JP2012194099A - Pseudo-distance error estimation method, position calculation method and pseudo-distance error estimation apparatus - Google Patents

Abstract

PROBLEM TO BE SOLVED: To propose a novel technique for estimating an error included in a pseudo distance.SOLUTION: A satellite signal is received from a satellite and an observation pseudo distance from a receiving point to the satellite is determined. Furthermore, a Doppler frequency of the received satellite signal is measured, and the Doppler frequency is used to calculate a predictive pseudo distance. The observation pseudo distance and the predictive pseudo distance are then used to estimate a first error included in the observation pseudo distance. On the other hand, a given receiving position is used to estimate a second error included in the observation pseudo distance. The first error and the second error are then used to estimate an intrinsic error included in the observation pseudo distance.

Description

  The present invention relates to a method for estimating an error included in an observed pseudorange.

  A GPS (Global Positioning System) is widely known as a positioning system using positioning signals, and is used in a GPS receiver built in a mobile phone or a car navigation device. In GPS, positioning calculation using information such as positions of a plurality of GPS satellites and pseudo distances to the respective GPS satellites is performed to obtain a position (positional coordinates) of the GPS receiver and a clock error (clock bias).

  As the positioning calculation, a so-called least-squares method that minimizes the sum of squares of errors that can be included in a pseudorange (hereinafter referred to as “observation pseudorange”) observed by a GPS receiver for each of a plurality of positioning satellites. The positioning calculation using the is widely used (for example, Patent Document 1).

JP 2009-97897 A

  The positioning calculation using the conventional least square method is based on a method that assumes that the error that can be included in the observed pseudorange is a value near zero for each positioning satellite. In mathematical terms, the positioning calculation is performed on the assumption that all of the captured positioning satellites follow a normal distribution in which the observation pseudorange error is zero in the expected value. However, in the satellite positioning system, there are various error factors, and the observation pseudorange can include various errors.

  For example, in a so-called multipath environment, a satellite signal reaches a GPS receiver through two or more paths. The signal received by the GPS receiver is a direct wave signal that is a satellite signal transmitted from a positioning satellite, a reflected wave reflected on a building, the ground, etc., a transmitted wave that has passed through an obstacle, and a diffracted wave that has been diffracted by an obstacle. It becomes a signal (multipath signal) on which an indirect wave signal such as is superimposed. The indirect wave signal reaches the GPS receiver with a longer path length than the direct wave signal. For this reason, the observation pseudorange may include a large error due to the presence of the indirect wave signal.

  Therefore, assuming that the observation pseudorange error is a normal distribution with an expected value of zero, the positioning calculation may be a positioning calculation that does not match the actual environment. Therefore, there is a problem that the accuracy of position calculation is reduced in an environment such as a multipath environment or an indoor environment where the pseudo-range error distribution does not always follow a normal distribution with an expected value of zero.

  The present invention has been made in view of the above-described problems, and an object thereof is to propose a new method for estimating an error included in an observation pseudorange.

  A first mode for solving the above problems is to receive a satellite signal from a satellite, obtain an observation pseudorange that is an observation value of a pseudorange from the reception point to the satellite, and the received satellite signal. Measuring the Doppler frequency, calculating the predicted pseudorange by predicting the pseudorange using the Doppler frequency, and using the observed pseudorange and the predicted pseudorange, Estimating a first error included, estimating a second error included in the observed pseudorange using a given reception position, the first error and the first error 2 is used to estimate a true error included in the observed pseudorange, and a pseudorange error estimation method.

  Further, as another form, a pseudorange observation unit that receives a satellite signal from a satellite and obtains an observation pseudorange that is an observation value of a pseudorange from the reception point to the satellite, and a Doppler frequency of the received satellite signal Using the Doppler measurement unit to measure, the pseudo-range prediction unit for calculating the predicted pseudo-range predicting the pseudo-range using the Doppler frequency, the observation pseudo-distance using the observation pseudo-range and the predicted pseudo-distance A first error estimator that estimates a first error included in the second error estimation unit that estimates a second error included in the observed pseudorange using a given reception position And a true error estimation unit that estimates a true error included in the observed pseudo distance using the first error and the second error. May be.

  According to the first embodiment, a satellite signal is received from a satellite, and an observation pseudo distance from the reception point to the satellite is obtained. On the other hand, the Doppler frequency of the received satellite signal is measured, and the predicted pseudorange is calculated using the Doppler frequency. Then, the first error included in the observed pseudorange is estimated using the observed pseudorange and the predicted pseudorange. If the accuracy of the predicted pseudorange is guaranteed, the error (first error) included in the observed pseudorange can be correctly estimated. However, since the measurement error may be included in the Doppler frequency, there is a possibility that the error is superimposed on the predicted pseudorange, and the first error is not necessarily accurate.

  Therefore, an error (second error) included in the observation pseudorange is estimated using a given reception position. As long as the reception position is set appropriately, the error included in the observed pseudorange can be estimated with a certain degree of accuracy. Then, by using the first error and the second error estimated by different methods as described above, it is possible to estimate a correct error (authentication error) included in the observation pseudorange.

  Further, as a second mode, in the pseudo-range error estimation method of the first mode, estimating the genuine error includes calculating a difference between the first error and the second error, The pseudo-range error estimation method may be configured to include correcting the first error using the difference calculation result for the period.

  According to the second mode, the difference between the first error and the second error is calculated. If the accuracy of the second error is guaranteed, the above difference can be regarded as an offset of the first error from the true error included in the observed pseudorange. Therefore, the first error can be appropriately corrected by using the difference calculation result for a predetermined period.

  Further, as a third mode, in the pseudo distance error estimation method according to the second mode, the correction may be performed by using the result obtained by averaging the calculation results of the difference for the predetermined period to reduce the first error. It is good also as comprising the pseudorange error estimation method which is correcting.

  According to the third embodiment, the true error included in the observation pseudorange is more accurately estimated by correcting the first error using the result of averaging the difference calculation results for the predetermined period. Can do.

  Further, as a fourth aspect, in the pseudo distance error estimation method of any one of the first to third aspects, calculating the predicted pseudo distance includes calculating a line-of-sight speed using the Doppler frequency; The pseudo distance error estimation method may be configured to include calculating the predicted pseudo distance by integrating the line-of-sight speed.

  According to the fourth embodiment, the line-of-sight speed is calculated using the Doppler frequency. The line-of-sight speed is a relative speed (relative speed) with the satellite with respect to the line-of-sight direction. Since the pseudo distance is the distance between the receiving point and the satellite with respect to the line-of-sight direction, the predicted pseudo-range can be appropriately obtained by integrating the line-of-sight speed.

  Further, as a fifth aspect, the pseudo distance error is estimated using the pseudo distance error estimation method according to any one of the first to fourth aspects, and a predetermined pseudo value using the estimated pseudo distance error as an expected value. It is also possible to configure a position calculation method including calculating the position of the reception point using the distance error distribution and the observation pseudo distance.

  According to the fifth aspect, the reception point is obtained by using the predetermined pseudorange error distribution having the pseudorange error estimated using the pseudorange error estimation method of the above form and the observed pseudorange. Can be determined appropriately.

  Further, as a sixth form, in the position calculation method of the fifth form, the pseudorange error distribution is a distribution defined by an expected value of the pseudorange error and a standard deviation of the pseudorange error, and the satellite The position calculation method may be configured to further include setting the standard deviation of the pseudorange error distribution using a model in which signal quality of the signal is associated with the standard deviation.

  According to the sixth embodiment, by using a model in which the signal quality of the satellite signal is associated with the standard deviation, the standard deviation of the pseudorange error distribution can be set appropriately, and as a result, the accuracy of position calculation is increased. Can be improved.

  Further, as a seventh aspect, in the position calculation method according to the sixth aspect, the model is determined for each positioning environment, further including determining a positioning environment, and the setting includes determining the determined positioning environment It is good also as comprising a position calculation method including setting the said standard deviation using the model corresponding to.

  According to the seventh embodiment, the positioning environment is determined. Then, by setting the standard deviation of the pseudorange error distribution using a model corresponding to the determined positioning environment, it is possible to perform position calculation using an appropriate pseudorange error distribution suitable for the positioning environment.

Explanatory drawing of pseudorange error distribution. Explanatory drawing of multipath. The figure which shows an example of an autocorrelation. The figure which shows an example of the autocorrelation in a multipath environment. The figure which shows an example of the autocorrelation in a multipath environment. The figure which shows an example of the time change of the pseudo distance error actual measurement value in a multipath environment. Explanatory drawing of each quantity which concerns on a pseudo distance. Explanatory drawing of an observation pseudorange and a prediction pseudorange. Explanatory drawing of the 1st and 2nd pseudo distance estimation error. The figure which shows an example of the time change of the pseudo distance error estimated value in a multipath environment. The block diagram which shows an example of a function structure of a portable telephone. The figure which shows an example of the circuit structure of the baseband process circuit part in 1st Example. The flowchart which shows the flow of a 1st baseband process. The flowchart which shows the flow of a pseudo distance error estimation process. The figure which shows an example of the experimental result which performed position calculation. The figure which shows an example of the data structure of the memory | storage part in 2nd Example. (A) An example of an indoor model A, (B) an example of an indoor model B, (C) an example of an outdoor model. The flowchart which shows the flow of a 2nd baseband process.

  Hereinafter, preferred embodiments to which the present invention is applied will be described with reference to the drawings. The present embodiment is an embodiment to which a GPS (Global Positioning System) which is a kind of satellite positioning system is applied. Of course, embodiments to which the present invention can be applied are not limited to the embodiments described below.

1. Principle A pseudo-range error estimation method (pseudo-range error estimation principle) in this embodiment will be described. In a satellite positioning system using GPS, a GPS satellite, which is a kind of positioning satellite, transmits navigation data including satellite orbit data such as ephemeris and almanac on a GPS satellite signal, which is a kind of positioning satellite signal. ing.

  The GPS satellite signal is a 1.57542 [GHz] communication signal modulated by a CDMA (Code Division Multiple Access) method known as a spread spectrum method by a C / A (Coarse and Acquisition) code which is a kind of spreading code. is there. The C / A code is a pseudo random noise code having a repetition period of 1 ms with a code length of 1023 chips as one PN frame, and is a code unique to each GPS satellite.

  In GPS, the position of a reception point (GPS antenna) is calculated by performing positioning calculation using information such as the position of a plurality of GPS satellites and a pseudo distance from each GPS satellite to a GPS satellite signal reception point. calculate. In the present embodiment, a GPS receiver is assumed in which a GPS antenna and a calculation portion that performs calculation processing on a GPS satellite signal received by the GPS antenna are integrally configured. That is, the calculation of the position of the reception point will be described as having the same meaning as the calculation of the position of the receiver. Note that the signal reception point (antenna) and the calculation portion do not necessarily have to be arranged and configured integrally, and may be arranged and configured separately.

  The pseudorange is obtained using a code phase obtained by performing a correlation calculation in a phase direction (hereinafter referred to as “phase search”) on a signal that has received a GPS satellite signal. The code phase is the phase of the C / A code of the GPS satellite signal received by the GPS receiver. Ideally, it can be considered that a plurality of C / A codes are arranged between the GPS satellite and the GPS receiver. The distance between the GPS satellite and the GPS receiver is not necessarily an integral multiple of the C / A code, and a fractional part may occur. The code phase corresponds to the fractional part of the pseudo distance. The integer part of the pseudorange can be obtained from the approximate positions of the GPS receiver and the GPS satellite.

  In the present embodiment, “pseudo distance” is described as indicating the entire observed distance (integer part + fractional part) between the GPS satellite and the GPS receiver in principle, but only the code phase (fractional part). Of course, it is also possible to constitute the embodiment by referring to.

  In the satellite positioning system using GPS, there are various error factors, and therefore various errors are superimposed on the observation pseudorange observed by the GPS receiver. For example, an error of a satellite clock, an error of satellite orbit information, an ionosphere delay, a troposphere delay, an error due to a noise signal generated inside the GPS receiver, and the like. In the present specification, an error included in the observed pseudorange is referred to as a “pseudorange error”. In the positioning calculation using GPS, positioning calculation using a so-called least square method that minimizes the sum of squares of pseudorange errors (residuals) related to each GPS satellite is widely used. At this time, a normal distribution is assumed as a pseudo-range error distribution (hereinafter referred to as “pseudo-range error distribution”).

  FIG. 1 is an explanatory diagram of a pseudorange error distribution. In FIG. 1, the horizontal axis represents the pseudorange error “ε”, and the vertical axis represents the probability density “f (ε)”. Expected value of pseudorange error “ε” (hereinafter referred to as “pseudorange error expected value”) “μ” and standard deviation of pseudorange error “ε” (hereinafter referred to as “pseudorange error standard deviation”) The conventional general method is to set “σ” to a fixed value. Specifically, the calculation is generally performed assuming that “μ = 0” and “σ = 1”. However, this assumption is not necessarily correct. A typical example is a multipath environment.

  FIG. 2 is an explanatory diagram of a multipath environment. The direct wave signal is indicated by a dotted line, and the indirect wave signal is indicated by a one-dot chain line. Due to the presence of the indirect wave signal, an error occurs in the observation pseudorange observed by the GPS receiver. The observation pseudorange is calculated using the code phase acquired by the GPS receiver by performing a phase search. In a multipath environment, an error is superimposed on the code phase. The code phase error may be a positive error or a negative error with respect to the true code phase.

  FIG. 3 is an explanatory diagram of the principle of code phase detection. FIG. 3 shows a schematic example of the autocorrelation value of the C / A code, where the horizontal axis is the code phase and the vertical axis is the correlation value. In the following description, the correlation value means the magnitude (absolute value) of the correlation value.

  The autocorrelation value of the C / A code is ideally represented by a substantially triangular shape that is symmetrical with the peak value at the apex. In this case, the phase corresponding to the peak value of the correlation value (hereinafter referred to as “correlation peak value”) is the phase of the C / A code of the received GPS satellite signal. In order to detect a correlation peak value, a code phase advanced by a certain amount with respect to a certain code phase (hereinafter referred to as “leading phase”) and a code phase delayed by a certain amount (hereinafter referred to as “delayed phase”) ). Then, a correlation value in which the correlation value of the lead phase and the correlation value of the lag phase are equal is detected as a correlation peak value.

  In FIG. 3, since the correlation value is a substantially symmetrical triangle, the correlation value of the code phase at the center of the correlation value of the lead phase and the correlation value of the lag phase is the correlation peak value, and the corresponding code phase is “ Detected as “peak phase”. This detected peak phase is referred to as “detected peak phase”. The shape of the correlation value in FIG. 3 is an ideal shape, but the shape of the correlation value changes in a multipath environment.

  4 and 5 are diagrams illustrating an example of the shape of a correlation value in a multipath environment. FIG. 4 is an example of a correlation value graph when the indirect wave signal arrives at the same phase as the direct wave signal, and FIG. 5 shows the correlation value when the indirect wave signal arrives at the opposite phase to the direct wave signal. It is an example of a graph. In these drawings, graphs of correlation values corresponding to a direct wave signal, an indirect wave signal, and a multipath signal obtained by synthesizing the direct wave signal and the indirect wave signal are shown. The horizontal axis is the code phase, and the vertical axis is the correlation value.

  The correlation value for the indirect wave signal has a substantially triangular shape like the correlation value for the direct wave signal, but the correlation peak value of the indirect wave signal is smaller than the correlation peak value of the direct wave signal. This is because the GPS satellite signal transmitted from the GPS satellite is reflected at the building or the ground or transmitted through an obstacle, so that the signal intensity at the time of transmission is weakened at the time of reception.

  The peak phase of the indirect wave signal is delayed from the peak phase of the direct wave signal. This is because the propagation distance from the GPS satellite to the GPS receiver is increased by the GPS satellite signal transmitted from the GPS satellite being reflected on the building or the ground or diffracting the obstacle. Since the correlation value for the multipath signal is the sum of the correlation value of the direct wave signal and the correlation value of the indirect wave signal, the triangular shape is distorted and is not symmetrical with respect to the peak value.

  When the indirect wave signal reaches the GPS receiver in the same phase as the direct wave signal, the direct wave signal and the indirect wave signal strengthen each other. For this reason, the correlation value of the composite wave signal is the sum of the magnitude of the correlation value for the direct wave signal and the magnitude of the correlation value for the indirect wave signal. In this case, the shape of the correlation value is, for example, as shown in FIG. In FIG. 4, the detected peak phase is a phase delayed from the true peak phase.

  On the other hand, when the indirect wave signal has a phase opposite to that of the direct wave signal, such as a range of a half cycle or more and less than one cycle, the direct wave signal and the indirect wave signal weaken each other. For this reason, the correlation value of the synthesized wave signal is a value obtained by subtracting the magnitude of the correlation value for the indirect wave signal from the magnitude of the correlation value for the direct wave signal. In this case, the shape of the correlation value is, for example, as shown in FIG. In FIG. 5, the detected peak phase is a phase advanced from the true peak phase.

  Here, the phase difference between the detected peak phase and the true peak phase is defined as “code phase error”. For convenience, the sign of the code phase error when the detected peak phase is behind the true peak phase is “positive”, and the code phase error when the detected peak phase is ahead of the true peak phase. The sign is defined as “negative”. In this case, the code phase error is “positive” in FIG. 4, and the code phase error is “negative” in FIG.

  As described above, since the pseudo distance is calculated using the code phase, the code phase error is superimposed on the pseudo distance as an error. That is, when a positive error is included in the code phase as shown in FIG. 4, the positive error is superimposed as a pseudorange error “ε”. On the other hand, when a negative error is included in the code phase as shown in FIG. 5, the negative error is superimposed as the pseudorange error “ε”.

  In this way, in the multipath environment, the pseudorange error “ε” can take a positive or negative value according to the positive or negative of the code phase error. Further, since the magnitude (absolute value) of the code phase error also changes at any time, the magnitude of the pseudo distance error “ε” also changes at any time.

  FIG. 6 is a graph showing a result of an experiment for actually measuring a pseudorange error in a multipath environment. In FIG. 6, the horizontal axis represents time “T”, and the vertical axis represents the measured pseudorange error (unit: meters) and the signal intensity. The pseudo distance error actual measurement value is shown by a black diamond plot, and the signal intensity is shown by a rectangular plot.

  From this graph, it can be seen that the pseudo-range error actual measurement value changes with time so as to follow the time change of the signal intensity. It should be noted that the measured pseudo-range error value changes across the positive and negative regions, and the amplitude thereof also changes in magnitude.

  From this result, in a multipath environment, etc., assuming that the observed pseudorange error is a normal distribution with zero expected value, positioning calculation is performed assuming an error distribution that does not match the actual environment. I understand that. Considering this in reverse, if a pseudo-range error that follows (matches) the actual pseudo-range error measured value shown in FIG. 6 can be estimated, positioning calculation can be performed assuming an error distribution according to the actual environment. I can say that.

  Therefore, in this embodiment, the pseudorange error is estimated by the following procedure. First, a GPS satellite signal is received from a GPS satellite, and an observation pseudo distance that is an observation value of a pseudo distance from the GPS receiver to the GPS satellite is obtained. On the other hand, the Doppler frequency of the received GPS satellite signal is measured, and a predicted pseudorange in which the pseudorange is predicted is calculated using the Doppler frequency.

The Doppler frequency corresponds to a frequency deviation of the reception frequency from the specified carrier frequency by Doppler caused by the movement of the GPS satellite and the GPS receiver. Specifically, the following equation (1) is established regarding the reception frequency and the Doppler frequency.

In Expression (1), “f” is a reception frequency, “f ₀ ” is a specified carrier frequency, and “f _d ” is a Doppler frequency. The specified carrier frequency “f ₀ ” is 1.57542 [GHz]. Also, the Doppler frequency “f _d ” can be obtained by performing a correlation calculation (frequency search) in the frequency direction on the received signal. Therefore, the reception frequency “f” is also determined.

At this time, the line-of-sight velocity can be calculated using the Doppler frequency “f _d ”. In the present embodiment, the line-of-sight speed means a relative speed (relative speed) between the GPS receiver and the GPS satellite with respect to the line-of-sight direction, that is, a relative line-of-sight speed. Specifically, for example, the line-of-sight velocity “V _R ” can be calculated according to the following equation (2).
However, “c” is the speed of light.

On the other hand, the pseudorange is a distance between the GPS receiver and the GPS satellite along the line-of-sight direction. Therefore, the relationship of the following equation (3) is established between the pseudo distance “ρ (t)” and the line-of-sight velocity “V _R (t)”.

According to the equation (3), the pseudo distance “ρ (t)” can be predicted by integrating the line-of-sight velocity “V _R (t)”. That is, the Doppler frequency “f _d ” of the received GPS satellite signal is measured, and the line-of-sight velocity “V _R ” is calculated using the Doppler frequency “f _d ”. Then, the predicted pseudorange (predicted value of the pseudorange) is obtained by integrating the calculated line-of-sight velocity “V _R ”.

This will be described in detail. Consider discrete times “T = T ₀ , T ₁ , T ₂ ,..., T _n ,. The subscript indicates the time number. At this time, the predicted pseudorange “P (T _n )” at time “T _n ” is calculated according to the following equation (4), for example.

In Expression (4), “C (T ₀ )” represents the observed pseudorange at time “T ₀ ”, and “ΔP (T _n )” represents the amount of change in the predicted pseudorange at time “T _n ” (hereinafter, “ This is referred to as “pseudo-range change amount”. The pseudo-range variation “ΔP (T _n )” is obtained by averaging the line-of-sight velocity “V _R (T _n )” at the current time and the line-of-sight velocity “V _R (T _n−1 )” at the previous time. It is obtained by multiplying the time difference “ΔT = T _n −T _n-1 ” between the time and the previous time.

Equation (4) is obtained by integrating and adding the line-of-sight velocity to the pseudorange observed at a reference time “T ₀ ” (hereinafter referred to as “reference observation pseudorange”). It means to predict the distance. This prediction method is a method based on propagation that propagates a pseudorange from one time to the next.

Here, the observation pseudorange “C (T)” is an actual observation value of the pseudorange. On the other hand, the predicted pseudorange “P (T)” is a predicted value of the pseudorange. Therefore, the difference between the observed pseudorange “C (T)” and the predicted pseudorange “P (T)” can be estimated as an error (first error) included in the observed pseudorange. Therefore, the first pseudo distance estimation error “E (T)” is calculated according to the following equation (5).

FIG. 7 is an explanatory diagram of various quantities related to the pseudo distance. In order to simplify the explanation, a situation where the GPS receiver is stopped (a situation where the GPS receiver is stationary at a certain point) is assumed. Let the position of the GPS receiver be A. A position of a GPS satellite at time “T _n-1 ” is B, and a position at time “T _n ” is C. The velocity vector of the GPS satellite at time “T _n-1 ” is illustrated as “V _SV (T _n−1 )” in vector notation, and the velocity vector of the GPS satellite at time “T _n ” is represented as “V _SV ( illustrated as T _n) ". Further, the time difference between the times “T _n ” and “T _n−1 ” is illustrated as “Δt = T _n −T _n−1 ”.

First, consider the time “T _n-1 ”. The observation pseudorange observed by the GPS receiver at time “T _n-1 ” is represented by “BA = C (T _n-1 )”. Further, since the GPS receiver is stopped, the relative velocity vector _{"V R (T n-1} )" for the viewing direction, the projection of the GPS satellites velocity vector _{"V SV (T n-1} )" to the viewing direction Vector. In this case, it is assumed that “BD = P (T _n−1 )” is obtained as a predicted pseudo distance as a result of predicting the pseudo distance at time “T _n−1 ”. In this case, according to Equation (5), the first pseudo-range estimation error at time “T _n-1 ” is “E (T _n−1 ) = DA = BA−BD = C (T _n−1 ) −. P (T _n-1 ) ".

Next, consider the time “T _n ”. The observation pseudorange observed by the GPS receiver at time “T _n ” is represented by “CA = C (T _n )”. Further, since the GPS receiver is stopped, the relative velocity vector "V _R (T _n)" is for line-of-sight direction, a vector obtained by projecting the GPS satellites velocity vector "V _SV (T _n)" in the line of sight direction . In this case, the line segment “CE = P (T _n−1 ) having the same length as the predicted pseudorange“ BD = P (T _n−1 ) ”obtained at time“ T _n−1 ”with respect to the line-of-sight direction. ”Is assumed (BD = CE).

In this case, in Equation (4), the average speed of the line-of-sight speeds “V _R (T _n )” and “V _R (T _n−1 )” is multiplied by the time difference “ΔT = T _n −T _n-1 ”. Thus, the pseudo distance change amount “ΔP (T _n )” at time “T _n ” is obtained. If this is expressed by “EF = ΔP (T _n )”, the predicted pseudorange “P (T _n )” at time “T _n ” is “P (T _n ) = CF = CE + EF = P (T _n )”. ₋₁ ) + ΔP (T _n ) ”. Further, from the equation (5), the first pseudo-range estimation error at time “T _n ” is “E (T _n ) = FA = CA−CF = C (T _n ) −P (T _n )”.

  FIG. 8 is a graph showing an example of experimental results obtained by actually measuring the observed pseudorange “C (T)” and the predicted pseudorange “P (T)” in the situation of FIG. In FIG. 8, the horizontal axis is time “T (unit is second)”, and the vertical axis is pseudo distance (unit is meter). The observed pseudorange “C (T)” is indicated by a round plot, and the predicted pseudorange “P (T)” is indicated by a rectangular plot. However, the pseudo distance shown here is the distance of the fractional part corresponding to the code phase.

  From this figure, it can be seen that the observed pseudorange “C (T)” and the predicted pseudorange “P (T)” both increase with time. This is a result indicating that the GPS receiver is stopped while the GPS satellite is moving, and the GPS satellite is gradually moving away from the GPS receiver. In addition, the observed pseudorange “C (T)” indicates a temporal change that oscillates up and down, but the predicted pseudorange “P (T)” indicates a smooth temporal change.

The first pseudo-range estimation error “E (T)” calculated by Expression (5) corresponds to an error included in the observed pseudo-range. However, this value cannot be trusted immediately. This is because the predicted pseudorange “P (T)” is not always correct. That is, due to the frequency accuracy of the clock (crystal oscillator) included in the GPS receiver, the measured Doppler frequency “f _d ” may include a measurement error. The measurement error of the Doppler frequency “f _d ” is superimposed on the predicted pseudorange “P (T)” as an error.

As a result, the temporal change of the predicted pseudorange “P (T)” shown in FIG. 8 is increased as a whole by the measurement error of the Doppler frequency “f _d ”. For this reason, the predicted pseudo distance raised to the first pseudo distance estimation error “E (T)” obtained by subtracting the predicted pseudo distance “P (T)” from the observed pseudo distance “C (T)” is also increased. There is a possibility that the error is superimposed by the error of “P (T)”. Therefore, in order to estimate the correct error (authentication error) included in the observation pseudorange “C (T)”, it is necessary to correct the error.

  Therefore, in this embodiment, the observation pseudorange is obtained by using the first pseudorange estimation error (first error) and the second pseudorange estimation error (second error) for which a certain degree of accuracy is guaranteed. The true error contained in is estimated. The second pseudorange estimation error is estimated using a given reception position.

In GPS, for example, positioning calculation for obtaining a position vector “p” and a clock bias “b” of the GPS receiver is performed according to an observation equation expressed by the following equation (6).

  In the equation (6), the vector “δρ” is a pseudo distance correction amount vector whose component is the correction amount of the pseudo distance of each captured GPS satellite. The matrix “G” on the right side is a geometric matrix that determines the satellite arrangement of each captured satellite. The vector “δp” is a position correction amount vector that is a correction amount of the position vector of the GPS receiver, and “δb” is a clock bias correction amount. The vector “ε” is a pseudorange error vector whose component is an error of the observation pseudorange of each captured satellite. Note that since the observation equation itself of Equation (6) is known per se, description of the derivation process and the like will be omitted.

  In the positioning calculation, “δp” and “δb” are approximately obtained by using the position correction amount vector “δp” and the clock bias correction amount “δb” as unknowns, for example, using the least square method or the Kalman filter. Then, using the obtained “δp” and “δb”, the position vector “p” and the clock bias “b” are corrected.

  If the position vector “p”, the position correction amount vector “δp”, the clock bias “b”, and the clock bias correction amount “δb” obtained in the past by the positioning calculation are used, the pseudo-range error vector “ε” is obtained from the equation (6). Can be calculated backwards. That is, the second pseudo-range estimation error can be estimated using the position of the GPS receiver obtained by the positioning calculation as a given reception position.

In this case, for one GPS satellite, the second pseudorange estimation error “Z (T _n )” at time “T _n ” is calculated according to the following equation (7).

  Expression (7) is an expression obtained by rewriting Expression (6) into an expression related to one GPS satellite and solving for the pseudorange error “ε”. However, “l” is the line-of-sight vector of the GPS satellite.

  FIG. 9 is a graph showing an example of experimental results obtained by actually measuring the first pseudo-range estimation error “E (T)” and the second pseudo-range estimation error “Z (T)”. In FIG. 9, the horizontal axis represents time “T (unit: seconds)”, and the vertical axis represents pseudorange estimation error (unit: meters). Further, the first pseudo distance estimation error “E (T)” is indicated by a triangular plot, and the second pseudo distance estimation error “Z (T)” is indicated by a diamond plot.

  In the experimental results shown and described in FIG. 8, by subtracting the predicted pseudorange “P (T)” from the observed pseudorange “C (T)”, the first pseudorange estimation error “E (T) in FIG. ) ”. Further, the second pseudo-range estimation error “Z (T)” of FIG. 9 is obtained by back-calculating the pseudo-range error “ε” using the past positioning results.

  As can be seen from FIG. 9, the first pseudo-range estimation error “E (T)” and the second pseudo-range estimation error “Z (T)” show almost the same tendency of time change. . However, the overall value of the first pseudo-range estimation error “E (T)” is relatively higher than the overall value of the second pseudo-range estimation error “Z (T)”. . This relative value difference is an error inherent in the predicted pseudorange “P (T)” in FIG. 8.

  In order to correct this error, in the present embodiment, the first pseudo-range estimation error “E (T)” is corrected using the second pseudo-range estimation error “Z (T)” for a predetermined period. . For example, the predetermined period may be defined as N hours retroactively from the current time, or may be determined as N times retroactively from the current timing when estimating the pseudorange error at predetermined time intervals. The value of “N” can be set as appropriate. However, as a result of repeated experiments by the inventor of the present application, for example, if the pseudorange error is estimated at intervals of 1 second, by setting “N = 10”, It was found that the pseudorange estimation error “E (T)” of 1 can be corrected effectively. It is preferable that at least “N ≧ 2”.

Specifically, according to the following equation (8), the difference between the first pseudorange estimation error “E (T)” and the second pseudorange estimation error “Z (T)” is expressed as a pseudorange error offset value “E _offset. (T) ".

If the accuracy of the second pseudorange estimation error “Z (T)” is sufficiently guaranteed, the pseudorange error offset value “E _offset (T)” calculated according to the equation (8) is It can be regarded as an offset of the first pseudo-range estimation error “E (T)” from the included true error.

Therefore, the first pseudo distance estimation error “E (T)” is corrected using, for example, the following equation (9), using the pseudo distance error offset value “E _offset (T)” for a predetermined period.

In Expression (9), “E _estimate (T)” indicates an estimated value of the pseudorange error (pseudorange error estimate). “AveE _offset (T)” indicates an average pseudo-range error offset value. It is an equation indicating that the first pseudo-range estimation error “E (T)” is corrected using the result of averaging the past N pseudo-range error offset values “E _offset (T)”.

FIG. 10 is a graph showing an example of an experimental result obtained by actually calculating the pseudorange error estimated value “E _estimate (T)” in the multipath environment. In FIG. 10, the horizontal axis represents time “T”, and the vertical axis represents pseudorange error (unit: meters). The pseudorange error estimated value “E _estimate (T)” is shown by a diamond plot.

When the graph of FIG. 10 is compared with the graph of FIG. 6, a pseudo-range error estimated value “E _estimate (T)” that follows the temporal change of the pseudo-range error actual measurement value shown in FIG. 6 is obtained. I understand. Therefore, it was proved that the pseudorange error can be accurately estimated even in a multipath environment by using the pseudorange error estimation method.

The pseudo distance error estimated value “E _estimate (T)” finally obtained is set as the pseudo distance error expected value “μ = μ (T)” shown and described in FIG. Then, using the pseudorange error distribution defined by the set pseudorange error expected value “μ = μ (T)”, positioning calculation using the least square method is performed.

  The above pseudorange error estimation method is effective when applied to each satellite individually. In other words, by estimating the pseudorange error for each satellite and setting the expected pseudorange error value, the pseudorange error distribution is individually defined for each satellite. Then, using the pseudorange error distribution defined for each satellite and the observed pseudorange observed for each satellite, for example, a convergence operation based on the Newton-Raphson method is performed, and the position vector and clock of the GPS receiver are calculated. Find approximate bias solution.

2. Embodiment Next, an embodiment of a pseudo distance error estimation apparatus and a position calculation apparatus that perform pseudo distance error estimation and position calculation based on the above principle will be described. Here, a mobile phone will be described as an example of an electronic device including a pseudo-range error estimation device and a position calculation device. First, the configuration of the mobile phone common to the embodiments will be described.

  FIG. 11 is a block diagram illustrating an example of a functional configuration of the mobile phone 1 according to the embodiment. The mobile phone 1 includes a GPS antenna 5, a GPS receiving unit 10, a host processing unit 30, an operation unit 40, a display unit 50, a mobile phone antenna 60, a mobile phone wireless communication circuit unit 70, A storage unit 80 and a clock unit 90 are provided.

  The GPS antenna 5 is a reception point (antenna) that receives an RF (Radio Frequency) signal including a GPS satellite signal transmitted from a GPS satellite, and outputs the received signal to the GPS receiver 10.

  The GPS receiver 10 is a calculation part that calculates and calculates the position and the like of the mobile phone 1 based on a signal input from the GPS antenna 5. In this embodiment, the GPS receiving unit 10 corresponds to a pseudorange error estimation device and a position calculation device.

  The GPS receiving unit 10 includes an RF receiving circuit unit 11 and a baseband processing circuit unit 20. The RF receiving circuit unit 11 and the baseband processing circuit unit 20 can be manufactured as separate LSIs (Large Scale Integration) or can be manufactured as one chip.

  The RF receiving circuit unit 11 is an RF signal receiving circuit. As a circuit configuration, for example, a receiving circuit that converts an RF signal output from the GPS antenna 5 into a digital signal by an A / D converter and processes the digital signal may be configured. Alternatively, the RF signal output from the GPS antenna 5 may be processed as an analog signal and finally A / D converted to output a digital signal to the baseband processing circuit unit 20.

  In the latter case, for example, the RF receiving circuit unit 11 can be configured as follows. That is, an oscillation signal for RF signal multiplication is generated by dividing or multiplying a predetermined oscillation signal. Then, by multiplying the generated oscillation signal by the RF signal output from the GPS antenna 5, the RF signal is down-converted to an intermediate frequency signal (hereinafter referred to as an "IF (Intermediate Frequency) signal"), After the IF signal is amplified, it is converted into a digital signal by an A / D converter and output to the baseband processing circuit unit 20.

  The baseband processing circuit unit 20 captures a GPS satellite signal by performing carrier removal, correlation calculation, and the like on the reception signal output from the RF reception circuit unit 11. Then, using the time information extracted from the captured GPS satellite signal, satellite orbit information, and the like, the position and clock error of the mobile phone 1 are calculated.

  The host processing unit 30 is a processor that comprehensively controls each unit of the mobile phone 1 according to various programs such as a system program stored in the storage unit 80, and includes a processor such as a CPU (Central Processing Unit). Composed. The host processing unit 30 displays a map indicating the current position on the display unit 50 based on the position coordinates acquired from the baseband processing circuit unit 20, and uses the position coordinates for various application processes.

  The operation unit 40 is an input device configured by, for example, a touch panel or a button switch, and outputs a pressed key or button signal to the host processing unit 30. By operating the operation unit 40, various instructions such as a call request, a mail transmission / reception request, and a position calculation request are input.

  The display unit 50 is configured by an LCD (Liquid Crystal Display) or the like, and is a display device that performs various displays based on display signals input from the host processing unit 30. The display unit 50 displays a position display screen, time information, and the like.

  The cellular phone antenna 60 is an antenna that transmits and receives cellular phone radio signals to and from a radio base station installed by a communication service provider of the cellular phone 1.

  The cellular phone wireless communication circuit unit 70 is a cellular phone communication circuit unit configured by an RF conversion circuit, a baseband processing circuit, and the like, and performs modulation and demodulation of the cellular phone radio signal, thereby enabling communication and mailing. Realize transmission / reception and so on.

  The storage unit 80 includes a storage device such as a ROM (Read Only Memory), a flash ROM, a RAM (Random Access Memory), and the like, and a system program for the host processing unit 30 to control the mobile phone 1, Various programs and data for executing various application processes are stored.

  The clock unit 90 is an internal clock of the mobile phone 1, and includes a crystal oscillator including a crystal resonator and an oscillation circuit. The time measured by the clock unit 90 is output to the baseband processing circuit unit 20 and the host processing unit 30 as needed. The clock unit 90 is calibrated using the clock error calculated by the baseband processing circuit unit 20.

2-1. First Example 2-1-1. Configuration of Baseband Processing Circuit Unit FIG. 12 is an explanatory diagram of the circuit configuration of the baseband processing circuit unit 20 and the data configuration of the storage unit in the first embodiment. The baseband processing circuit unit 20 includes a processing unit 21 and a storage unit 23 as main functional configurations.

  The processing unit 21 is a control device and an arithmetic device that collectively control each functional unit of the baseband processing circuit unit 20, and includes a processor such as a CPU or a DSP (Digital Signal Processor). The processing unit 21 includes a satellite capturing unit 211, a pseudorange error estimation unit 213, and a position calculation unit 215 as functional units.

  The satellite capturing unit 211 is a functional unit that captures GPS satellites. Specifically, digital signal processing of carrier removal and correlation calculation is performed on the digitized reception signal output from the RF reception circuit unit 11 to capture a GPS satellite. Then, peak determination is performed on the correlation calculation result, and the Doppler frequency of the received carrier signal and the code phase of the received C / A code are acquired as measurement information.

  Further, the satellite capturing unit 211 decodes the navigation data based on the correlation calculation result. When the phase of the received carrier signal (carrier phase) and the phase of the received C / A code (code phase) are detected and the correlation is established, the navigation data is constructed based on the time variation of the correlation value. Each bit value can be decoded. This phase synchronization is realized by, for example, a PLL (Phase Locked Loop) known as a phase locked loop.

  The satellite capturing unit 211 receives a GPS satellite signal from a GPS satellite and obtains an observation pseudorange that is an observation value of a pseudorange from the reception point to the GPS satellite, or a Doppler frequency of the received GPS satellite signal This corresponds to a Doppler measurement unit that measures.

  In accordance with the principle described above, the pseudorange error estimation unit 213 determines, for each GPS satellite captured by the satellite capture unit 211, an error (pseudomorphic) included in the pseudorange from the mobile phone 1 (GPS antenna 5) to the GPS satellite. Estimate the distance error.

  The pseudo-range error estimation unit 213 uses a pseudo-range prediction unit that calculates a predicted pseudo-range predicted by using the Doppler frequency measured by the satellite capturing unit 211, and an observation pseudo-range and a predicted pseudo-distance. This corresponds to a first error estimation unit that estimates the first error included in the observation pseudorange. In addition, using a given reception position, a second error estimation unit that estimates a second error included in the observation pseudorange, or using the first error and the second error, This corresponds to a true error estimation unit that estimates the true error included in the distance.

  The position calculation unit 215 uses various amounts such as measurement information, navigation data, time information, and satellite information related to each GPS satellite captured by the satellite capturing unit 211, and the pseudorange error estimated by the pseudorange error estimation unit 213. Then, the positioning calculation using the least square method is performed to calculate the position (position coordinates) and clock error (clock bias) of the mobile phone 1. Then, the calculated position is output to the host processing unit 30, and the clock unit 90 is calibrated with the calculated clock error. The position calculation unit 215 calculates the position of the reception point using a predetermined pseudo distance error distribution having the pseudo distance error estimated by the pseudo distance error estimation unit 213 as an expected value and the observation pseudo distance. It corresponds to.

  The storage unit 23 stores a system program of the baseband processing circuit unit 20, various programs for realizing various functions such as a satellite acquisition function, a pseudorange error estimation function, and a position calculation function, data, and the like. In addition, it has a work area for temporarily storing data being processed and results of various processes.

  The storage unit 23 stores a first baseband processing program 231 that is read by the processing unit 21 and executed as the first baseband processing (see FIG. 13) as a program. The first baseband processing program 231 includes a pseudorange error estimation program 2311 executed as a pseudorange error estimation process (see FIG. 14) as a subroutine.

  In addition, the storage unit 23 stores, as main data, satellite-specific data 234 related to each captured GPS satellite and positioning result data 239. Each satellite data 234 includes measurement information 235 relating to the GPS satellite, satellite information 236, pseudo-range error estimation quantities 237, and pseudo-range error distribution 238.

  The measurement information 235 is information such as the code phase of the received GPS satellite signal and the Doppler frequency for the GPS satellite. The satellite information 236 is information such as the position, velocity, and movement direction of the GPS satellite.

The pseudo distance error estimation quantities 237 are various quantities used in the estimation of the pseudo distance error. The observed pseudorange “C (T)”, the predicted pseudorange “P (T)”, the first pseudorange estimation error “E (T)”, and the second pseudorange estimation error “Z (T)” described in the principle. These include various quantities such as “, pseudo-range error offset value“ E _offset (T) ”, pseudo-range error offset average value“ aveE _offset (T) ”, and pseudo-range error estimated value“ E _estimate (T) ”.

The pseudorange error distribution 238 is the pseudorange error distribution 238 shown and described in FIG. 1, and includes a pseudorange error expected value 238A and a pseudorange error standard deviation 238B. The pseudo distance error estimated value “E _estimate (T)” estimated by the pseudo distance error estimation process is set in the pseudo distance error expected value 238A. Also, a fixed value (for example, “1”) is set in the pseudo distance error standard deviation 238B.

  The positioning result data 239 is data obtained as a result of the positioning calculation, and includes the position of the mobile phone 1 and a clock error.

2-1-2. Process Flow FIG. 13 shows the first baseband processing executed in the baseband processing circuit unit 20 when the processing unit 21 reads out the first baseband processing program 231 stored in the storage unit 23. It is a flowchart which shows a flow.

  First, the processing unit 21 performs acquisition target satellite selection processing (step A1). Specifically, a GPS satellite positioned in the sky at the current time measured by the clock unit 90 is determined using satellite orbit data such as almanac and ephemeris, and selected as a capture target satellite. Then, the satellite capturing unit 211 performs loop A processing for each capture target satellite (steps A3 to A17).

  In the process of loop A, the satellite capturing unit 211 captures a GPS satellite signal by performing digital signal processing such as carrier removal and correlation calculation on the received signal input from the RF receiving circuit unit 11 for the capturing target satellite. (Step A5). Then, using the result of the correlation calculation, the code phase and the Doppler frequency related to the captured GPS satellite signal are measured, and stored as measurement information 235 in the satellite-specific data 234 (step A7).

  In addition, the satellite capturing unit 211 calculates satellite information 236 such as the position, velocity, and moving direction of the capture target satellite using the navigation data and time information acquired by capturing the GPS satellite signal, and the satellite-specific data. It memorize | stores in 234 (step A9). Then, the processing unit 21 performs pseudorange error estimation processing according to the pseudorange error estimation program 2311 stored in the storage unit 23 (step A11).

FIG. 14 is a flowchart showing the flow of the pseudo-range error estimation process.
The pseudorange error estimation unit 213 obtains a pseudorange using the code phase included in the measurement information 235, and stores the pseudorange in the pseudorange error estimation quantities 237 as the observed pseudorange “C (T)” (step B1).

Further, the pseudorange error estimation unit 213 calculates the line-of-sight velocity “V _R ” according to the equation (2) using the Doppler frequency included in the measurement information 235 (step B3). Then, using the calculated line-of-sight velocity “V _R ”, a pseudo distance is predicted according to the equation (4), and stored in the pseudo distance error estimation quantities 237 as a predicted pseudo distance “P (T)” (step B5). .

  Next, the pseudorange error estimation unit 213 uses the observed pseudorange “C (T)” and the predicted pseudorange “P (T)”, and includes the first pseudorange included in the observed pseudorange according to Equation (5). The error is estimated and stored in the pseudo distance error estimation quantities 237 as the first pseudo distance estimation error “E (T)” (step B7).

  Thereafter, the pseudo distance error estimation unit 213 estimates the second error included in the observation pseudo distance according to the equation (7) using the position and the clock error included in the positioning result data 239, and the second pseudo distance error estimation unit 213 estimates the second error included in the observation pseudo distance. The distance estimation error “Z (T)” is stored in the pseudo distance error estimation quantities 237 (step B9).

Next, the pseudo-range error estimation unit 213 uses the first pseudo-range estimation error “E (T)” and the second pseudo-range estimation error “Z (T)” according to Equation (8). Is calculated and stored in the pseudo-range error estimation quantities 237 as a pseudo-range error offset value “E _offset (T)” (step B11).

Then, the pseudo distance error estimation unit 213 averages the pseudo distance error offset value “E _offset (T)” for a predetermined offset average period stored in the pseudo distance error estimation quantities 237, and the result is the pseudo distance. The error distance average value “aveE _offset (T)” is stored in the pseudo-range error estimation quantities 237 (step B13).

Finally, the pseudorange error estimation unit 213 uses the pseudorange error offset average value “aveE _offset (T)” to correct the first pseudorange estimation error “E (T)” according to Equation (9). The result is stored in the pseudo-range error estimation quantities 237 as a pseudo-range error estimate “E _estimate (T)” (step B15). Then, the pseudo distance error estimation unit 213 ends the pseudo distance error estimation process.

Returning to the first baseband process of FIG. 13, the processing unit 21 sets the pseudorange error estimated value “E _estimate (T)” obtained by the pseudorange error estimation process as the pseudorange error expected value 238A (step A13). ). Then, the processing unit 21 sets the pseudorange error distribution 238 of the capture target satellite based on the set pseudorange error expected value 238A and the predetermined pseudorange error standard deviation 238B (step A15), and then Transfer processing to the target satellite. If the processing of steps A5 to A15 has been performed for all the capture target satellites, the processing unit 21 ends the processing of loop A (step A17).

  Thereafter, the position calculation unit 215 performs position calculation processing (step A19). Specifically, positioning calculation using the least square method is performed using the pseudorange error distribution 238 set in step A15 for each capture target satellite and the observed pseudorange obtained in step B1 for each capture target satellite. Thus, the position (positional coordinates) and clock error (clock bias) of the mobile phone 1 are approximately obtained. Then, the positioning result is stored in the positioning result data 239.

  Next, the processing unit 21 outputs the position calculated in the position calculation process to the host processing unit 30 (step A21). And the process part 21 determines whether a process is complete | finished (step A23), and when it determines with not complete | finishing yet (step A23; No), it returns to step A1. If it is determined that the process is to be terminated (step A23; Yes), the first baseband process is terminated.

2-1-3. Experimental Results FIG. 15 is a graph showing an example of experimental results obtained by performing positioning calculation using the above-described position calculation method. The horizontal direction of the graph indicates the position calculation accuracy in the east-west direction, and the vertical direction indicates the position calculation accuracy in the north-south direction. The center of the graph corresponds to a position error “0 [meter]”, and the closer to the center of the graph, the higher the position calculation accuracy. The position error when the positioning calculation is performed by the conventional method is shown by a white diamond plot, and the position error when the positioning calculation is performed by the method of this embodiment is shown by the black diamond plot.

  From the graph of FIG. 15, it can be seen that, with the conventional method, the plot showing the position error varies widely as a whole, and the position calculation accuracy is low. On the other hand, in the method of the present embodiment, the plot indicating the position error is concentrated on the central portion as a whole, and it can be seen that the position calculation accuracy is improved as compared with the conventional method. Thereby, the effectiveness of the position calculation method of this embodiment was proved.

2-1-4. Action In the baseband processing circuit unit 20, the satellite capturing unit 211 obtains an observation pseudo distance from the GPS antenna 5 to the GPS satellite using a GPS satellite signal received from the GPS satellite. In addition, the satellite capturing unit 211 measures the Doppler frequency of the received GPS satellite signal. The pseudorange error estimation unit 213 calculates a predicted pseudorange using the Doppler frequency measured by the satellite capturing unit 211, and uses the observed pseudorange and the predicted pseudorange to include the first pseudorange distance included in the observed pseudorange. Is estimated.

  On the other hand, the pseudo distance error estimation unit 213 uses the position and clock error of the mobile phone 1 obtained by the position calculation unit 215 to perform the positioning calculation, and uses the second pseudo distance included in the observation pseudo distance. Estimate the estimation error. Then, the true error included in the observed pseudorange is estimated using the estimated first and second pseudorange estimation errors. By using the positioning result, the error included in the observation pseudorange can be estimated with high accuracy. Then, by correcting the first pseudo distance estimation error using the second pseudo distance estimation error, it is possible to correctly estimate the true error included in the observation pseudo distance.

  Further, by estimating the pseudorange error for each GPS satellite and setting the expected value of the pseudorange error, the pseudorange error distribution can be defined for each GPS satellite. Then, using the pseudorange error distribution defined for each GPS satellite and the observed pseudorange observed for each satellite, for example, positioning calculation using the least square method is performed. Thereby, even in an environment such as a multipath environment or an indoor environment where the pseudo-range error distribution does not always follow a normal distribution with an expected value of zero, position calculation can be performed accurately.

2-2. Second Example 2-2-1. Data Configuration of Storage Unit FIG. 16 is a diagram illustrating an example of a data configuration of the storage unit 23 of the baseband processing circuit unit 20 according to the second embodiment. Note that the same reference numerals are assigned to the same data as the storage unit 23 of the baseband processing circuit unit 20 of FIG. 12 according to the first embodiment, and the description thereof is omitted.

  The storage unit 23 stores a second baseband processing program 231B that is read by the processing unit 21 and executed as the second baseband processing (see FIG. 18) as a program. The second baseband processing program 231B includes a pseudorange error estimation program 2311 as a subroutine.

  Further, the storage unit 23 stores, as main data, pseudorange error standard deviation model data 232, model selection condition table 233, satellite-specific data 234, and positioning result data 239.

  The pseudo distance error standard deviation model data 232 is defined by a model related to a pseudo distance error standard deviation set as the pseudo distance error standard deviation 238B of the pseudo distance error distribution 238 (hereinafter referred to as “pseudo distance error standard deviation model”). Data.

  In the present embodiment, the pseudorange error standard deviation model is defined as a model in which the signal quality of the GPS satellite signal is associated with the pseudorange error standard deviation. The signal quality is the quality of a signal received from a GPS satellite signal. For example, the correlation power that can be calculated from a signal-to-noise ratio SNR (Signal to Noise Ratio), a cross polarization ratio XPR (Cross Polarization Power Ratio), and an IQ correlation value. It is represented by a signal quality index value such as a value.

The SN ratio is calculated, for example, according to the following formula (10).
SNR = P _S / P _N (10)
However, “P _S ” is a peak correlation value among the correlation values obtained as a result of the correlation calculation. “P _N ” is a correlation value at a phase separated from the peak phase by a predetermined phase (for example, one chip). Higher signal-to-noise ratio means higher signal quality.

XPR is calculated according to the following equation (11), for example.
XPR = (P _S −P _N ) / P _S (11)
However, XPR means that the closer to “1”, the higher the signal quality.

  FIG. 17 is a diagram illustrating an example of the pseudorange error standard deviation model. FIG. 17A is an example of an indoor model A corresponding to an environment where the satellite view is poor indoors. FIG. 17B is an example of an indoor model B corresponding to an environment where the satellite view is good indoors. FIG. 17C is an example of an outdoor model corresponding to an outdoor environment.

  In each figure, the horizontal axis is a signal quality index value (here, SNR), and the vertical axis is a pseudorange error standard deviation “σ” (unit is meter). The numerical range of the signal quality index value is generally determined according to the positioning environment. The better the positioning environment, the larger the signal quality index value, and thus the larger the numerical range of the signal quality index value. Therefore, in FIG. 17, the scale of the signal quality index value on the horizontal axis is changed for each model.

  Referring to FIG. 17, it can be seen that any of the pseudorange error standard deviation models shows a changing tendency in which the pseudorange error standard deviation decreases as the signal quality index value increases. However, the degree of attenuation varies depending on the positioning environment. In the outdoor model, when the signal quality index value increases, the pseudorange error standard deviation decreases to almost zero, so it can be said that the degree of attenuation is large. Although the indoor model B is not as large as the outdoor model, the pseudo-range error standard deviation attenuates to near zero. However, in the indoor model A, it can be seen that even if the signal quality index value increases, the pseudorange error standard deviation does not attenuate so much.

  As described above, since the degree of attenuation of the pseudorange error standard deviation may be different for each positioning environment, it is appropriate to define a pseudorange error standard deviation model for each positioning environment. Specifically, sample data of pseudorange errors is collected for each positioning environment. Then, the collected pseudo distance error sample data is classified into a plurality of normal distributions according to signal quality, and a standard deviation of each normal distribution is obtained to obtain a model of signal quality index value versus pseudo distance error standard deviation.

  The model selection condition table 233 is a table in which conditions for selecting which pseudo-range error standard deviation model is to be selected in which positioning environment.

2-2-2. Process Flow FIG. 18 shows the second baseband processing executed in the baseband processing circuit unit 20 by reading out the second baseband processing program 231B stored in the storage unit 23 by the processing unit 21. It is a flowchart which shows a flow. Note that the same steps as those in the first baseband processing in FIG. 13 are denoted by the same reference numerals and description thereof will be omitted, and steps different from those in the first baseband processing will be mainly described.

  After step A1, the processing unit 21 determines the current positioning environment based on, for example, the previous GPS satellite acquisition result (step C2). The determination of the positioning environment is preferably realized by comprehensively considering a plurality of factors such as (A) signal intensity, (B) satellite sky arrangement, and (C) the number of visible satellites.

  (A) The signal strength is the strength of the received GPS satellite signal. (B) The satellite sky arrangement is an index value indicating the degree of variation of GPS satellites in the sky, and is represented by, for example, a PDOP (Position Dilution Of Precision) value. The greater the variation of GPS satellites, the smaller the PDOP value. (C) The number of visible satellites is the number of GPS satellites that are located in the sky at the reception point and can be observed at the reception point. It can be judged that the positioning environment is better as the signal intensity is stronger, the satellite sky arrangement is better, and the number of visible satellites is larger.

  The processing unit 21 sets the expected pseudorange error value 238A (step A13) in the processing of the loop A performed for each acquisition target satellite, and then stores it in the storage unit 23 with reference to the model selection condition table 233 in the storage unit 23. A pseudo distance error standard deviation model corresponding to the positioning environment determined in step C2 is selected from the pseudo distance error standard deviation model data 232 (step C10).

  Next, the processing unit 21 calculates a signal quality index value of a GPS satellite signal received from the capture target satellite (step C12). Then, the processing unit 21 sets the pseudo distance error standard deviation 238B using the pseudo distance error standard deviation model selected in Step C10 and the signal quality index value calculated in Step C12 (Step C14).

  Thereafter, the processing unit 21 sets the pseudorange error distribution 238 of the capture target satellite based on the pseudorange error expected value 238A set in Step A13 and the pseudorange error standard deviation 238B set in Step C14 (Step S13). C16). And the process part 21 transfers a process to the following acquisition object satellite.

2-2-3. In the second embodiment, the pseudorange error standard deviation is set based on the pseudorange error standard deviation model defined for each positioning environment and the signal quality of the received GPS satellite signal. Thereby, it is possible to set an appropriate pseudorange error distribution suitable for the positioning environment. Moreover, by setting the pseudo range error expected value and the pseudo range error standard deviation individually for each satellite, the pseudo range error distribution can be optimized for each satellite, and the accuracy of position calculation can be further improved.

3. Modifications Embodiments to which the present invention can be applied are not limited to the above-described embodiments, and can be changed as appropriate without departing from the spirit of the present invention. Hereinafter, modified examples will be described.

3-1. Calculation of predicted pseudorange In addition to the Doppler frequency, the reception frequency includes a frequency shift due to a clock drift of the GPS receiver. Therefore, it is preferable to calculate the predicted pseudorange “P (T)” in consideration of not only the Doppler frequency but also clock drift. In this case, in the equations (1) and (2), the line-of-sight velocity “V _R ” is calculated in consideration of the clock drift “f _drift ” together with the Doppler frequency “f _d ”, The distance “P (T)” may be calculated.

In the above embodiment, the line-of-sight velocity “V _R ” is calculated using the measured Doppler frequency “f _d ”, but it is also possible to calculate the line-of-sight velocity “V _R ” using the positioning result. . That is, the position vector of the GPS receiver acquired as a positioning result in the past is time-differentiated to calculate the velocity vector of the GPS receiver. Then, a relative velocity vector between the GPS receiver and the GPS satellite is calculated using the calculated velocity vector of the GPS receiver and the velocity vector of the GPS satellite. Then, by projecting the relative velocity vector in the line-of-sight direction, the line-of-sight velocity (gaze velocity vector) “V _R ” can be calculated. The predicted pseudorange “P (T)” can be calculated from the equation (4) also by using the line-of-sight velocity “V _R ” calculated in this way.

3-2. Given reception position In the above embodiment, the position of the GPS receiver determined by the positioning calculation is used as the given reception position, and the second error (second pseudo distance estimation error) included in the observed pseudorange. ) Was estimated. However, it goes without saying that the position used as a given reception position is not limited to this.

  For example, the second pseudo-range estimation error may be estimated using a position (base station position or reception point position) acquired using server assist as a given reception position. In addition, the second pseudo-range estimation error may be estimated with a position corresponding to a point or place operated and input by a user (user) of the electronic device as a given reception position. The second pseudo-range estimation error can be estimated using an arbitrary reception position as long as the reception position guarantees a certain degree of accuracy.

  In the above embodiment, the second pseudo-range estimation error is estimated by taking into account the clock bias in addition to the reception position. However, if the clock bias value cannot be known, the reception is performed in Expression (7). The second pseudo distance estimation error may be estimated using only the position.

3-3. Correction of First Pseudo Distance Estimation Error In the above embodiment, the first pseudo distance estimation error is corrected using a pseudo distance error offset average value obtained by simply arithmetically averaging the pseudo distance error offset values for a predetermined period. The correction method is not limited to this. For example, a weighted average may be performed by weighting the pseudo distance error offset value for a predetermined period, and the weighted average result may be used for correction. In this case, the reliability of the pseudorange error offset value is determined based on the signal strength of the GPS satellite signal, the reception environment, etc., and the weight of the pseudorange error offset value determined to be high is set to a high weighted average. It is effective. Moreover, you may correct | amend using the median value of the pseudo | simulation distance error offset values for a predetermined period instead of using an average value.

3-4. Electronic Device In the above embodiment, the case where the present invention is applied to a mobile phone which is a kind of electronic device has been described as an example. However, an electronic device to which the present invention can be applied is not limited thereto. For example, the present invention can be similarly applied to other electronic devices such as a car navigation device, a portable navigation device, a personal computer, a PDA (Personal Digital Assistant), and a wristwatch.

3-5. In the above embodiment, the pseudo-range error estimation process is described as being executed by the processing unit of the baseband processing circuit unit. However, the pseudo-range error estimation process may be executed by the host processing unit of the electronic device. Good. In this case, the GPS receiver does not correspond to the pseudorange error estimation device, but the electronic device corresponds to the pseudorange error estimation device.

  Also, the processing may be distributed such that the satellite acquisition processing and pseudorange error estimation processing are executed by the processing unit of the baseband processing circuit unit, and the position calculation processing is executed by the host processing unit of the electronic device.

3-6. In the above embodiment, the GPS has been described as an example of the satellite positioning system. However, WAAS (Wide Area Augmentation System), QZSS (Quasi Zenith Satellite System), GLONASS (GLObal NAvigation Satellite System), GALILEO Other satellite positioning systems may be used.

DESCRIPTION OF SYMBOLS 1 Mobile phone, 10 GPS receiving part, 11 RF receiving circuit part, 20 Baseband processing circuit part, 21 Processing part, 23 Storage part, 30 Host processing part, 40 Operation part, 50 Display part, 60 Mobile phone antenna, 70 wireless communication circuit unit for mobile phone, 80 storage unit, 90 clock unit

Claims (8)

Receiving a satellite signal from a satellite and obtaining an observation pseudorange that is an observation value of the pseudorange from the reception point to the satellite;
Measuring the Doppler frequency of the received satellite signal;
Using the Doppler frequency to calculate a predicted pseudorange that predicted the pseudorange;
Estimating a first error included in the observed pseudorange using the observed pseudorange and the predicted pseudorange;
Estimating a second error included in the observed pseudorange using a given reception position;
Estimating a true error included in the observed pseudorange using the first error and the second error;
A pseudo-range error estimation method including: Estimating the true error is
Calculating a difference between the first error and the second error;
Using the difference calculation result for a predetermined period to correct the first error;
including,
The pseudorange error estimation method according to claim 1. The correction is to correct the first error using a result obtained by averaging the calculation results of the difference for the predetermined period.
The pseudorange error estimation method according to claim 2. Calculating the predicted pseudorange is
Calculating a line-of-sight speed using the Doppler frequency;
Obtaining the predicted pseudorange by integrating the line-of-sight velocity;
including,
The pseudorange error estimation method according to any one of claims 1 to 3. Estimating the pseudorange error using the pseudorange error estimation method according to any one of claims 1 to 4,
Calculating a position of the reception point using a predetermined pseudorange error distribution with the estimated pseudorange error as an expected value and the observed pseudorange;
Position calculation method including The pseudorange error distribution is a distribution defined by an expected value of the pseudorange error and a standard deviation of the pseudorange error,
Further comprising setting a standard deviation of the pseudorange error distribution using a model in which the signal quality of the satellite signal is associated with the standard deviation.
The position calculation method according to claim 5. The model is determined according to the positioning environment,
Further comprising determining a positioning environment;
The setting includes setting the standard deviation using a model corresponding to the determined positioning environment;
The position calculation method according to claim 6. A pseudorange observation unit that receives a satellite signal from a satellite and obtains an observation pseudorange that is an observation value of a pseudorange from the reception point to the satellite;
A Doppler measurement unit for measuring the Doppler frequency of the received satellite signal;
Using the Doppler frequency, a pseudo-distance predictor that calculates a predicted pseudo-distance predicting the pseudo-distance;
A first error estimating unit that estimates a first error included in the observed pseudorange using the observed pseudorange and the predicted pseudorange;
A second error estimator that estimates a second error included in the observed pseudorange using a given reception position;
A true error estimation unit that estimates a true error included in the observation pseudo-range using the first error and the second error;
A pseudo-range error estimation device comprising: