Patent Application
20120314733
The present invention relates to a method of estimately calculating a pseudorange through receiving positioning signals from GNSS satellites, and particularly relates to a method of estimately calculating a pseudorange by carrier smoothing a pseudorange obtained based on measurement values.
Conventionally, many positioning apparatuses for receiving positioning signals from GNSS satellites and performing a positioning have been put into practical use and used on various kinds of mobile terminals.
For such positioning apparatuses, an improvement in positioning accuracy has been required, and in order to achieve this, the art so called carrier smoothing using carrier phase information has been used conventionally. Carrier smoothing is for calculating a current estimated pseudorange by using a pseudorange (observed pseudorange) that is directly calculated based on code phase information in received positioning signals, and an added value of a pseudorange (estimated pseudorange) estimated previously and a carrier phase change.
As one of such estimation calculation methods, a “weighted-hatch-filter” disclosed in Nonpatent Document 1 is used, for example. A weight coefficient is determined based on a variance of the observed pseudorange and a variance of the estimated pseudorange.
Nonpatent Document 1: Kee, C., Walter, T., Enge, P., and Parkinson, B., “Quality Control Algorithms on WAAS Wide-Area Reference Stations”, Journal of The Institute of Navigation, Vol. 44, No. 1, Spring, 1997, pp. 53-62
However, when a tall construction and the like exist near the positioning apparatus, such as in an urban area, the positioning apparatus receives direct positioning signals from GNSS satellites as well as indirect positioning signal(s) which were reflected on, for example, the tall construction, and an error occurs in the pseudorange to be calculated. Such phenomena is referred to as multipath, and due to this influence of the multipath error, the observed pseudorange includes a large error.
Here, in the weighted hatched filter, because a steady value that is set based on empirical rules in advance is used as the weight coefficient, even if the conventional carrier smoothing described above is performed, during a period where multipath continuously occurs, the error of the pseudorange to be estimated enlarges and positioning accuracy degrades.
The present invention aims to realize a pseudorange estimating method with which a pseudorange can be estimately calculated in high accuracy without being influenced by multipath.
The present invention relates to a method of estimating a pseudorange based on reception signals of GNSS positioning signals. The pseudorange estimating method includes calculating an observed pseudorange based on a code phase difference of the reception signals, measuring Doppler frequencies of the reception signals, and calculating an estimated pseudorange by using carrier smoothing of adding with weights, the observed pseudorange calculated based on the code phase difference, a previously estimated pseudorange, and a change of a carrier wave phase. The weight in the carrier smoothing is determined based on a change rate of the observed pseudorange and the Doppler frequency.
In this method, when the psudorange is estimately calculated by the carrier smoothing, the weighting based on the pseudorange change and the Doppler frequency is used. Here, although the detail is described later in “MODE OF CARRYING OUT THE INVENTION” by using
Therefore, the influence of multipath is loosened by performing the carrier smoothing using the value reflecting the influence of multipath according to an appearance of multipath without using the fixed value as the conventional case, and a highly accurate estimation calculation of the pseudorange becomes available.
Further, the weight in the carrier smoothing may be determined based on a difference value between the change rate of the observed pseudorange and the Doppler frequency, or a statistic of the difference values.
Further, the weight in the carrier smoothing may be determined based on the change rate of the observed pseudorange, the Doppler frequency, and the estimated pseudorange.
Further, the weight in the carrier smoothing may be determined based on a statistic of difference values between the change rate of the observed pseudorange and the Doppler frequency, and a statistic of the estimated pseudoranges.
In these methods, specific examples of weighting in the carrier smoothing is shown.
Further, the calculating the estimated pseudorange may include adding with the weights, a value based on the Doppler frequency alternative to the change of the carrier wave phase.
In this method, an example of a correction term in the carrier smoothing is shown. By using the value based on the Doppler frequency to be used in setting the weight, the change of the carrier wave phase is not required to be measured separately, and processing is simplified.
Further, this pseudorange estimating method of the invention may include detecting multipath contained in the reception signal. The calculating the estimated pseudorange may include determining, when multipath is detected in the detecting multipath, the weight in the carrier smoothing based on the change rate of the observed pseudorange and the Doppler frequency, and determining, when multipath is not detected, the weight in the carrier smoothing to be a predetermined value.
In this method, a method of setting the weight according to multipath is shown, and the coefficients described above is used only when multipath exists. This can easily set in advance to a value for estimating the pseudorange in high accuracy, the coefficient when in a state where, when multipath does not exist, the pseudorange can stably be obtained, and the carrier smoothing is performed. Therefore, when multipath does not exist, by using this fixed set value, the estimation calculation speed can be improved, and a processing load can be reduced. On the other hand, when multipath exists, by performing the coefficient setting described above, the pseudorange can be estimated in high accuracy even if multipath exists. In this manner, the processing load can be reduced according to the situation while estimating the pseudorange in high accuracy constantly.
According to this invention, a pseudorange can estimately be calculated in high accuracy even under an environment where multipath is caused. Thus, a highly accurate positioning result can be obtained.
A pseudorange estimating method, and a pseudorange estimating program and a pseudorange estimating function system of realizing the method according to an embodiment of the invention are described with reference to the drawings. Note that, in this embodiment, although a GPS of a GNSS is described as an example, the method and configuration of this embodiment can also be applied to other similar positioning systems.
Further, in the following description, an example in which a weighted hatch filter is used as a linear equation of a state space model for estimating a pseudorange is shown. However, the method of the invention can be applied also to other filter operations in which a weight coefficient can be used, such as the Kalman filter.
First, a concept of detecting multipath required in a pseudorange estimation calculation of the invention is described with reference to
Here, a pseudorange error Error(PR(iv)) in
A C/No (iv) in
A pseudorange change Rr(iv) in
A delta range DR(iv) in
Moreover, as shown in the hatched part of
Here, as shown in
On the other hand, as shown in
Here, because the pseudorange change Rr(iv) is indicated by a change of distance in time, that is a unit of speed, and the delta range DR(iv) is a value that is an integrated value of Doppler frequencies indicated by the unit of speed, they can simply be used in four operations. By using this, a difference value DV(iv) is calculated through reducing the pseudorange change Rr(iv) by the delta range DR(iv). Because this difference value DV(iv) is a difference value between the pseudorange change Rr(iv) and the delta range DR(iv), it is substantially the same in the time range where the pseudorange change Rr(iv) is stable and multipath does not occur, and it varies significantly in the time range where the pseudorange change Rr(iv) is unstable and multipath occurs.
Further, as shown in
Based on these characteristics, the difference value DV(iv), an average value DV(Av) and a standard deviation σDV calculated by using a plurality of the difference values DV(iv) are respectively set with thresholds that are obtained experimentally, and it is determined that multipath exists when multipath detecting conditions based on the thresholds are satisfied, and it is determined that multipath does not exist when the multipath detecting conditions are not satisfied.
Thus, when the existence of multipath is determined, carrier smoothing processing by the weighted hatch filter described subsequently is executed according to the existence of the multipath, and the pseudorange is estimately calculated.
First, the weighted hatch filter used in this embodiment is described. Equation 1 shown subsequently is a linear equation expressing the weighted hatch filter, wherein “k” indicates the epoch, PR(iv)k indicates an observed pseudorange calculated based on observation values for k-th epoch, and PRe(iv)k indicates an estimated pseudorange estimated for k-th epoch. DR(iv)k is the delta range calculated for k-th epoch. σ2PRek-1 indicates an error variance of the observed pseudorange for k-th epoch, and a σ2PRek-1 indicates an error variance of the observed pseudorange for k-1th epoch.
In Equation 1, the observed pseudorange PR(iv)k and the delta range DR(iv)k which are state variables are observation values, and the error variance σ2PRek of the estimated pseudorange used in the coefficients is calculated based on the error variance σ2PRk of the observed pseudorange PR(iv)k. Therefore, if the error variance σ2PRk of the observed pseudorange PR(iv)k used in the coefficients along with the error variance σ2PRek-1 of the estimated pseudorange can be set, the estimated pseudorange PRe(iv)k can be calculated. Note that, in Equation 1, although the delta range DR(iv)k is used in the correction term of carrier smoothing, a change of a carrier wave phase may also be used.
These coefficients are determined according to the existence of multipath.
First, when multipath does not exist, the pseudorange stabilizes as described above, and the pseudorange error becomes extremely small. Further, such a state can be created experimentally in advance. Therefore, based on such experimental result and simulation result, the error variance σ2PRk described above is set to be a fixed value with which the estimated pseudorange can stably be obtained.
On the other hand, when multipath exists, the error variance σ2PRk is set by using the standard deviation σDVk of the difference value DV(iv)k calculated in the determination of the existence of multipath described above.
Here, the difference value DV(iv)k is expressed in the following Equation 3.
DV(iv)k=(PR(iv)k−Pre(iv)k-1)−Dr(iv)k (3)
Further, through modifying Equation 3, Equation 4 is obtained.
PR(iv)k=DV(iv)k+PRe(iv)k-1+DR(iv)k (4)
Here, the equations do not correlate in the predetermined period (e.g., for 1 second). Therefore, the relation of each error variance can be expressed in Equation 5.
σ2PRk=σ2DVk+σ2PRek-1+σ2DRk (5)
Meanwhile, if multipath exists, the error variance σ2DVk of the difference value DV(iv)k becomes greater than the error variance in the case where multipath does not exist.
Note that, this σCN based on the probability density function using the C/No is calculated based on an approximate equation shown in the following Equation 5.
As shown in
Therefore, when multipath exists, it is assumed that 3σDVk of the calculated difference value DV(iv)k follows the normal distribution, and the error variance σ2PRk of the observed pseudorange PR(iv)k is set based on Equation 5 by using 3σDVk of the difference value DV(iv)k.
Here, the error variance σ2DRk of the delta range DR(iv)k is required. However, the delta range DR(iv) hardly receives the influence of multipath and is steady as described above, and therefore, it may be calculated in a well-known method based on a plurality of delta ranges DR(iv) that can be acquired in a predetermined time length (e.g., in 1 second).
Further, by using the error variance σ2PRk of the observed pseudorange PR(iv)k and the error variance σ2DRk of the delta range DR(iv)k, the error variance σ2PRek of the estimated pseudorange PRe(iv)k can be calculated based on Equation 2.
Further, in Equation 5, when substituting the error variance σ2PRek-1 of the previous estimated pseudorange, the correction by the error variance of the delta range is performed based on the following equation, and then the substitution into Equation 5 is performed.
σ2PRek-1=σ2PRek-1+σ2PRek (7)
By performing this processing, the influence from the error of the error variance of the delta range can be suppressed.
The pseudorange estimation calculation result when the coefficient setting is performed as above is shown in
As shown in
On the other hand, with the weighted hatch filter of this embodiment where the weights are changeable based on multipath, the pseudorange error is hardly generated in the period where multipath does not exist and the period where multipath exists.
This is because the weight coefficient is determined based on the error variance corresponding to the appearance of multipath, and by this processing, the influence of multipath is suppressed and the pseudorange can be estimately calculated in high accuracy.
Next, the pseudorange estimation calculation method of this embodiment is described with reference to
First, in the multipath detecting method of this embodiment, the C/No (iv), the pseudorange PR(iv), and the delta range DR(iv) are acquired at every count timing (e.g., every second) to be stored (S101). Here, the C/No (iv) is calculated based on the correlation result acquired from the two-dimensional correlation spectrum obtained during the period between the counting timings as described above (e.g., for 1 second), that is a correlation data distribution in the code phase axis and a correlation data distribution in the frequency axis. The pseudorange PR(iv) is calculated based on the code phases obtained during the period between the count timings as described above (e.g., for 1 second) by using a well-known method. The delta range DR(iv) is calculated by integrating the Doppler frequencies that are respectively obtained from carrier phase differences obtained during the period between the count timings as described above (e.g., for 1 second).
Next, the pseudorange change Rr(iv) is obtained by finding the difference between the pseudorange PR(iv) and an immediate previous pseudorange PR(iv) thereof. Further, a difference operation between the calculated pseudorange change Rr(iv) and the delta range DR(iv) is performed to calculate and store the difference value DV(iv) (S102). Note that, here, the delta range DR(iv) is also stored.
Next, it is determined whether the numbers of data corresponding to the sampling numbers for calculating an average value C/No(Av) and a standard deviation σC/No of the C/No and an average value DV(Av) and a standard deviation σDV of the difference values exist, respectively. Here, if the predetermined numbers of data cannot be acquired, it is defined to be indeterminable. On the other hand, if the predetermined numbers of data can be acquired, the average value C/No(Av) and the standard deviation σC/No of the C/No and the average value DV(Av) and the standard deviation σDV of the difference values are calculated.
Further, after the average value C/No(Av) and the standard deviation σC/No of the C/No and the average value DV(Av) and the standard deviation σDV of the difference values are calculated, it is determined whether multipath exists based on the C/No (iv), the difference value DV(iv), the average value C/No(Av) and the standard deviation σC/No of the C/No, and the average value DV(Av) and the standard deviation σDV of the difference values (S103).
Here, the existence of multipath is determined as follows. For example, when the C/No (iv) is above a threshold for an individual measurement value of a preset C/No and the difference value DV(iv) is below a threshold for an individual measurement value of a preset difference value, it is determined that multipath does not exist. Next, if this condition is not satisfied, the average value C/No(Av) and the standard deviation σC/No of the C/No reach predetermined values for the C/No and the average value DV(Av) and the standard deviation σDV of the difference values reach predetermined values for the difference value, it is determined that multipath does not exist. Note that, when the condition for the individual measurement and the condition for the average value are all satisfied, it may be determined that multipath does not exist.
Next, if multipath is determined as it does not exist (S104: NO), through setting the error variance σ2PR of the observed pseudorange PR(iv) and the error variance σ2DR of the delta range DR(iv) to preset fixed values, the weight coefficient is determined (S105).
On the other hand, if multipath is determined as it exists (S104: YES), the error variance σ2DVk is calculated based on the current standard deviation σDVk of the difference values calculated at the time of the multipath determination described above, and, among a group of stored delta ranges DR(iv) for the recent predetermined time length (e.g., for 1 second), the current error variance σ2DRk of the delta range is calculated (S106).
Next, by using these standard deviation σDVk of the difference values, the error variance σ2DRk of the delta range, and an error variance σ2PRek-1 of the previous estimated pseudorange, the error variance σ2PRk of the current observed pseudorange is calculated based on Equation 2 (S107).
Next, the weight coefficient is determined from the calculated error variance σ2PRk of the current observed pseudorange and the error variance σ2PRek-1 of the previous estimated pseudorange (S108).
Next, after the weight coefficient is determined at Step S105 or S108, the current observed pseudorange PR(iv)k, the previous estimated pseudorange PRe(iv)k-1, and the current delta range DR(iv)k are substituted into the weighted hatch filter indicated in Equation 1 to calculate the current estimated pseudorange PRe(iv)k (S109). This calculation result is outputted to, for example, a positioning operator as well as being stored therein, and it is used in the estimation calculation of the pseudorange thereafter.
Thus, by using the pseudorange estimation calculation method of this embodiment, the pseudorange can be estimately calculated without being influenced by the existence of multipath.
Next, a configuration of the system for achieving such pseudorange estimation calculation processing is described with reference to the drawings.
As shown in
These carrier correlation unit 13 and the code correlation unit 14 are connected with a baseband convertor 12. The baseband converter 12 is inputted with an IF signal obtained through down-converting a GPS signal received by an antenna 10 to an intermediate frequency by an RF processor 11. The baseband converter 12 uses a carrier frequency signal from a carrier NCO 33 of the carrier correlation unit 13 to convert the IF signal into a code signal of the baseband and outputs it to the code correlation unit 14.
The carrier correlation unit 13 includes a carrier correlator 31, a loop filter 32, and the carrier NCO 33. The carrier correlator 31 multiplies the carrier frequency signal from the carrier NCO 33 by the IF signal of the RF processor 11 and outputs a carrier phase difference therebetween. The outputted carrier phase difference is fed back to the carrier NCO 33 via the loop filter 32. Further, the carrier phase difference is also outputted to the delta range measurer 15.
The code correlation unit 14 includes a P correlator 41P, an E correlator 41E, an L correlator 41L, an adder 42, a loop filter 43, a code NCO 44, and a shift register 45.
The code correlation unit 14 is a correlation unit for performing code tracking by performing a so called Early-Late correlation.
The P correlator 41P multiplies a Punctual replica code by the code signal from the baseband convertor 12 and outputs Punctual phase difference data. The E correlator 41E multiplies an Early replica code of which a code phase is ½ chip ahead of the Punctual replica code by the code signal from the baseband convertor 12 and outputs Early phase difference data. The L correlator 41L multiplies a Late replica code of which a code phase is ½ chip behind the punctual replica code by the code signal from the baseband convertor 12 and outputs Late phase difference data. Note that, in this embodiment, although each phase difference among the Early, Punctual and Late is ½ chip, it may suitably be set according to the situation.
The adder 42 finds a difference between the Early phase difference data and the Late phase difference data, and creates E-L correlation data. The E-L correlation data is fed back to the code NCO 44 via the loop filter 43 as well as outputted to the pseudorange calculator 17.
The code NCO 44 creates a replica code based on the E-L correlation data, and outputs it to the shift register 45. The shift register 45 creates an Early replica code, a Punctual replica code, and a Late replica code of which the code phases vary by ½ chip from each other, based on the replica code from the code NCO 44. The punctual replica code is outputted to the P correlator 41P, the Early replica code is outputted to the E correlator 41E, and the Later replica code is outputted to the L correlator 41L in synchronization thereto, respectively.
The delta range measurer 15 calculates the delta range DR(iv) by calculating the Doppler frequency based on the carrier phase difference and integrating the predetermined time length of the Doppler frequencies (e.g., 1 second).
The C/No measurer 16 stores the Punctual phase difference data from the code correlation unit 14 for the predetermined time length (e.g., for 1 second), performs frequency conversion processing, such as FFT processing, on a plurality of stored Punctual phase difference data aligned on a time axis, and measures the C/No (iv) based on the two-dimensional correlation spectrum configured with a spectrum on the time axis and the spectrum on a frequency axis.
The pseudorange calculator 17 calculates the pseudorange PR(iv) by a well-known method based on the E-L correlation data from the code correlation unit 14.
The pseudorange estimation calculator 18 calculates the difference value DV(iv) as described above, based on the delta range DR(iv) from the delta range measurer 15 and the pseudorange PR(iv) from the pseudorange calculator 17. The pseudorange estimation calculator 18 performs the multipath determination by the individual measurement values based on the difference value DV(iv) and the C/No (iv) from the C/No measurer 16, and performs the multipath determination by continuous values based on the average value DV(Av) and the standard deviation aDV(Av) of the difference values, the average value C/No(Av) of the C/No, and the standard deviation σC/NO(Av) of C/No which are obtained from the difference value DV(iv) and the C/No (iv).
Next, if it is determined that multipath does not exist, the pseudorange estimation calculator 18 estimately calculates the pseudorange PRe(iv)k by using the weighted hatch filter indicated in Equation 1 where the weight coefficients constituted with the fixed value is set.
On the other hand, if it is determined that multipath exists, the pseudorange estimation calculator 18 calculates the error variance σ2PRk of the current observed pseu dorange by using Equation 2 based on the standard deviation σDVk of the difference values according to the appearance of multipath, the error variance σ2DRk of the delta range, and the error variance σ2PRek-1 of the previous estimated pseudorange, as described above. Moreover, the pseudorange estimation calculator 18 estimately calculates the pseudorange PRe(iv)k by using the weighted hatch filter indicated in Equation 1 where the weight coefficients constituted with the error variance σ2PRk of the current observed pseudorange and the error variance σ2PRek-1 of the previous estimated pseudorange are set.
Note that, in the description above, the example in which the pseudorange estimation calculation method described above is achieved with configuration constituted with function blocks is shown. However, he pseudorange estimation calculation method described above may be programmed and stored in a memory so as to execute a pseudorange estimation calculation by a CPU performing a processing operation of the program.
Moreover, such a pseudorange estimating function is used in a mobile terminal 100 as shown in
The mobile terminal 100 as shown in
The antenna 10 is the same as the antenna shown in
A pseudorange estimation system 101 of the positioning apparatus 120 corresponds to the pseudorange estimating function system described above, and a positioning operator 102 of the positioning apparatus 120 performs positioning of a position of the own apparatus, and outputs the positioning result to the application processor 130. Note that, the receiver 110, the pseudorange estimation system 101, and the positioning operator 102 may function as the GNSS receiving apparatus 120 to use the GNSS receiving apparatus 120 as an independent apparatus.
Based on the obtained positioning result, the application processor 130 displays the position of the own apparatus and executes processing for being used in navigation, etc.
According to such a configuration, since a highly accurate pseudorange as described above can be obtained, a highly accurate positioning result is obtained, and a highly accurate position display, navigation and the like can be achieved.
| Number | Date | Country | Kind |
|---|---|---|---|
| 2010-042853 | Feb 2010 | JP | national |
| Filing Document | Filing Date | Country | Kind | 371c Date |
|---|---|---|---|---|
| PCT/JP2011/054023 | 2/23/2011 | WO | 00 | 8/24/2012 |
