JP2009079975A - Positioning system - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To estimate and operate an ionosphere delay easily and highly accurately by using one linear regression equation. <P>SOLUTION: A base station 1 receives a positioning signal from a positioning satellite SAT, and acquires a carrier phase integrated value and a code pseudo distance (S1). The base station 1 acquires a navigation message, analyzes it, and acquires information of the positioning satellite used for estimation and operation of the ionosphere delay (S2, S3). The base station 1 performs linear approximation by performing Taylor expansion around the positioning satellite position acquired by past estimation and operation, relative to the distance between the base station 1 and the positioning satellite (S4). The base station 1 sets the linear regression equation by using a linear approximation result on the positioning satellite position as a matrix operation element, by including the ionosphere delay as an unknown, and by using the carrier phase integrated value and a value calculated from the code pseudo distance and the base station position as observation values. The base station 1 estimates and operates the ionosphere delay by applying a Kalman filter or the like to the linear regression equation (S5). <P>COPYRIGHT: (C)2009,JPO&amp;INPIT

Description

  The present invention relates to a positioning system that estimates and calculates ionospheric delay using a positioning signal.

Conventionally, various positioning systems that perform positioning using positioning signals transmitted from positioning satellites have been disclosed, and there are independent positioning and relative positioning based on positioning methods. In the positioning calculation in such a positioning system, there is a problem of ionospheric delay. For this reason, in general, ionospheric delay information is acquired from navigation messages from satellites, and the effect of ionospheric delay is removed by using ionospheric delay information during positioning calculation.
Tatsunori Sada, “GPS Survey Technology”, Ohmsha, October 20, 2003

  As described above, the ionospheric delay information is necessary for highly accurate positioning, and the more accurate the ionospheric delay information, the more accurate positioning can be performed. And the method of calculating such highly accurate ionospheric delay information has not been easy.

  Accordingly, an object of the present invention is to provide a positioning system that can easily perform highly accurate estimation calculation of ionospheric delay information.

  The present invention relates to a positioning system including a plurality of positioning satellites that transmit positioning signals, and a base station that includes a receiving unit that receives positioning signals and has a known position. The base station of this positioning system includes estimation calculation means for estimating the ionospheric delay bias. The estimation calculation means observes the code pseudorange and the carrier phase integrated value between the base station and the positioning satellite from the satellite information obtained from the positioning signal, and calculates the distance between the positioning satellite and the base station from the past of the positioning satellite. Linear approximation by expanding the first-order Taylor series at the estimated position, including at least the ionospheric delay bias of the base station as an unknown variable, and the observed value obtained by subtracting the base station position from the carrier phase integrated value and code pseudorange And a linear regression equation including the positioning satellite position based on the linear approximation as an operation matrix element is constructed, and the ionospheric delay bias of the base station is estimated and calculated from the linear regression equation.

  In this configuration, the ionospheric delay bias can be estimated easily by calculating the ionospheric delay bias using one linear regression equation.

  The estimation calculation means of the positioning system according to the present invention performs the estimation calculation including the integer value bias for each carrier wave in the explanatory variable of the linear regression equation. Here, for each carrier, for example, indicates at least two types of carriers included in a positioning signal that can be used in GNSS.

  In this configuration, calculation is performed to estimate the integer bias at the base station together with the ionospheric delay bias. As a result, when an unknown station close to a known station (a base station whose position is known) performs relative positioning with respect to the known station, since the integer value bias of the base station becomes a known value, the constraint condition increases, Positioning calculation at an unknown station is easy and highly accurate.

  Moreover, the base station of the positioning system of this invention is provided with a plurality of receiving means. The estimation calculation means sets a plurality of ionospheric delay biases corresponding to the respective reception means as the same, and sets it as the only ionospheric delay bias for the base station.

  In this configuration, the objective variable, which is an observation value used in the linear regression equation, increases, but the explanatory variable related to the ionospheric delay bias does not increase, so that a more accurate estimation calculation can be performed.

  The positioning system of the present invention has a plurality of base stations. The positioning system includes ionosphere information estimation means for estimating and calculating ionosphere information corresponding to the longitude and latitude of the ionosphere based on ionosphere delay biases estimated and calculated by a plurality of base stations.

  In this configuration, ionospheric delay information based on longitude and latitude is formed based on the ionospheric delay bias of a plurality of base stations, so that each unknown station can perform highly accurate positioning using this ionospheric delay information. it can.

  According to the present invention, the ionospheric delay bias can be estimated and calculated with high accuracy using only one regression equation. In addition, a highly accurate positioning system can be easily configured by using the estimated ionospheric delay bias.

A positioning system according to an embodiment of the present invention will be described with reference to the drawings. In the following description, a positioning system using GPS will be described, but the present invention can be applied to all other GNSSs (global navigation satellite systems).
FIG. 1 is a conceptual diagram showing the configuration of the positioning system of this embodiment.
FIG. 2 is a block diagram showing the configuration of the base station 1 of this embodiment.
FIG. 3 is a flowchart showing an estimation flow of the ionospheric delay bias of the base station 1 of the present embodiment.

  The positioning system of this embodiment includes a base station 1 and a plurality of positioning satellites SAT1 to SATn.

  The positioning satellites SAT1 to SATn modulate the carrier wave (carrier signal) on which the navigation message is superimposed with a code set in advance for each satellite and transmit it to the outside.

  The base station 1 is provided with a positioning antenna 10, and the base station 1 includes a GPS receiver 11, a navigation message analysis unit 12, a satellite information processing unit 13, and an estimation calculation unit 14.

  The positioning antenna 10 receives positioning signals transmitted from observable positioning satellites SAT1 to SATn, and the GPS receiver demodulates the positioning signals. When this demodulation is performed, the carrier phase integrated value and the code pseudo distance (code phase) are calculated simultaneously (S1). The navigation message analysis unit 12 analyzes the navigation message from the demodulated positioning signal and acquires information on the positioning satellite (S2). The satellite information processing unit 13 uses the ephemeris information of the positioning satellite to select a positioning satellite to be used for the ionospheric delay bias estimation calculation, and outputs various information regarding the selected positioning satellite to the estimation calculation unit 14 (S3).

  The estimation calculation unit 14 matches each information input from the satellite information processing unit 13 and each information input from the base station information communication unit 13 with respect to the target positioning satellite. And the estimation calculating part 14 sets one linear regression equation mentioned later using each input observation value. Here, the observed values are the CA code, the code pseudo distance for each P (Y) code, the carrier phase integrated value for each of the L1 carrier and the L2 carrier, and the value obtained by subtracting the position of the base station from each of the observed values. It becomes the objective variable of the linear regression equation. On the other hand, the unknown includes at least an ionospheric delay bias to be estimated and further includes an integer bias for each carrier wave. This unknown is an explanatory variable for the linear regression equation. Further, an element related to the positioning satellite position obtained by linear approximation developed by the first-order Taylor series around the past positioning satellite position is used as an operation matrix element of the linear regression equation. The estimation calculation unit 14 estimates and calculates the ionospheric delay bias by applying the least square method, the LAMBDA method, or the Kalman filter to the set linear regression equation (S4, S5).

  The base station 1 transmits the ionospheric delay bias thus estimated and calculated to the unknown station in response to a request from the unknown station. At this time, an integer bias estimated and calculated simultaneously with the ionospheric delay bias may be transmitted to the unknown station. Further, the base station 1 transmits an ionospheric delay bias together with its own station position information to an ionosphere delay information setting device installed separately.

  Next, an ionospheric delay bias estimation calculation algorithm in the base station will be specifically described. In the following description, the carrier phase integrated value is simply referred to as “carrier phase”.

The observation equations of the carrier phases φ ^p _{CA, k} (t) and φ ^p _{PY, k} (t) for the base station k and the GPS satellite p (positioning satellites SAT1 to SATn) are expressed by equations (3) and (4). The observation equations of the code pseudorange (pseudodistance) ρ ^p _{L1, k} (t) and ρ ^p _{L2, k} (t) are expressed by equations (1) and (2). Multipath errors are negligible and ignored.

Here, λ _L1 and λ _L2 indicate the wavelengths of the L1 wave and the L2 wave, and r ^p _k (t, t−τ ^p _k ) is the base station k at time t and the time (t−τ ^p _k ). Indicates the distance from the GPS satellite p, τ ^p _k indicates the propagation time of the radio wave between the satellite p and the base station k, δI ^p _k (t) indicates the ionospheric delay, and δT ^p _k (t) indicates the troposphere Δt _k (t) represents the clock error of the base station k at the true time t, and δt ^p (t−τ ^p _k ) represents the clock of the GPS satellite p at the time (t−τ ^p _k ). N ^p _k indicates an integer bias between the base station k and the GPS satellite p, and δb _{CA, k} (t), δb _{PY, k} (t), δb _{L1, k} (t), δb _{L2, k} (t) represents the receiver hardware bias of the base station k, and δb ^p _CA (t), δb ^p _PY (t), δb ^p _L1 (t), and δb ^p _L2 (t) represent the base station k. Ε ^p _k (t), e ^p _k (t) represents observation noise.

Here, the distance between the base station k and the GPS satellite _{^{p r p k (t, t}} -τ p k) a positioning satellite estimated position is unknown ^{se p (t) ≡ [xe} p (t), ye p ( t), ze ^p (t)] ^T (where T is a vector or matrix transpose) is subjected to first-order Taylor series expansion, and r ^p _k (t) is linearly approximated to obtain Equation (5).

Here, s ^p is a positioning satellite position.

  Based on this result, the relationships of equations (6) to (9) are set.

Expressions (1) to (4) become Expression (10) including a vector / matrix expression.

  However,

It is.

  Then, when this equation (10) is linearly transformed, equation (11) is obtained. In Equation (11), the error term is omitted.

  Furthermore, when further linear transformation is performed on the expression (11), the expression (11) can be expressed as the expression (12).

Using the linear regression equation thus simplified, the term δb related to the hardware bias is almost constant, and the ionospheric delay data δI _k is an estimation of the ionospheric delay provided by the Klobuccharo ionospheric model or the international GNSS project. using the value DELTA Ie _k, the difference between the estimated value DELTA Ie _k ionospheric delay bias .delta.I _k Toko is assumed to primary Markov process, it is possible to set the observation equation and the state equation of the following equation.

x (t + 1) = x (t)
y _{k1, d} = Hx (t) + υ (t)
By applying the Kalman filter estimation theory to the state equation and the observation equation, the difference value between the ionospheric delay bias δI _k and the estimated value δIe _k can be estimated, and as a result, the ionospheric delay bias δI _k can be estimated and calculated. Can do. At this time, for the integer value biases N _{L1, k} and N _{L2, k} , the estimated value of the integer value is calculated by the LAMBDA method using the real number estimated value and estimated error covariance by the Kalman filter. By calculating the estimated value of such an integer value, it is possible to estimate and calculate the ionospheric delay bias δI _k with higher accuracy.

  As described above, by using the configuration and processing of the present embodiment, the ionosphere delay bias can be estimated and calculated with high accuracy and easily at the base station.

In the above description, the case where one positioning antenna 10 and one GPS receiver 11 are installed in the base station 1 is described. However, a plurality of positioning antennas and GPS receivers are installed in the base station 1. Also good. Thus, when a plurality of positioning antennas and GPS receivers are used, since the distance between the positioning antennas (GPS receivers) is short, it can be considered that the ionospheric delay bias is the same. Therefore, in the above-described linear regression equation, the observed value can be increased without increasing the number of unknown ionospheric delay bias δI _k , so that the ionospheric delay bias δI _k can be estimated and calculated with higher accuracy. it can.

In the above description, the case where the hardware bias of the base station and the hardware bias of the positioning satellite are considered as the hardware bias has been described. However, the hardware bias of the positioning satellite is on the order of 10 ⁻⁹ . Can be ignored. If it can be ignored in this way, the ionospheric delay bias can be estimated and calculated more easily.

  By the way, the ionospheric delay bias calculated in this way is transmitted to the ionospheric delay information setting apparatus installed separately together with the local station position information. The ionospheric delay information setting device collects the ionospheric delay bias from each base station and the local station position information associated therewith, and calculates ionospheric delay information composed of ionospheric delay data groups in longitude and latitude in the ionosphere. To do. At this time, the ionosphere delay information setting device calculates VTEC (number of vertical electrons in the ionosphere) from the ionosphere delay bias between the base station and each GPS satellite obtained as described above. Further, the ionospheric delay information setting device estimates and calculates a function E (eβ, es) between the latitude eβ of the ionospheric point and the longitude es of the ionospheric point in the Sun-fixed coordinate system, using the calculated VTEC. The function E (eβ, es) thus obtained is transmitted as ionospheric delay information to a positioning satellite, an information providing satellite, or the like. The ionospheric delay information is broadcast from each satellite, and is used, for example, when the own device that performs positioning performs positioning calculation with an unknown positioning device (unknown station). Thereby, each unknown station can perform highly accurate positioning.

It is a conceptual diagram which shows the structure of the positioning system of embodiment of this invention. It is a block diagram which shows the structure of the base station 1 of this embodiment. It is a flowchart which shows the estimation flow of the ionospheric delay bias of the base station 1 of this embodiment.

Explanation of symbols

1-base station 10-positioning antenna 11-GPS receiver 12-navigation message analysis unit 13-satellite information processing unit 14-estimation calculation units SAT1-SATn-positioning satellite

Claims (4)

Multiple positioning satellites that transmit positioning signals;
A positioning system comprising a receiving means for receiving the positioning signal and a base station whose position is known,
The base station
From the satellite information obtained from the positioning signal, observe the code pseudorange and the carrier phase integrated value between the base station and the positioning satellite,
The distance equation between the positioning satellite and the base station is linearly approximated by developing a first order Taylor series at the estimated position of the positioning satellite in the past,
At least the ionospheric delay bias of the base station is included in the explanatory variable as an unknown, the observation value obtained by subtracting the base station position from the carrier phase integrated value and the code pseudorange is included in the objective variable, and the positioning satellite based on the linear approximation Construct a linear regression equation that includes the position as an arithmetic matrix element,
A positioning system comprising estimation calculation means for estimating and calculating the ionospheric delay bias of the base station from the linear regression equation.   The positioning system according to claim 1, wherein the estimation calculation unit includes an integer value bias for each carrier wave in an explanatory variable of the linear regression equation. The base station comprises a plurality of receiving means,
The positioning system according to claim 1 or 2, wherein the estimation calculation means sets a plurality of ionospheric delay biases corresponding to the receiving means as the same ionospheric delay bias for the base station. There are a plurality of the base stations,
The ionosphere information estimation means for estimating and calculating ionosphere information corresponding to the longitude and latitude of the ionosphere based on the ionosphere delay bias estimated and calculated by the plurality of base stations. The positioning system described in.

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