measurements from the LOS base stations determined from block 22 labeled LOS RANGE 1, and LOS RANGE 2 are also transmitted to block 26. From the range measurements of the reconstructed LOS base stations or of the determined LOS base stations, or of a combination of reconstructed LOS range measurements, the estimation for a mobile location can be identified using a conventional multilateral technique , as described in U.S. Patent No. 5,365,516, incorporated as reference in this application. Thus, the estimation of a mobile location can be determined from the time difference of the arrival time measurements as the difference of propagation delays between the mobile station 14 and base station pairs 12. In this case, the Estimated position is at the intersection of hyperbolas. The number of base stations can be reduced below three if there is also an arrival information angle. These methods are described in T.S. Rappaport et al., "Position Location Using Wireless Communication On Highways of the Future", IEEE Communications Maaazine, October 1996. Figure 4 illustrates a method for identifying whether a base station is LOS or NLOS in block 22. In this method, the time history of range measurements between the base station 12 and the mobile station 14 is combined with the predetermined standard deviation from conventional measurement noise in a radio signal environment. The arrival time of signals sent from the base station 12 to a mobile station 14 and answered back to the base station 12 can be converted to a range measurement in the block 30. The range measurement at the base station month. in time tk can be represented as: rm (tL) =, L t,) + nt,) + NLOSa (ti) (2) for m = 1 / ..., M i = 0, ... K-l, where Lm tj) is the distance LOS between a mobile station and the més? m base station in two dimensions that is given by: L t,) = \ x (t1) + j * y (t1) -? M - j * y m I; (3) x (ti), and (£ i) and (xm, ym) are respectively the coordinates of the mobile station in time, ti7 and those of the base station month: L, n; nm (ti) represents the conventional measurement noise such as for example the white additive Gaussian measurement noise and the NLOSm (t¿) represents the measurement error NLOS at time t ±; and M is the total number of base stations; and K is the total number of time samples. In block 30, an LOS range measurement with negligible noise is obtained for base station 12 in LOS with mobile station 14. Range measurement LOS can be obtained by physically measuring a range between base station 12 and mobile station 14 or it can be obtained as a range measurement determined by equation (1) in a negligible noise environment. In block 31, a noisy range measurement is determined as a range measurement that is in LOS with a base station taken in a noise ambient. In block 3.2.-,, the standard deviation of the noisy range measurement from the LOS measurement without noise is determined. The blocks 30, 31 and 32 may be predetermined before identifying the base station 12 either as LOS or NLOS in block 22. The standard deviation due to the noise nm (t) may be represented by sm. In block 33, the range measurement obtained from block 21 is smoothed by modeling and solving the unknown coefficients,? m (ri)} "~ 0 with at least one check technique. The smoothed range measurement can be represented as: In block 34, the standard deviation of the smoothed range measurement is determined from a noise range measurement (i.e., the residue). The standard deviation of the residue from block 34 can be represented as o * m since s ^ = E [nn (t)} . Range measurements smoothed along with noisy range measurement can. used for. determine the standard deviation c? with the formulation of: m = ^? (SÁ -rm (t,)) 2 (6) From the value of the standard deviation, < Sm, of block 34, and of the standard deviation sm, of block 32, the range measurement can be determined either as the result of the base station 12 which is LOS or NLOS, in block 36. When the range measurement has NLOS error, the value of the standard deviation m is significantly greater than the value of the standard deviation sm. Consequently, the range measurement for the base station 12 that is NLOS with the mobile station 14 is determined when the m is greater than the standard deviation sm. A range measurement of the base station 12 that is LOS with the mobile station 14 is determined when the standard deviation < Sm is in the order of the standard deviation sm. Alternatively, a residual analysis classification method can be used to identify a range measurement being from a NLOS base station 13 with the mobile station 14. The range measurements between the mobile station 12 and the base station 14 that have been obtained , in block 21 are entered into block 40. In each time request ti7 the estimated coordinates • •% Ls (t? X $ Ls (t?) ^ e ^ to mobile station 14 are determined as at least quadratic estimates in block 40. The estimated coordinates are selected to minimize the formula: M (7) B) = l where Lm (/,) = xm + j * S > (t,) - j * y ", | . In block 41, a range measurement calculated from the estimated coordinates is determined.

In block 42, a residual difference of the range measurement between the mobile station 12 and the base station 14 is determined with the calculated range measurement. The residual difference can be represented as: em (tl) = rm (t,) -Lm (t¡) (8) In block 44, the number of times the residual difference of a range measurement to a base station 12 has the highest value compared to the residual difference determined by the range measurements at the other base stations is counted by each time request. . It has been found that the base stations that have a range measurement between an NLOS base station and a mobile station have a significantly greater number of the greater absolute residual differences than the number of the largest absolute residual differences of the stations. other base stations. From the value of the counted number of residual differences, the base station 14 can be defined as a base station 12 which is an LOS or a base station 12 which is NLOS with the mobile station 14, according to block 46. Figure 6 illustrates a method for correcting range measurements between a base station 12 that has been NLOS determined with the mobile station 14 to reconstruct a LOS range measurement. The data related to the range measurements from block 21 are smoothed using a polynomial adjustment of the order Nes? Mo described in block 32. Smoothed range measurements are entered into block 52. The maximum deviation below the smoothed curve due The NLOS error is determined in block 56. It has been found that the NLOS error is a non-negative random variable that can be represented approximately on a real axis as follows: 0 <; NL0Sm (t < ßm where ßm is the maximum error value NLOS.) The standard measurement noise, pm (t can, be represented as a random variable of null meaning that can be represented approximately on a real axis as follows: -am < n-jí i) < am so that in a range measurement where there is also an NLOS error, the total noise component can be represented approximately on the real axis as follows: -am < nt) + NLOSra (t ) < ßm -am. It has been found that the maximum deviation point of the distance measured below the smoothed curve is approximately a.m. below the LOS function represented as Lm (ti). In block 58, the smoothed curve shifts mathematically down to the point of maximum deviation. The smoothed curve is mathematically shifted up by a value of the noise deviation a in block 60 to provide a reconstructed curve representing a reconstructed LOS base station. Figure 7 represents a graph of a comparison of simulated range measurements. Curve 90 represents the true time range measurement between a base station 12 that is in LOS with a mobile station 14. Curve 91 represents determined range measurements that have NLOS error. The curve 92 represents a smoothed range measurement of the block station 12 and the mobile station 14 determined from the block 30 of Figure 4. The curve 93 represents the base station 12 which is in LOS reconstructed with the mobile station 14 from of block 60 of Figure 6. Figure 8 is a schematic diagram of a system 80 for implementing the method for mobile location estimation. System 80 includes base station server 81. The base station server 81 can be a computer located in the base station 12 or in a network with it. The server 81 of the base station communicates with the base station 12 to request and receive data related to the range measurements of the mobile station 14 and the base station 12. The base station server 81 also collects the information about measurements range between the mobile station 14 and each of the base stations 81A-81N. The information is reported to the server 81 of the base station either by the mobile station or by servers of the base station 81A-81N. The functions of the modules shown in Figures 4-6 are encoded with a standard programming language, such as the C ++ programming language. The encoded modules can be executed by the server 81 of the base station. The results for examples of mobile location estimates with system 80 are shown in Tables I to IV and. in "Figures" 9 through 12. In all the examples, the position of the vehicle in the xy plane in whatever is given by: • • x (t) = x0 + vxt and (t) = y0 + vyt x (t ) represents the x coordinate in the xy plane at the requested time, t, and (t) represents the y coordinate in the xy plane at the requested time, t, xQ represents the initial x coordinate, and D represents the initial y coordinate , vx represents the velocity in the x direction, v and represents the velocity in the y direction, the sampling period was selected to be 0. 5s and 200 samples were taken. The constant speed remaining at vx = 9.7 m / s and vy = 16.8 m / s. The base stations 12 were assigned to have NLOS or LOS range measurements. The standard deviation of the standard measurement noise was represented as a sm was 15Om and Bm was selected as 1300m. In each example the three base stations 101, 102, 103 were used evenly spaced around a 5-kilometer circle and a fourth base station 104 was placed in the center of the circle, as shown in Figure 9.

In a first example, base station 101 and base station 102 provide NLOS range measurements and base stations 103 and base station 104 provides LOS range measurements. The standard deviation < Sm (m) of the smoothed curve determined in Figure 4 as shown in Table 1.

TABLE 1 STANDARD DEVIATION OF MEASUREMENTS FROM THE CURVE SOFTENED FOR 2 MEASURES NLOS The results indicate that the base stations 101 and 102 have the NLOS range measurements with a significantly greater standard deviation than the base station 103 and the base station 104 having a LOS range measurement. Figure 10A shows error tracking, two-dimensional, without NLOS identification and correction. Figure 10B shows the two-dimensional error tracking after the method for estimating a mobile location of the present invention is carried out. The results indicate improvement of the estimated trajectory of the vehicle after the identification and correction of the NLOS. In a second example, the base stations 101, 102, 103 and 104 have NLOS range measurements. The standard deviation tfm (m) of the smoothed curve determined in Figure 4 is shown in Table 2.

TABLE 2 STANDARD DEVIATION OF MEASUREMENTS FROM THE SOFTENED CURVE FOR FOUR MEASUREMENTS NLOS The results indicate a similar standard deviation tf ", (m) for all four base stations 101, 102, 103 and 104 that have NLOS. In a third example, the results were determined using x0 = -118.3m and 0 = -3.7m with the residual analysis tracking method shown in Figure 5. In test 1, the base station 104 was NLOS. In test 2, the base station 103 and the base station 104 are NLOS. In test 3, the base station 102, the base station 103 and the base station 104 were not in line of sight. The number of times each base station had the largest absolute residual difference is shown in Table 3.

TABLE 3 PERCENTAGE OF TIMES THAT THE BASE STATION (EB) HAD THE LARGEST RESIDUAL The results indicate the NLOS base stations that have higher percentages of residual differences. In a fourth example, the results of the method for location estimation in the present invention were compared with a conventional minimum quadratic analysis, a minimum quadratic analysis with all range measurements that are in line of sight and a Lower Limit Cramer analysis. Rao (Cramer Rao Lower Bound CRLB) conventional. The Lower Cramer Rao Limit represents a lower limit on the rms error of any non-deviated estimator. Table 4 represents the current method shown in column 2, the minimum conventional quadratic analysis shown in column 1, a minimum quadratic analysis with all LOS measurements in column 3, and the lower limit Cramer Rao analysis shown in the column Four . The location and velocity errors in each coordinate were measured in meters and in meters / seconds, respectively. μxo = mean of the error in estimation X0 sxo = standard deviation of £ Q μyo = mean of the error in estimation y0 syo = standard deviation of j > 0 μvx = mean of the error in estimation Vx svo = standard deviation of ix μvy = mean of the error in estimation vy svy = standard deviation of $ y TABLE 4 COMPARISON OF THE ESTIMATOR'S PERFORMANCE The results indicate that the method for estimation of a mobile location of the present invention significantly reduced the estimate deviation as compared to the results without NLOS error correction. Figure 12 is a comparison of the probability of detecting an NLOS range measurement. The sampling period was 0.5 seconds. The number of samples varied between 5 and 150. X0 was 200m and ys was 100m. Base station 101 and base station 104 were LOS. The base station 102 and the base station 103 were NLOS. The results indicate that NLOS can be detected with high probability for a small number of samples. It is understood that the embodiments described in the foregoing are illustrative of only a few of the many possible specific modifications that may represent applications of the principles of the invention. Many other and diverse arrangements can be invented by those skilled in the art in accordance with these principles, without departing from the spirit and scope of the invention.

Claims (19)

1. CLAIMS; An estimation method for the location of a mobile station, comprising the steps of: a) obtaining range measurements between the mobile station and a base station; b) identifying whether the base station is in line of sight with the mobile station or off line of sight with the mobile station, at which time an estimation of the location of the mobile station is made; c) correcting out-of-line visual range measurements for a base station identified as out of sight line with the mobile station of step b), to determine reconstructed line-of-sight measures; d) repeat the steps of items a) through c) for a predetermined number of base stations; and e) determining the mobile station location estimate from the reconstructed visual line range measurements determined in step c) or range measurements determined in step a) for a visual line base station identified in step b), or the combination of the reconstructed line-of-sight range measurements determined in step c) and the range measurements determined in step a), for a visual line base station identified in step b).
2. 2. The method according to claim 1, wherein step b) comprises, in turn, the steps of: obtaining the line of sight measurements between the mobile station and a noise-free base station; obtain noisy visual line range measurements between the mobile station and the base station; predetermining a first standard deviation of the difference of the visual line range measurements with the noisy visual line range measurements, smoothing the range measurements determined in step a); determining a second standard deviation of the difference between smoothed range measurements and noisy visual line range measurements; and discriminating between the base station that is in line of sight or the base station that is out of line of sight from the first standard deviation and the second standard deviation, where the base station is determined not to be in line of sight when the second standard deviation is greater than the first standard deviation and visual line when the second standard deviation is in the order of the first standard deviation.
3. 3. The method according to claim 2, wherein the range measurement obtained in step a) is represented by: r t,) = L t + n t ±) + NL0Sa (t1) for m = 1, ..., M i = 0, ... K-l, where Lm (t¡) is the distance LOS between a mobile station and the bimound base station in two dimensions that is given by: L t,) = \ x (t1) + j * and (ti) - xm - j * ym \; / '= V-1, | | it is absolute value, x (tx), and (t.j) and (xm, ym) are respectively the coordinates of the mobile station in time, tlr and those of the mav base station; ^ (t ±) represents the conventional measurement noise such as for example Gaussian additive white noise and NLOSm (fc ±) represents the measurement error NLOS at time ti7- and M is the total number of base stations; and K is the total number of time samples.
4. 4. The method according to claim 3, wherein the range measurement is smoothed by modeling ? rm (tL) = S H = 0 «" »," &"and solving the unknown coefficients,? minJ n = with a minimum quadratic technique 5. The method according to claim 4, wherein the second standard deviation is represented by: where 6. The method according to claim 1, wherein step b) further comprises the steps of: estimating the coordinates of the mobile station from the range measurement obtained in step a) in time; calculate a range measurement from the estimated coordinates; determining a residue from the difference of the range measurement obtained in step a) and from said calculated range measurement; count the number of times the waste is the largest in each base station for each instant of time; and defining the base station as off-line from the base station that has the largest value of the number of times the largest waste was counted. 7. The method according to claim 6, wherein the estimated coordinates are represented by ^ ÍS (t,), j > ¿S (/;) at each instant of time ti, the estimated coordinates are determined as minimum squared estimates M for F¡ = (rm { T,) -Lm. { t,) f where 4 (í,). The method according to claim 1, wherein step c) further comprises the steps of: determining the maximum noise deviation value and standard deviation from the range measurements obtained in step a) and a measurement of predetermined visual line range with negligible noise; smoothen the range measurements obtained from step a); graph a curve of smoothed range measurements; determine a maximum deviation point of the range measurement below the curve; move the curve down to pass through the point of maximum deviation; and move the curve upwards by the value of the maximum noise deviation, thus providing the reconstructed range measurement. 9. The method according to claim 1, wherein steps a) through c) are repeated for at least two base stations and further comprising the step of determining the arrival information at an angle, wherein the location of the mobile station it is estimated from the range measurements or reconstructed visual line range measurements of the two base stations and the arrival information at an angle. The method according to claim 1, wherein steps a) to c) are repeated for three base stations. 11. An estimation system for the location of a mobile station, comprising: a means for obtaining range measurements between the mobile station and a plurality of base stations; identification means for identifying whether each of the base stations is in line with the mobile station as a visual line base station, or off line of sight with the mobile station as a base station off line of sight; a correction means for correcting the range measurement for each of the base stations out of line of sight, in order to determine a reconstructed line of sight range measurement; and an estimation means for determining the mobile station location estimate from the reconstructed visual line range measurements or range measurements for the visual line base station, or the combination of the visual line range measurements reconstructed and range measurements for base stations in visual line. The system according to claim 11, wherein the identification means comprises: means for obtaining a visual line-of-sight measurement without noise between the mobile station and each of the base stations; means for obtaining a visual, noisy line-of-sight measurement between the mobile station and each of the base stations; means to predetermine a first standard deviation of the difference of the visual line range measurement with noisy visual line range measurements, means to smooth the range measurements; means for determining a second standard deviation of the difference between smoothed range measurements and noisy visual line range measurement; and means for discriminating each of the base stations as in line of sight or out of line of sight, from the 'first standard deviation and the second standard deviation, where it is determined that the base station is out of line of sight when the second standard deviation is significantly greater than the first standard deviation, and it is in line of sight when the second standard deviation is in the order of the first standard deviation. The system according to claim 12, wherein the range measurement is represented by: rm (tL) = L t,) + n t,) + NLOS t,) for m - 1, ..., M i = 0, ... K-l, where Lm (t ±) is the distance LOS between a mobile station and the base station in two dimensions that is given by: L t ±) = \ x (t1) + j * y (ti) - xm - j * ya \; y '= V-1, | | it is absolute value, x (ti), and (t¿) and (xm, ym) are respectively the coordinates of the mobile station in time, tx, and those of the base station mva; n., ^) represents the conventional measurement noise such as for example the white additive Gaussian measurement noise and the NLOSm (t ±) represents the NLOS measurement error in. the time tL; and M is the total number of base stations; and K is the total number of time samples. The system according to claim 13, wherein the range measurement is smoothed by modeling N-l r. (T ±) =? ^, (N) t ", n = 0 and solving the unknown coefficients, m (n)} ^ with a minimum quadratic technique. The system according to claim 14, wherein the second standard deviation is represented by: where jV-l £ ", (',) =? a», "B-0 16. The system according to claim 12, wherein said identification means comprises: means for estimating coordinates of the mobile station from the range measurements from a plurality of base stations received over time; means for calculating a measurement of 'range calculated from the estimated coordinates; means to determine a residue from the difference of the range and calculated range measurements; means for counting the number of times the waste is the largest in each base station for each instant of time; and means for defining the base station as off-line from the base station having the largest value of the number of times the largest waste was counted. 17. The system according to claim 14, wherein the estimated coordinates are represented by Ls (ti) > ? s (.t¡ in each instance of time t ±, the estimated coordinates are determined as minimum squared estimates where Lm (tt) 18. The system according to claim 12, wherein the means of estimation comprises: means for determining a value of the maximum noise deviation and the standard deviation for each of the range measurements and a predetermined visual line range measurement with noise negligible; means to smooth out range measurements; means for plotting a curve of smoothed range measurements; means for determining a maximum deviation point of the range measurements below the curve; means for moving the curve down to pass through the point of maximum deviation; and means for moving the curve upwards by the value of the maximum noise deviation, thus providing the reconstructed range measurement. The system according to claim 12, further comprising means for obtaining an angled arrival information wherein the location of a mobile station is estimated from the range measurements or from the reconstructed visual line range measurement of the stations. base and arrival information at an angle.