APPARATUS FOR NAVIGATION SATELLITE SIGNAL QUALITY MONITORING

Abstract: An apparatus for the detection of positioning system satellite signal distortions includes a correlator that determines a plurality of correlation measurements at points along a correlation curve. The correlation measurements are based upon a correlation between a received satellite signal and a reference. A signal distortion detector determines differences between the correlation measurements along the correlation curve and detects a signal distortion from the differences.

Description: APPARATUS FOR NAVIGATION SATELLITE SIGNAL QUALITY MONITORING Technical Field of the Invention The present invention relates generally to satellite based positioning systems such as the Global Positioning System (GPS) and more particularly to the monitoring of the quality of the signals transmitted by satellites in a satellite based positioning system. Background of the Invention and Prior Art A satellite based positioning system is used to determine a position of a receiver and typically includes satellite control facilities, a plurality of satellites, the receiver, and one or more local or regional ground stations. Each of the satellites transmits a signal that contains a code and certain prescribed information useful to the receiver in determining its position. The receiver synchronizes itself to the codes of at least four satellites and uses the information in the signals from these satellites in order to perform a triangulation like procedure so as to determine its coordinates and time offset with respect to a reference, such as the center of the Earth and the GPS standard time. The receiver is not constrained to a specific location and, therefore, represents a variable position. Indeed, the purpose of the satellite based positioning system is to make it possible for the receiver to determine its position regardless of the cation of the receiver. On the other hand, the local or regional ground station is in a fixed location and is used to monitor the signals transmitted by the satellites. The signals transmitted by the satellites can be adversely affected, for example, by atmospheric conditions which can lead to improper position determinations by the receiver. The ground station, therefore, notifies the receiver of any necessary signal corrections to allow the receiver to make more accurate position calculations. This arrangement is referred to as differential positioning. The ground station of the present invention also monitors the signals transmitted by the satellites in order to detect faults within the satellites. For GPS, these faults are specified by the FAA who imposes stringent requirements to protect users against positioning system signal faults. A set of test waveforms has been chosen by the FAA to represent at least some of the more egregious faults. These waveforms are used for certification testing of the ground station equipment. The prior art determines faults by comparing conventional code tracking discriminators at different correlator spacings. As shown in Figure 1 , a correlation curve is established by correlating the code received from a satellite with a suite of code references which are time shifted replicas of the code transmitted by that satellite. For example, seven correlation measurements may be calculated as shown in Figure 1. The in-phase measurement IP represents the amount of correlation between the received code and a reference code that has a zero time shift with respect to the received code (this measurement is referred to as punctual). The in-phase measurement IE-) represents the amount of correlation between the received code and a reference code that has a first predetermined time shift so that it is early with respect to the received code. The in-phase measurement ILι represents the amount of correlation between the received code and a reference code that has a second predetermined time shift so that it is late with respect to the received code. Similarly, the in-phase measurement IE 2 is derived using a third predetermined time shift, the in-phase measurement IL 2 is derived using a fourth predetermined time shift, the in-phase measurement IE 3 is derived using a fifth predetermined time shift, and the in-phase measurement IL 3 is derived using a sixth predetermined time shift. The magnitude of the first predetermined time shift may be equal to the magnitude of the second predetermined time shift, the magnitude of the third predetermined time shift may be equal to the magnitude of the fourth predetermined time shift, and the magnitude of the fifth predetermined time shift may be equal to the magnitude of the sixth predetermined time shift. It is assumed that all measurements are normalized such that the measured correlation is a function of the time shifts only and not the absolute power of the received satellite signal. First, second, and third discriminators are then formed according to the following equations: d sub 1 ~ = ~ (lL sub 1 ~ - ~ IE sub 1 ) IP d sub 2 ~ = ~ (IL sub 2 ~ - ~ IE sub 2) IP d sub 3 ~ = ~ (IL sub 3 ~ - ~ IE sub 3) IP These discriminators are thereafter compared to each other through the formation of quantities dι ,2> dι ,3 , and d 2 , 3 according to the following equations: d sub {1 ,2} ~ = ~ LINE d sub 1 ~ - ~ d sub 2 LINE d sub {1 ,3} ~ = ~ LINE d sub 1 ~ - ~ d sub 3 LINE d sub {2,3} - = ~ LINE d sub 2 ~ - ~ d sub 3 LINE The quantities dι ,2 , dι ,3 , and d 2,3 are compared to corresponding thresholds D- 1 ,2 , D-1 ,3 , and D 2 , 3 such that, if the first discriminator d^ exceeds D-ι ι2 , if the second discriminator di , 3 exceeds Di , 3, or if the third discriminator d 2, 3 exceeds D 2ι3 , a fault is assumed to exist. During normal operation of the global positioning system, this test is performed on the signals received from each of the satellites. During certification, a test is to be performed using each of the test waveforms chosen by the FAA in order to prove that fault detection occurs. At least one of the problems with this method is that it is requires six correlators in order to determine the three quantities dι_ 2 , d-i^, and d 2,3 which is too much hardware for the amount of useful data being provided. It is also known for ground stations to determine faults by scanning the whole correlation peak (i.e., the portion of the correlation curve around the punctual in-phase measurement IP) in order to determine whether the peak varies from some prescribed norm by a predetermined amount. However, this fault detection arrangement requires a substantial amount of computing power and it lacks accuracy. A third method in the prior art uses the following ratios between the measurements IE3, IE2, IE1 , IL1 , IL2, and IL3: r sub { E3,E2} ~ = ~ {IE3} over {IE2} r sub { E3,E1} ~ = ~ {lE3} over {IE1} r sub { E3.L1} ~ = ~ {1E3} over {IL1} Each of these ratios is compared to a corresponding predetermined value. The present invention is directed to an arrangement which overcomes one or more problems of the prior art. Summary of the Invention In accordance with one aspect of the present invention, an apparatus for the detection of positioning system satellite signal faults comprises a correlator and a fault detector. The correlator determines a plurality of correlation measurements at points along a correlation curve, and each correlation measurement is based upon a correlation between a received satellite signal and a reference. The fault detector determines differences between the correlation measurements along the correlation curve and detects a fault from the differences. In accordance with another aspect of the present invention, a method of detecting faults affecting a signal transmitted by a positioning system satellite comprises: correlating the transmitted signal with a first reference in order to determine a first correlation measurement at a first point along a correlation curve; correlating the transmitted signal with a second reference in order to determine a second correlation measurement at a second point along the correlation curve; correlating the transmitted signal with a third 'reference in order to determine a third correlation measurement at a third point along the correlation curve; determining a first difference from the first and second : correlation measurements; determining a second difference from the second and third correlation measurements; directly comparing the first difference to a first threshold; directly comparing the second difference to a second threshold; . and, detecting a fault in the satellite based upon the comparisons of the first > and second differences to the first and second thresholds. In accordance with still another aspect of the present invention, a method of detecting faults affecting a signal transmitted by a positioning system satellite comprises: correlating the transmitted signal with references in order to determine a plurality of correlation measurements at corresponding points along a correlation curve; determining a single value from n pairs of the correlation measurements, wherein n > 2; comparing the single value to a threshold; and, detecting a fault in the satellite based upon the comparison. Brief Description of the Drawings These and other features and advantages will become more apparent from a detailed consideration of the invention when taken in conjunction with the drawings in which: Figure 1 is a waveform showing a correlation diagram useful in explaining prior art fault detection as implemented in a ground station in a global positioning system; Figure 2 is a schematic diagram of a portion of a ground station receiver pertinent to the present invention; and, Figure 3 is a waveform showing a correlation diagram useful in explaining fault detection as implemented by a ground station jn a global positioning system in accordance with the present invention. Detailed Description A portion of a groundistation 10 pertinent to the present nvention is shown in Figure 2.^Th ' e ground station has correlators il 2-Eήry J x ι.; 2-E 3 i2-E 2 , 12-Ei, 12-P, ' 2-ϊ-i ,' 2-L 2 i 1 ' 2-L 3 , . . ., ' 12-L n> where n ' +SπrEis -?χ greater than two, and where n is the number of late correlation measurements and m is the number of early correlation measurements to be used -in- ; i :■:> ■ determining a fault. The correlator 12-P correlates the usual code in the ' : received signal with a reference 14-P to produce a punctual correlation output IP, the correlator 12-L-j, correlates the code in the received signal with a .<. reference 14-L^ to produce a late correlation output ILι, the correlator Λ2-L 2 correlates the code in the received signal with a reference 14-L to produce a late correlation output IL 2 , the correlator I2-L 3 correlates the code in ; the - '. '• received signal with a reference I4-L 3 to produce a late correlation ©utput I L3, . . ., and the correlator 12-L n correlates the code in the received signal with a . reference 14-L n to produce a late correlation output IL n . ; In addition, a correlator 12-E-ι correlates the code in the received signal with a reference 14-Ei to produce an early correlation output IE 1 , a correlator I2-E 2 correlates the code in the received signal with a reference 14-E 2 to produce an early correlation output IE , a correlator 12-E 3 correlates the code in the received signal with a reference 14-E 3 to produce an early correlation output IE , . . ., and a correlator 12-E m correlates the code in the received signal with a reference 14-E m to produce an early correlation output IE m . The ground station 10 has a processor 16 which uses the punctual and late correlation outputs IP, IL-i, IL 2 , IL 3 , . . ., IL n as disclosed hereinafter in order to determined whether a fault exists. Alternatively or additionally, the processor 16 can use the early correlation outputs lE-i, IE 2 , IE 3 , . . ., IE m as disclosed hereinafter in order to determined whether a fault exists. In order to generate the punctual correlation output IP, the processor 16 shifts the reference 14-P, which may be a replica of the code contained in the received signal, until an optimum correlation is obtained. The processor 16 then controls the reference 14-L-ι so that the reference 14-Li is a replica of the reference 14-P and so that the reference 14-L-ι is time shifted with respect to the reference 14-P by a first predetermined amount of time. Accordingly, the correlator 12-L-ι produces the late correlation output IL 1 . The processor 16 also controls the reference 14-L 2 so that the reference 14-L 2 is a replica of the reference 14-P and so that the reference 14-L 2 is time shifted with respect to the reference 14-P by a second predetermined amount of time, where the second predetermined amount of time is greater than the first predetermined amount of time. Accordingly, the correlator I2-L 2 produces the late correlation output IL 2 . Similarly, the processor 16 controls the reference I4-L3 so that the reference I4-L 3 is a replica of the reference 14-P and so that the reference I4-L 3 is time shifted with respect to the reference 14-P by a third predetermined amount of time, where the third predetermined amount of time is greater than the first and second predetermined amounts of time. Accordingly, the correlator I2-L 3 produces the late correlation output IL 3 . The remaining late correlation outputs up to IL n are generated in a like manner. The first, second, third, etc. predetermined amounts of time are all chosen so that the late correlation outputs ll_ι through IL n are all on the downward or late slope of the correlation curve as shown in Figure 3. Additionally or alternatively, the correlators 12-E-], 12-E 2 , 12-E 3 , . . ., 12-E m may be positioned so as to generate the early correlation outputs lE-i, IE 2 , IE 3 , . . ., IE m . Also, quadrature phase correlation outputs QE m , . . ., QE-i, QP, QL 1 ,. . ., QL n may be generated by correlating the code in the received signal to a time shifted quadrature form of the reference 14-P. In accordance with this latter alternative, each measurement used to generate a fault indication may be formed as an RMS (Root Mean Square) value of the corresponding in phase and quadrature phase measurements. The set IE m , . . ., IE 3 , IE 2 , IEΞ-I , IP, IL-i, IL 2 , IL 3 , . . ., IL n may be denoted as l m , . . ., I_ 3 , L 2 , l_ι, lo, I 1 , 1 2 . . ■ ■ ■. 'n anc l tne following corresponding set of RMS values SQRT { IE sub m sup 2 ~ + ~ QE sub m sup 2}, ~. ~. ~ , SQRT { IE sub 1 sup 2 ~ + ~ QE sub 1 sup 2}, ~ SQRT { IP sup 2 ~ + ~ QP sup 2}, ~. ~. ~ , -SQRT { IL sub n sup 2 ~ + ~ QL sub n sup 2} may be denoted as R m , . . ., R_ 3> R. 2) R-ι, R 0 , Rι, R2, R3, ■ ■ -, R n - If early as well as late correlation outputs are to be used for fault detection, the processor 16 processes the early correlation outputs IE m through lE-i, the punctual correlation output IP, and/or the late correlation outputs IL-i through IL n so as to derive one or more measured differences j j . These measured differences dj j are generated in accordance with the following equations: d sub {i,j} ~ = ~ I sub i ~ - ~ I sub j or d sub {i,j} ~ = ~ R sub i ~ - ~ R sub j where i = -m, . . ., n and j = -m, . . ., n, and where the negative sign indicates measurements on the early slope and the positive sign indicates measurements on the late slope of the correlation curve. At this point, it is possible to subtract the expected difference from all or a subset of these measured differences j j and to compare the resulting difference deviations to corresponding thresholds in order to determine the existence of a fault. For example, assuming that all of these difference deviations are used, then these difference deviations may be compared to corresponding thresholds in accordance with the following equation: LINE d sub {ij} ~ - ~ Ed sub {ij} LINE - > ~ D sub {ij} where Edy is the difference that is expected for each corresponding measured difference dj j when there is no fault. In some cases, the measured differences dj j may be affected by thermal and multipath noise which could lead to false detection of faults, depending upon the sensitivity of the fault detection apparatus, i.e., the magnitudes of the thresholds Dj . Accordingly, in these cases, a fault could be detected when no fault is in fact present, or a fault which is present might not be detected at all. The thermal noise content in dj j can be determined as a function of the delay hy between the reference codes 14-E m , . . ., 14-E 3 , 14-E 2 , 14-E-ι, 14-P, 14-L-ι, 14-L 2 , 14-L 3 , . . ., 14-L n . The delay hy is the delay between the two references that are correlated with the received signal to produce Ij and I j . Typically, j j = 0.025 to 0.05 chip, but may vary from this range. The thermal noise th1 in dj j depends on the signal to noise ratio and the standard deviation (1-sigma) of th1 and is given by the following equation: sigma sub {th1} ( ij ) ~ = ~ 293SQRT { { h sub {i j} B } over { S/No } } (4) where B is the two-sided bandwidth of the noise. In addition, there is another contribution, th2, to the thermal noise due to the variation of the punctual reference (i.e., the reference 14-P). Accordingly, the total thermal noise is th = th1 + th2. The multipath noise mp depends on the antenna gain pattern and its overbounding 1-sigma 50 {stack {vert -50 {..} # e}} vert -50 ) is expressed as a function of satellite elevation vert 50 {stack {vert -50 {..} # e}}. The statistical properties of th and mp are usually identified at installation of the ground station and the statistical information is parameterized and are thereafter stored in memory. One way to minimize any adverse effects of thermal and multipath noise is to make a plurality of measurements for each of the measured differences dj j that are used in the detection of faults. Then, the measurements for each of the measured differences dj j may be averaged or filtered. Because the thermal noise and some of the multipath noise are not particularly correlated from one measurement to the next, averaging will tend to reduce the effects of thermal and multipath noise. As an example, let it be assumed that the punctual correlation output IP and the late correlation outputs IL-i and IL 2 are used to detect faults. Accordingly, the following measured differences are determined: d 0] ι = IP - IL-i; do ,2 = IP - IL 2 ; and, d^ = IL-i - IL 2 - In order to reduce the effects of thermal and multipath noise, however, plural calculations of the measured difference do , ι are made based upon plural correlation measurements resulting in plural punctual correlation outputs IP and plural late correlation outputs IL-|. All such calculations of the measured difference do , ι are then averaged. Similarly, plural calculations of the measured difference do ,2 are made based upon the plural correlation measurements resulting in plural punctual correlation outputs IP and plural late correlation outputs IL 2 . As before, all such calculations of the measured difference do ,2 are averaged. Likewise, plural calculations of the measured difference d ι2 are made based upon the plural correlation measurements resulting in the plural late correlation outputs IL-j and plural late correlation outputs IL 2 . Again, all such calculations of the measured difference dι ,2 are averaged. These averages may then be compared to their corresponding thresholds Dn , ι, D 0,2 , and Dι τ2 in order to determine the existence of a fault. Another way to reduce the effect of thermal and multipath noise is to suitably filter the measured differences dj j , or the punctual correlation output IP, the late correlation outputs IL-f through IL n , and the early correlation outputs IEι through IE m , such as with a low pass filter. Still another way to reduce the effect of thermal and multipath noise is by implementing the following procedure. In describing this procedure, it is useful to define a covariance matrix P in accordance with the following equation: P ~ = ~ E [ ( underline d underline m ) ( underline d ~ - ~ underline m ) sup T ] where the underlines indicate vectors, where E[A] is the statistical expectation of A, where the vector m is the mean value of the vector d, and where the vector d is determined in accordance with the following equation: {underline d} sup T ~ = ~ ( d sub 1 , d sub 2, d sub 3, d sub 4, . . ., d sub N) (6) where dk = Ik - lk-1 - Ed for k = -m, . . ., n-1 or where dk = Rk - R k - 1 - Ed for k = -m, . . ., n-1 assuming N + 1 correlation measurements such as l m , . . -, I- 3 , I- 2 , I- 1, lo. , I2. . • ■ •. In- An upper triangular matrix U and a diagonal matrix D are determined according to the following equation: P ~ = ~ U D U sup T where P is the covariance matrix given by equation (6). With the covariance matrix P known from equation (6), the upper triangular matrix U and the diagonal matrix D can be determined, for example, by using Cholesky factorization. Thus, the following relationship may be defined in accordance with the following equation: stack { vert -50 {\~} # d # vert 50 {-} } ~ = ~ U sup {-1} ( underline d ~ - ~ underline m) where stack { vert -50 {\~} # d # vert 50 {-} } is a vector representing the decorrelated deviations generating the vector d. Equation (9) can be re-written according to the following equation: underline d ~ = ~ U ~ stack { ert -50 {\~} # d # vert 50 {-} } ~ + ~ underline m(9) Then, combining equations (6) and (10) produces the following equation: p ~ = ~ E ~ [ u ~ s ac k { vert -50 {\~} # d # vert 50 {-} } ~ (U ~ stack { vert -50 {\~} # d # vert 50 {-} } ) sup T ] ~ = ~ U ~ E ~ [ stack { vert -50 {\~} # d # vert 50 {-} } - ( stack { vert -50 {\~} # d # vert 50 {-} } ) sup T ] ~ U sup T (10) By comparing equations (6) and (11 ), it can be seen that D is given by following equation: D ~ = ~ E ~ [ stack { vert -50 {\~} # d # vert 50 {-} } - ( stack { vert -50 {\~} # d # vert 50 {-} } ) sup T ] and that D, as defined above, is a diagonal matrix having the following format: D ~ = ~ SCALESYM 1200 [ MATRIX {{ stack { vert -50 {\~} # sigma }} & vert -50 {0} & vert -50 {0} & vert -50 {...} & vert -50 {0} # vert -50 {0} & { stack { vert -50 {\~} # sigma } } & vert -50 {0}& vert -50 {...} & vert -50 {0} # vert -50 {0} & vert - 50 {0} & { stack { vert -50 {\~} # sigma }. } & vert -50 {...} & vert -50 {0} # STACK { . # . } & STACK { . # . } & STACK { . # . } & STACK { . # . } & STACK { . # . } # vert -50 {0} & vert -50 {0} & vert -50 {0} & vert -50 {...} & { stack { vert -50 {\~} # sigma } } } SCALESYM 1200 ] Variances vert 50 {{ stack { vert -50 {\~} # sigma }} vert -50 stack {2#i}} are then determined from the diagonal matrix D. As can be seen from the above equations, the deviations in the vector { stack { vert -50 {\~} # d # vert 50 {-} } } vert -30 sub i where i varies from 1 to N are uncorrelated and have the variances vert 50 {{ stack { vert -50 {\~} # sigma }} vert -50 stack {2#i}}. The final ^ value for determining a fault is obtained according to the following equation: d [ chi sup 2 ] ~ = ~ stack { vert -50 n # SCALESYM 200 SUM # {i=1 }} {{{{ stack { vert -50 {\~} # d }} vert -50 stack {2#i}}}} over { vert 30{{ stack { vert -50 {\~} # sigma }} vert -50 stack {2#i}}} A normalization to ®* = 1 as required in the definition of ^ will be performed in equation (14). The value d[f^ ] is a single value which has reduced thermal and multipath noise, which represents information regarding a plurality of correlation measurements, and which may be compared to a threshold D in order to determine the existence of a fault. Certain modifications of the present invention have been discussed above. Other modifications will occur to those practicing in the art of the present invention. For example, as described above, the t^ 2 distribution is based on the assumption that all involved distributions are Gaussian. The distributions of d^ may deviate from this assumption and appropriate corrections to the formulas given here may be necessary. Moreover, the-present invention has been described above in connection with the detection of satellite signal faults such as those specified by the FAA, These faults result in signal distortions detectable by use of the present invention. The present invention as embodied by the following claims can also be used to detect other signal distortions such as those arising from multipath and satellite code cross correlation effects. Accordingly, the description of the present invention is to be construed as illustrative only and is for the purpose of teaching those skilled in the art the best mode of carrying out the invention. The details may be varied substantially without departing from the spirit of the invention, and the exclusive use of all modifications which are within the scope of the appended claims is reserved.

Claims: WHAT IS CLAIMED IS: The embodiments of the invention in which an exclusive property or right is claimed are defined as follows: 1. An apparatus for the detection of positioning system satellite signal distortions comprising: a correlator that determines a plurality of correlation measurements at points along a correlation curve, wherein each correlation measurement is based upon a correlation between a received satellite signal and a reference; and, a signal distortion detector that determines differences between the correlation measurements along the correlation curve and that detects a signal distortion from the differences. 2. The apparatus of claim 1 wherein each of the correlation measurements represents a different time shift between the reference and the satellite signal. 3. The apparatus of claim 2 wherein all of the different time shifts are late time shifts. 4. The apparatus of claim 2 wherein all of the different time shifts are early time shifts. 5. The apparatus of claim 2 wherein the different time shifts include a late time shift and an early time shift. 6. The apparatus of claim 2 wherein the different time shifts also includes a zero time shift. 7. The apparatus of claim 1 wherein the signal distortion detector forms a deviation between the differences and expected values of the differences and compares the deviation to a threshold in order to detect existence of the signal distortion. 8. The apparatus of claim 1 wherein the signal distortion detector forms a deviation between each of the differences and a corresponding expected value of the difference and compares each of the deviations to a corresponding threshold in order to detect existence of the signal distortion. 9. The apparatus of claim 1 wherein the signal distortion detector forms a deviation between each of the differences and a corresponding expected value of the difference, wherein the signal distortion detector determines a single deviation value based upon the deviations, and wherein the signal distortion detector compares the single deviation value to a threshold in order to detect existence of the signal distortion. 10. The apparatus of claim 1 wherein the signal distortion detector forms a deviation between each of the differences and an expected value of the corresponding difference, wherein the signal distortion detector determines a covariance matrix based upon statistical properties of the deviations, and wherein the signal distortion detector uses the covariance matrix to perform a ^ procedure on the deviations to create a single deviation indicative of the signal distortion. 11. The apparatus of claim 1 wherein the signal distortion detector detects the signal distortion by forming the following expressions: d sub {ij} ~ - ~ Ed sub {i j} (Claim 11 continued) wherein each dj j is a difference between a pair of correlation measurements i and j, and wherein Edj j is an expected value of the difference dj j when there is no signal distortion. 12. The apparatus of claim 1 wherein the signal distortion detector detects the signal distortion in accordance with the following expressions: LINE d sub {ij} ~ - ~ Ed sub {ij} LINE ~ > ~ D sub {i j} wherein dj j is a difference between a pair of correlation measurements i and j, wherein Edj j is an expected value of the difference dj when there is no signal distortion, and wherein Dj is a threshold. 13. The apparatus of claim 12 wherein the signal distortion detector performs averaging in order to reduce effects of thermal and multipath noise. 14. The apparatus of claim 12 wherein the signal distortion detector performs filtering in order to reduce effects of thermal and multipath noise. . 15. The apparatus of claim 1 wherein the signal distortion detector performs averaging in order to reduce effects of thermal and multipath noise. 16. The apparatus of claim 1 wherein the signal distortion detector performs filtering in order to reduce effects of thermal and multipath noise. 17. A method of detecting signal distortions affecting a signal transmitted by a positioning system satellite comprising: correlating the transmitted signal with a first reference in order to determine a first correlation measurement at a first point along a correlation curve; correlating the transmitted signal with a second reference in order to determine a second correlation measurement at a second point along the correlation curve; correlating the transmitted signal with a third reference in order to determine a third correlation measurement at a third point along the correlation curve; determining a first difference from the first and second correlation measurements; determining a second difference from the second and third correlation measurements; directly comparing the first difference to a first threshold; directly comparing the second difference to a second threshold; and, detecting a signal distortion in the satellite based upon the comparisons of the first and second differences to the first and second thresholds. 18. The method of claim 17 further comprising determining a third difference from the first and third correlation measurements and directly comparing the third difference to a third threshold, wherein the detection of a signal distortion comprises detecting a signal distortion in the satellite based upon the comparison of the first, second, and third differences to the first, second, and third thresholds. 19. The. method of claim 17 wherein the first, second, and third correlation measurements represent different time shifts between the reference and the transmitted signal. 20. The method of claim 19 wherein all of the different time shifts are late time shifts. 21. The method of claim 19 wherein all of the different time shifts are early time shifts. 22. The method of claim 19 wherein the different time shifts include late and early time shifts. 23. The method of claim 19 wherein the different time shifts also includes a zero time shift. 24. The method of claim 17, 18, 19, 20, 21 , 22, or 23 wherein the detection of the signal distortion comprises: forming a deviation between each of the first and second differences and a corresponding expected value for the difference; and, comparing each of the deviations to a corresponding threshold in order to detect existence of the signal distortion. 25. The method of claim 17 wherein the detection of the signal distortion comprises: forming a deviation between each of the differences and a corresponding expected value of the difference; determining a single deviation value based upon the deviations; and, comparing the single deviation value to a threshold in order to detect existence of the signal distortion. 26. The method of claim 17 wherein the detection of the signal distortion comprises: forming a deviation between each of the differences and a corresponding expected value of the difference; determining a covariance matrix and mean values based upon statistical properties of the deviations; and, using the covariance matrix and mean values to perform a ^ procedure on the deviations to create a single deviation value indicative of the signal distortion. 27. The method of claim 26 wherein the detection of the signal distortion comprises comparing the single deviation value to a threshold in order to detect existence of the signal distortion. 28. The method of claim 17, 18, 19, 20, 21 , 22, or 23 wherein the detection of the signal distortion comprises detecting the signal distortion in accordance with the following expression: d sub {ij} Ed sub {i j} wherein dj j is the difference between correlation measurements i and j, and wherein Edj j is the expected value of the difference dj j when there is no signal distortion. 29. The method of claim 17, 18, 19, 20, 21 , 22, or 23 wherein the detection of the signal distortion comprises detecting the signal distortion in accordance with the following expression: LINE d sub {ij} ~ - ~ Ed sub {ij} LINE ~ > ~ D sub {ij} (Claim 29 continued) wherein dj j is the difference between correlation measurements i and j, wherein Edj j is the expected value of the difference dj j when there is no signal distortion, and wherein Dj j is a threshold. 30. The method of claim 17, 18, 19, 20, 21 , 22, or 23 wherein the detection of the signal distortion comprises performing averaging in order to reduce effects of thermal and multipath noise. 31. The method of claim 17, 18, 19, 20, 21 , 22, or 23 wherein the detection of the signal distortion comprises filtering in order to reduce effects of thermal and multipath noise. 32. A method of detecting signal distortions affecting a signal transmitted by a positioning system satellite comprising: correlating the transmitted signal with references in order to determine a plurality of correlation measurements at corresponding points along a correlation curve; determining a single value from N values, wherein each value is formed based on a pair of correlation measurements, and wherein N > 2; comparing the single value to a threshold; and, detecting a signal distortion in the satellite based upon the comparison. 33. The method of claim 32 wherein each of the correlation measurements represents a different time shift between the references and the transmitted signal. 34. The method of claim 33 wherein all of the time shifts are late time shifts. 35. The method of claim 33 wherein all of the time shifts are early time shifts. 36. The method of claim 33 wherein at least one of the time shifts is a late time shift, and wherein at least one of the time shifts is an early time shift. 37. The method of claim 33 wherein the different time shifts also includes a zero time shift. 38. The method of claim 32 wherein the determination of the single value comprises: forming N differences between pairs of the correlation measurements; and, determining the single value from deviations between the N difference and corresponding expected values of the N differences. 39. The method of claim 32 wherein the determination of the single value comprises: forming N differences between pairs of the correlation measurements; forming deviations between the N differences and expected values of the N differences; - determining a covariance matrix and mean values based upon statistical properties of the deviations; using the covariance matrix and mean values to decorrelate the deviations in order to form new deviations that are not correlated; and, performing a ^ procedure on the decorrelated deviations to determine the single value. 40. The method of claim 39 wherein the use of the covariance matrix and mean values to decorrelate the deviations comprises using the covariance to form decorrelated and normalized deviations, and wherein the r^ procedure is performed on the decorrelated and normalized deviations to determine the single value. 41. The method of claim 32 further comprising averaging in order to reduce effects of thermal and multipath noise. 42. The method of claim 32 further comprising filtering in order to reduce effects of thermal and multipath noise. 43. The method of claim 32 wherein the determination of the single value from N pairs of the correlation measurements comprises: defining a covariance matrix P in accordance with the following equation: P ~ = ~ E [ ( underline d underline m ) ( underline d underline m ) sup T ] wherein the underlines indicate vectors, wherein E[A] is a statistical expectation of A, wherein the vector rn is the mean value of the vector d, wherein the vector d is determined in accordance with the following equation: ' {underline d} sup T ~ = ~ ( d sub 1 , d sub 2, d sub 3, d sub 4, . . ., d sub N) wherein N is the number of deviations, wherein the deviations d|< are formed from pairs of the correlation measurements Ij and I j according to the following equation: d sub K ~ = ~ I sub i - - ~ I sub j ~ - - Ed sub K (Claim 43 continued) wherein EdK is expected value of d«; determining an upper triangular matrix U and a diagonal matrix D according to the following equation: P ~ = ~ U D U sup T defining stack { vert -50 {\~} # d # vert 50 {-} } in accordance with the following equation: stack { vert -50 {\~} # d # vert 50 {-} } ~ = ~ U sup {-1} ( underline d ~ - ~ underline m) wherein stack { vert -50 {\~} # d # vert 50 {-} } is a vector representing the decorrelated deviations generating the vector d; producing the following equation from the equations above: P ~ = ~ E ~ [ U ~ stack { vert -50 {\~} # d # vert 50 {-} } ~ (U - stack { vert -50 {\~} # d # vert 50 {-} } ) sup T ] ~ = ~ U ~ E ~ [ stack { vert -50 {\~} # d # vert 50 B } ~ ( stack { vert -50 {\~} # d # vert 50 {-} } ) sup T ] ~ U sup T determining the following equation from the equations above: D ~ = ~ E ~ [ stack { vert -50 {\~} # d # vert 50 {-} } - ( stack { vert -50 {\~} # d # vert 50 {-} } ) sup T ] wherein D has the following format: (Claim 43 continued) D ~ = - SCALESYM 1200 [ MATRIX {{ stack { vert -50 {\~} # sigma }} & vert -50 {0} & vert -50 {0} & vert -50 {...}& vert -50 {0} # vert -50 {0} & { stack { vert -50 {\~} # sigma } } & vert -50 {0}& vert -50 {...} & vert -50 {0} # vert -50 {0} & vert - 50 {0} & { stack { vert -50 {\~} # sigma } } & vert -50 {...}& vert -50 {0} # STACK {.#.}& STACK {.#.}& STACK {.#.}& STACK {.#.}& STACK {.#.}# vert -50 {0} & vert -50 {0} & vert -50 {0} & vert -50 {...}&{ stack { vert -50 {\~} # sigma } } } SCALESYM 1200 ] determining variances vert 50 {{ stack { vert -50 {\~} # sigma }} vert -50 stack {2#i}} from D above; p determining a final r^ value according to the following equation: d [ chi sup 2 ] ~ = ~ stack { n # SCALESYM 200 SUM # {i=1}} {{{{ stack { vert - 50 {\~} # d }} vert -50 stack {2#i}}}} over { vert 30{{ stack { vert -50 {\~} # sigma }} vert -50 stack {2#i}}} and comparing d[r^ 2 ] to a threshold D in order to determine existence of a signal distortion.

Inventors: BRENNER MATS A, BRENNER, MATS, A.
Applicants: HONEYWELL INT INC, HONEYWELL INTERNATIONAL INC.
Application year: 2001
Main classification: G01S
IPC codes: G01C21, G01S1, G01S5