JP2008039689A - Position-detecting device and position-detecting method - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To eliminate a need to start a determination process for an integer value bias again when a cycle slip occurs. <P>SOLUTION: The position-detecting device detects the position of a mobile station by estimating an integer value bias included in an integrated value of the phase of a career wave of a satellite signal that the mobile station observes every predetermined period. In the device, covariance matrix used for estimating the integer value bias is updated by using covariance according to each satellite that has been introduced in the previous period, and, when a new satellite can be observed in the present period, a predetermined initial value, as covariance according to the new satellite, is added to the covariance matrix. <P>COPYRIGHT: (C)2008,JPO&INPIT

Description

  The present invention relates to a position detection device and a position detection method for detecting the position of a mobile station.

  In recent years, GPS surveying using a carrier phase has been widely used in the field of surveying. In this GPS survey using the carrier phase, the reference side receiver and the positioning side receiver simultaneously receive satellite signals sent from a plurality of satellites, and the reference side and the positioning side integrate the carrier phase of each satellite signal. Each value is calculated independently. The integrated value of the carrier phase (hereinafter simply referred to as “phase integrated value”) includes an indeterminate element (hereinafter referred to as “integer value bias”) corresponding to an integral multiple of the wavelength of the carrier. Unlike the clock error or the like, this integer value bias cannot be eliminated by taking a single phase difference or a double phase difference of the phase integration value. For this reason, in the field of GPS surveying, a technique has been proposed in which the integral value bias, which is an uncertain factor, is eliminated by taking the triple phase difference of the phase integration value, or the integer value bias itself is obtained.

Here, as a technique for determining an integer value bias, a technique using a Kalman filter is known (see, for example, Patent Document 1). In this technology, a tracking filter that updates the state variable each time observations are made using the position on the positioning side and the integer bias as the state variables, and the single phase difference on the positioning side relative to the reference side as the observation amount is configured. Is done. As another technique for determining the integer value bias, a technique for obtaining an integer value bias of a double phase difference under a predetermined condition by a least square method using a double phase difference of a carrier wave including the integer value bias is known. (For example, refer to Patent Document 2).
JP 2004-77228 A JP 2003-98245 A

  By the way, the prior art as described above is based on the premise that radio waves from at least five satellites are continuously received (without cycle slip) during the integer value bias determination process. However, in practice, there may be a case where the interruption of radio waves from a satellite that has been or has been determined to be an integer value bias (cycle slip). In this case, the process for determining the integer value bias must be repeated from the beginning. Don't be.

  In addition, the above-mentioned conventional technology does not assume that the positioning side moves during the integer bias determination process, but if the positioning side is a moving body such as a vehicle, the influence of surrounding buildings, tunnels, etc. Thus, cycle slip is likely to occur even during the integer value bias determination process. In addition, since the radio wave reception state from the satellite of the receiver on the mobile body changes due to the movement of the mobile body, it may be necessary to switch the satellite used for positioning.

  Therefore, in view of the above problems, the present invention provides a position detection device and a position detection method that do not require the integer bias determination process to be restarted from the beginning even when a cycle slip or satellite switching occurs. The purpose is to do.

In order to solve the above-described problem, according to one aspect of the present invention, the position of the mobile station is detected by estimating an integer value bias included in the integrated value of the carrier phase of the satellite signal observed by the mobile station every predetermined period. A position detecting device,
When the satellites that can be observed by the mobile station change in this cycle, an integer value based on the observation data of satellites that can be observed in this cycle and the observation data of satellites that can be observed continuously from the previous cycle A position detecting device is provided, characterized in that a bias is estimated, and the covariance relating to the continuously observable satellite derived in the previous period is used for the estimation.

Further, according to another aspect of the present invention, a position detecting device for detecting a position of a mobile station by estimating an integer value bias included in an integrated value of a carrier wave phase of a satellite signal observed by the mobile station every predetermined period Because
Update the covariance matrix used to estimate the integer bias using the covariance associated with each satellite derived in the previous period,
When a new satellite becomes observable in the current cycle, a position detection device is provided, wherein a predetermined initial value is added to the covariance matrix as a covariance related to the new satellite.

  In this aspect, when a satellite that was observable in the previous cycle becomes unobservable in the current cycle, the covariance related to the unobservable satellite may be deleted from the covariance matrix.

Further, according to another aspect of the present invention, a position detecting device for detecting a position of a mobile station by estimating an integer value bias included in an integrated value of a carrier wave phase of a satellite signal observed by the mobile station every predetermined period Because
A determination means for determining a satellite that can be observed by the mobile station based on a predetermined determination criterion;
Based on the determination result by the determination means, for the satellites that can be observed in the previous cycle and the current cycle, the covariance related to the satellite derived in the previous cycle is used, and the satellites that can be observed for the first time in the current cycle are used. On the other hand, using a predetermined initial value, the covariance matrix generating means for generating a covariance matrix related to all satellites that can be observed in the current cycle,
Provided is a position detection device characterized by estimating an integer value bias and updating the covariance matrix using the covariance matrix and observation data relating to each satellite obtained in the current cycle. .

According to another aspect of the present invention, a position detection method for detecting the position of a mobile station by estimating an integer value bias included in an integrated value of a carrier wave phase of a satellite signal observed by the mobile station every predetermined period Because
Update the covariance matrix used to estimate the integer bias using the covariance associated with each satellite derived in the previous period,
When a new satellite becomes observable in the current cycle, a position detection method is provided, wherein a predetermined initial value of the covariance relating to the new satellite is added to the covariance matrix.

  In any of the above aspects, whether or not satellite observation (reception) is impossible or possible is determined by whether or not the satellite signal reception intensity from the satellite is more than a predetermined minimum reception intensity. It may be based on judgment.

  According to the present invention, it is possible to obtain a position detection device and a position detection method that do not require the integer bias determination process to be repeated from the beginning even when a cycle slip or the like occurs.

  The best mode for carrying out the present invention will be described below with reference to the drawings.

  FIG. 1 is a configuration diagram of a carrier phase GPS positioning system according to the present invention. As shown in FIG. 1, the GPS positioning system includes a GPS satellite 10 that orbits the earth, a fixed reference station 20 that is installed at a predetermined position (known point) on the earth, and is positioned on the earth. And a mobile station 30 that can move.

  The GPS satellite 10 always broadcasts navigation messages toward the earth. The navigation message includes orbit information about the corresponding GPS satellite 10, a clock correction value, and an ionospheric correction coefficient. The navigation message is spread by the C / A code, is carried on the L1 carrier (frequency: 1575.42 MHz), and is constantly broadcast toward the earth.

  Currently, 24 GPS satellites 10 orbit the earth at an altitude of about 20,000 km, and each of the four GPS satellites 10 is evenly arranged on six orbiting earth surfaces inclined by 55 degrees. ing. Therefore, as long as the sky is open, at least five GPS satellites 10 can be observed at any time on the earth.

  FIG. 2 is a more detailed configuration diagram of the carrier phase GPS positioning system of FIG. The mobile station 30 includes a GPS receiver 32. In the GPS receiver 32, an oscillator (not shown) whose frequency matches the carrier frequency of the GPS satellite 10 is incorporated. The GPS receiver 32 converts the radio wave received from the GPS satellite 10 through the GPS antenna 32a into an intermediate frequency, and then performs C / A code synchronization using the C / A code generated in the GPS receiver 32. Retrieve the navigation message.

Further, the GPS receiver 32 measures the phase integration value Φ _iu of the carrier phase based on the carrier wave from each GPS satellite 10 _i . For the phase integration value Φ _iu , the subscript i (= 0, 1, 2,...) Indicates the number assigned to each GPS satellite 10 _i , and the subscript u is the integration on the mobile station 30 side. Indicates a value. As shown in the following equation, the phase integration value Φ _iu includes the phase Θ _iu (t) of the oscillator at the carrier reception time t and the carrier phase Θ _iu (t−τ) when the satellite signal is generated in the GPS satellite 10 _i. It is obtained as a difference.
Φ _iu (t) = Θ _iu (t) −Θ _iu (t−τ _u ) + N _iu + ε _iu (t) Equation (1)
Here, τ _u represents the travel time from the GPS satellite 10 to the GPS receiver 32, and ε _iu represents noise (error). Note that at the start of observation of the phase difference, the GPS receiver 32 can accurately measure the phase within one wavelength of the carrier wave phase, but cannot determine what wavelength it corresponds to. For this reason, an integer value bias N _iu is introduced to the phase integrated value Φ _iu (t) as an uncertain element as shown in the above equation.

  The mobile station 30 also includes a communication device 33 such as a mobile phone. As will be described later, the communication device 33 is configured to perform bidirectional communication with a communication facility 23 such as a mobile phone base station on the reference station 20 side.

The reference station 20 has a GPS receiver 22 including a GPS antenna 22a. GPS receiver 22, similar to the GPS receiver 32 of mobile station 30, based on the carrier wave from the GPS satellite 10 _i, as shown in the following equation, the integrated value [Phi _ib carrier phase at time t (t) Measure.
Φ _ib (t) = Θ _ib (t) −Θ _ib (t−τ _b ) + N _ib + ε _ib (t) Equation (2)
N _ib represents an integer value bias, and ε _ib represents noise (error). For the phase integration value Φ _ib , the subscript b indicates the integration value on the reference station 20 side. The reference station 20 transmits the measured phase integrated value Φ _ib to the mobile station 30 via the communication facility 23. A plurality of reference stations 20 are installed in a predetermined area. As shown in FIG. 2, each reference station 20 and communication facility 23 (or a plurality of communication facilities) may be connected via a network such as the Internet, or a communication facility 23 may be provided for each reference station 20. . In the former configuration, the mobile station 30 can obtain the information received by each reference station 20 as long as it can communicate with the communication facility 23.

  FIG. 3 is a functional block diagram showing an embodiment of the position detection apparatus 34 according to the present invention mounted on the mobile station 30. The position detection device 34 according to the present embodiment is configured with a calculator 40 as the center, and the calculator 40 is connected to the GPS receiver 32 and the communication device 33 described above. Further, various sensors 50 mounted on the mobile station 30 are connected to the computing unit 40. Note that the computing unit 40 may be incorporated in the GPS receiver 32. When the mobile station 30 is a vehicle, the GPS receiver 32, the computing unit 40, and / or the communication device 33 may be mounted in the navigation device.

  The computing unit 40 may be composed of a microcomputer, and includes a satellite position calculating unit 42, a dynamic state quantity introducing unit 44, and an integer value bias estimating unit 48, as shown in FIG.

The satellite position calculation unit 42, based on the orbit information of the navigation message received by the GPS receiver 32, the position (X _i (t), Y) of each observable GPS satellite 10 _i in the world coordinate system at time t. _i (t), Z _i (t)) is calculated. Since the GPS satellite 10 is one of artificial satellites, its movement is limited to a certain plane (orbital plane) including the center of gravity of the earth. The orbit of the GPS satellite 10 is an elliptical motion with the earth's center of gravity as one focal point, and the position of the GPS satellite 10 on the orbital plane can be calculated by sequentially calculating the Kepler equation. Further, the position (X _i (t), Y _i (t), Z _i (t)) of each GPS satellite 10 _i at the carrier wave reception time t is determined by the orbital plane of the GPS satellite 10 and the equatorial plane of the world coordinate system. In consideration of the rotational relationship, the position of the GPS satellite 10 on the orbital plane is obtained by three-dimensional rotational coordinate conversion. As shown in FIG. 4, the world coordinate system is defined by an X axis and a Y axis that are orthogonal to each other within the equator plane, and a Z axis that is orthogonal to both axes, with the center of gravity as the origin.

  The dynamic state quantity introduction unit 44 calculates a predetermined dynamic state quantity of the mobile station 30 based on the output signals of the various sensors 50 input at a predetermined period, and creates a known input. For example, when the mobile station 30 is a vehicle, the dynamic state quantity introducing unit 44 includes two wheel speed sensors set on the non-driven wheels of the vehicle, various sensors such as a yaw rate sensor, a right / left G acceleration sensor, and an azimuth meter. Based on the 50 output signals, the vehicle longitudinal speed Vx (t) and the vehicle lateral speed Vy (t) at the carrier wave reception time t are calculated.

  Since the vehicle speed vectors (Vx (t), Vy (t)) are based on the body coordinate system (see FIG. 4) based on the vehicle body, the dynamic state quantity introducing unit 44 uses the speed vector (Vx ( t) and Vy (t)) are coordinate-converted into the world coordinate system via the local coordinate system. Normally, coordinate rotation conversion can be realized using Euler angles, but here, conversion from the body coordinate system to the local coordinate system is realized only with the yaw angle ψ (t), assuming that the roll angle and pitch angle are small. (However, it is naturally possible to consider the roll angle and the pitch angle, or to ignore the yaw angle.) The conversion from the local coordinate system to the world coordinate system is realized by conversion using the longitude φ (t) and the latitude λ (t) of the vehicle position.

Specifically, the vehicle position in the world coordinate system _{(X u, Y u, Z} u) and the longitude and latitude of the vehicle position (phi, lambda) and when, velocity vector d of the vehicle in terms of the world coordinate system / Dt [X _u , Y _u , Z _u ] is as follows:
d / dt [X _u , Y _u , Z _u ] ^T = rot (φ, λ) · rot (ψ) · [Vx, Vy] ^T equation (3)
Here, [] ^T means transposition of a matrix, and rot (φ, λ) and rot (ψ) are as follows.

尚、経度φ（ｔ）及び緯度λ（ｔ）は、測量が既に完了している所定地点の既知の経度及び緯度（固定値）であってよい。但し、経度φ（ｔ）及び緯度λ（ｔ）は、単独測位により得られる移動局３０の経度φ（ｔ）及び緯度λ（ｔ）（変動値）であってもよい。また、ヨー角度ψ（ｔ）は、ヨー角速度（ヨーレートセンサの検出信号）を積分することで算出されてよく、若しくは、方位角計を用いて決定されてもよい。

The longitude φ (t) and the latitude λ (t) may be known longitudes and latitudes (fixed values) at predetermined points where surveying has already been completed. However, the longitude φ (t) and the latitude λ (t) may be the longitude φ (t) and the latitude λ (t) (variation value) of the mobile station 30 obtained by independent positioning. Further, the yaw angle ψ (t) may be calculated by integrating the yaw angular velocity (detection signal of the yaw rate sensor) or may be determined using an azimuth meter.

If the right side of the above equation (3) is placed as inputs U01, U02, and U03 and discretized, the result is as follows.
X _u (t _n ) = X _u (t _n−1 ) + DT · U01 Expression (4)
Y _u (t _n ) = Y _u (t _n−1 ) + DT · U02 Formula (5)
Z _u (t _n ) = Z _u (t _n−1 ) + DT · U03 Equation (6)
Therefore, the final known input is as follows.
U = [DT · U01, DT · U02, DT · U03] ^T equation (6-1)
In the above equation, DT is a sample time (data update interval), and t _n = t _n−1 + DT. In the following description, for the sake of explanation, it is assumed that the sample time DT is the same as the calculation cycle of the phase integration value by the GPS receivers 22 and 32 described above.

In the integer value bias estimation unit 48, observation data relating to each GPS satellite 10 _i (particularly, the phase integrated value Φ _ib on the reference station 20 side received by the mobile station 30 via the communication device 33 and the phase on the mobile station 30 side). The integer value bias is estimated based on the integrated value Φ _iu ).

Specifically, the double phase difference between the phase integration values for the two GPS satellites 10 _j , 10 _h (i = j, h, where j ≠ h) at time t is expressed by the following equation.
[ _{Phi] jhbu} = ([ _{Phi] jb} (t)-[Phi] _ju (t))-([ _{Phi] hb} (t)-[Phi] _hu (t)) Equation (7)
On the other hand, the double phase difference Φ _jhbu of the phase integrated value is expressed as (distance between GPS satellite 10 _i and GPS receiver 22 or 32) = (wavelength L of carrier wave) × (phase integrated value), It becomes as follows.

ここで、式（８）における［Ｘ_ｂ（ｔ）、Ｙ_ｂ（ｔ）、Ｚ_ｂ（ｔ）］は、時刻ｔにおける基準局２０のワールド座標系における座標値（既知）であり、［Ｘ_ｕ（ｔ）、Ｙ_ｕ（ｔ）、Ｚ_ｕ（ｔ）］は、時刻ｔにおける移動局３０の座標値（未知）であり、［Ｘ_ｊ（ｔ）、Ｙ_ｊ（ｔ）、Ｚ_ｊ（ｔ）］及び［Ｘ_ｈ（ｔ）、Ｙ_ｈ（ｔ）、Ｚ_ｈ（ｔ）］は、時刻ｔにおける各ＧＰＳ衛星１０_ｊ、１０_ｈの座標値（衛星位置算出部４２により算出）である。Ｎ_ｊｈｂｕは、整数値バイアスの２重位相差である（即ち、Ｎ_ｊｈｂｕ＝（Ｎ_ｊｂ−Ｎ_ｊｕ）−（Ｎ_ｈｂ−Ｎ_ｈｕ））。尚、時刻ｔは、例えばGPS時刻で同期が取られているものとする。

Here, [X _b (t), Y _b (t), Z _b (t)] in Expression (8) are coordinate values (known) in the world coordinate system of the reference station 20 at time t, and [X _u (T), Y _u (t), Z _u (t)] are coordinate values (unknown) of the mobile station 30 at time t, and [X _j (t), Y _j (t), Z _j (t) ]] And [X _h (t), Y _h (t), Z _h (t)] are the coordinate values (calculated by the satellite position calculation unit 42) of the GPS satellites 10 _j and 10 _h at time t. N _jhbu is a double phase difference of an integer bias (that is, N _jhbu = (N _jb −N _ju ) − (N _hb −N _hu )). The time t is assumed to be synchronized with, for example, GPS time.

In the integer value bias estimation unit 48, the following state equation is set using the known input derived by the dynamic state quantity introduction unit 44 (see the above equation (6-1)).
η (t _n ) = η (t _n−1 ) + U (t _n−1 ) + W (t _n−1 ) Equation (9)
Here, η (t _n ) represents a state variable at time t = t _n , and the position of the mobile station 30 [X _u (t _n ), Y _u (t _n ), Z _u (t _n )], And an integer value bias double phase difference N _ijbu (where i ≠ j). Here, the double difference _{N Ijbu} integer bias is required at least four, for example, when five GPS satellites _{10 0-4} is observable, based on the GPS satellites 10 _0, eta = [X _{u, Y u, Z u,} N 01bu, N 02bu, N 03bu, may be _{N 04bu].} U and W are the above-mentioned known input and disturbance (system noise: normal white noise), respectively.

The integer value bias estimation unit 48 employs the following observation equation.
Z (t _n ) = H (t _n ) · η (t _n ) + V (t _n ) (10)
Here, Z and V indicate an observation amount and an observation noise (normal white noise), respectively. The observation amount Z is a double phase difference of phase integration values (see the above formula (7)). State equation of the equation (9) is a linear, observation quantity Z is the state variable _X u, _Y since it is non-linear with respect to _u and _{Z u,} each term state variable _X u of the formula (8), _{Y u} And Z _u are partially differentiated to obtain H in equation (10).

Therefore, when the Kalman filter is applied to the state equation of the above equation (9) and the observation equation of the above equation (10), the following equation is obtained.
As time update,
η (t _n ) ⁽⁻⁾ = η (t _n−1 ) ⁽⁺⁾ + U (t _n−1 ) Equation (11)
P (t _n ) ⁽⁻⁾ = P (t _n−1 ) ⁽⁺⁾ + Q (t _n−1 ) Formula (12)
As an observation update,
^{_{K (t n) = P (}} t n) (-) · H T (t n) · (H (t n) · P (t n) (-) · H T (t n) + R (t n)) ^-1 Formula (13)
η (t _n ) ⁽⁺⁾ = η (t _n ) ⁽⁻⁾ + K (t _n ) · (Z (t _n ) −H (t _n ) · η (t _n ) ⁽⁻⁾ ) (14)
P (t _n ) ⁽⁺⁾ = P (t _n ) ⁽⁻⁾ −K (t _n ) · H (t _n ) · P (t _n ) ⁽⁻⁾ Equation (15)
Here, Q and R represent a covariance matrix of disturbance and a covariance matrix of observation noise, respectively. The above equations (11) and (14) are filter equations, the above equation (13) is a filter gain, and the above equations (12) and (15) are covariance equations. In addition, ^(-) and ⁽⁺⁾ indicated by superscript indicate before and after updating.

Next, with reference to FIG. 5, the operation of the position detection device 34 of the present embodiment will be described. The processing routine shown in FIG. 5 is executed at every calculation period (sample time DT) of the phase integrated value by the GPS receivers 22 and 32. Hereinafter, a processing routine at time t = t _n (= t _n−1 + DT) will be described as an example.

First, at step 100, the satellite information (position information of each GPS satellite 10 _i at time t = _{t n,} the phase integrated value of the reference station 20 side for each GPS satellite 10 _i, and, in the mobile station 30 side with respect to each GPS satellite 10 _i (Phase integrated value) is acquired.

In the following step 110, the satellite information obtained in the previous cycle (t = t _n-1 ) and the satellite information obtained in the current cycle are compared, and the satellite switching (for example, new whether such GPS satellites 10 _i of the occurrence and the GPS satellites 10 _i loss) has occurred is determined. At this time, only the GPS satellite 10 _i for which a predetermined minimum reception intensity or more is secured may be considered. That is, the GPS satellite 10 _i that has fallen below the minimum reception intensity in this cycle may be determined to be “disappeared (unobservable)”, and the GPS satellite 10 _i that has exceeded the minimum reception strength in this cycle may be determined. May be determined to be “appearance (observable)”.

If it is determined in step 110 that the switching of the GPS satellite 10 _i has occurred, a reorganization process of the error covariance matrix P is executed (step 120). For example, it is received reference satellite 10 _non-zero five GPS satellites 10 _1-5 previous cycle, when the reception from the GPS satellites ₁₀₆ in this period was newly discovered, resulting in the previous cycle was error covariance matrix ^{_{P (t n-1) (}} +) with respect to (the formula (12)), and as shown in FIG. 6 (a), the covariance is newly added according to the GPS satellites 10 ₆ Is done. In this case, the covariance of the five GPS satellites 10 _1-5 is not to be initialized, the covariance obtained in the previous cycle is taken over, only covariances of the new GPS satellites 10 ₆ Initialized with a predetermined initial value. In FIG. 6A, a numerical value in the frame 70 (0 except for the diagonal component 100/3) is shown as an example of the predetermined initial value. The predetermined initial value is not necessarily a predetermined value, and a plausible value may be adopted.

On the other hand, have been received five GPS satellites 10 _1-5 previous cycle, when the reception is interrupted from the GPS satellites 10 ₄ in this period, the error covariance matrix P (t obtained in the previous cycle ^_n-1) with respect to ^(+), as shown in FIG. 6 (B), the covariance is deleted according to the GPS satellite 10 _4, the covariance of the other four GPS satellites _{10 1-3,5} Taken over.

Further, in this step 120, in the time update of the above equation (11), the state variable η (t _n-1 ) ⁽⁺⁾ (the above equation ^{) as} in the error covariance matrix P (t _n-1 ) ⁽⁺⁾ The reorganization process is also executed for (see (12)). For example, in the example shown in FIG. 7 (A), corresponding to the new appearance of the GPS satellites _106, the state variables associated with the GPS satellites ₁₀₆ is initialized by predetermined initial value, in FIG. 7 (B) in the example shown, in response to loss of GPS satellites 10 _4, the state variables associated with the GPS satellites ₁₀₄ are deleted.

In the subsequent step 130, the above formulas (13) to (15) are applied, and positioning calculation is executed. At this time, in the case of passing through the step 120, η (t _n ) ⁽⁻⁾ and P (t _n ) ⁽⁻⁾ obtained through the reorganization process are used. The error covariance matrix P (t _n ) ⁽⁺⁾ of the current cycle obtained in this step 130 is the process of step 120 in the next cycle (t = t _{n + 1} ) together with the state variable (t _n ) ^(+). It will be used in.

In the following step 140, processing for calculating and outputting a positioning solution is executed. The estimated value of the integer bias obtained from step 130 is obtained as a real number solution. However, since the integer value bias is actually an integer value, the closest integer solution (that is, wave number) is obtained with respect to the obtained real number solution. As this method, the integer value bias is decorrelated, and the search space for the integer solution is narrowed to specify the solution.
An MBDA method or the like may be used. In addition, when the GPS receivers 22 and 32 are two-frequency receivers that can receive both the L1 wave and the L2 wave emitted from the GPS satellite 10, the above-described operation is performed for each of the L1 wave and the L2 wave. Similar estimation may be performed simultaneously and in parallel to create a sum of both periods (wide lane) to narrow down integer solution candidates with integer bias.

  If the integer solution of the integer value bias is determined in this manner, the position of the mobile station 30 can be determined with high accuracy by the interference positioning method using the integer solution of the integer value bias unless a cycle slip occurs thereafter. Can be calculated.

  By the way, according to the present embodiment, by inputting a known external input U (k) to the Kalman filter, it is possible to calculate a state variable (positioning, integer value bias) even when the mobile station 30 moves. . Therefore, even if the position detection device 34 according to the present embodiment is mounted on a moving body such as a vehicle, highly accurate positioning can be realized.

However, during the actual movement of the mobile station 30, the radio wave reception state from each GPS satellite 10 _i is not stable due to the influence of surrounding buildings, tunnels, etc., and the radio wave is stably received from a certain number of GPS satellites 10 _i. There are cases where it is not possible. Further, as the mobile station 30 moves over a long distance, the GPS satellite 10 _i that can be observed (receivable) by the mobile station 30 may change, and the GPS satellite 10 _i may need to be switched. On the other hand, every time the combination of the five GPS satellites 10 _i changes, the integer value bias determination process is restarted from the beginning for the new five GPS satellites 10 _i (that is, In the configuration in which all the covariances related to the GPS satellite 10 _i are initialized), the position detection accuracy is temporarily deteriorated frequently due to the initialization, which is inappropriate for a moving body such as a vehicle.

On the other hand, according to the present embodiment, as described above, even when the GPS satellite 10 _i is switched or a cycle slip occurs, the covariance derived before that is taken over and used. Therefore, it is not necessary to repeat the integer bias determination process from the beginning after the GPS satellite 10 _i is switched, and the position detection accuracy is not greatly deteriorated. Therefore, according to the present embodiment, it is possible to realize position detection that is robust against switching of GPS satellites 10 _i and cycle slip, and stable position detection accuracy even when mounted on a moving body such as a vehicle. Can be maintained.

Further, according to the present embodiment, as described above, when the appearance of a new GPS satellite 10 _i (i ≠ 0) excluding the reference satellite is confirmed, the covariance related to the GPS satellite 10 _i is added as needed. Therefore, there is a high possibility that the covariance (covariance other than the initial value) related to four or more GPS satellites 10 _i can be used at all times. Therefore, according to this embodiment, even during movement of the mobile station 30 in an environment where radio wave reception state is not stable, as long as the reception from the GPS satellites 10 ₀ a reference satellite is not lost, to maintain a high detection accuracy be able to.

FIG. 8 shows test data demonstrating high position detection accuracy realized by the position detection device 34 according to the present embodiment. FIG. 8A shows a test result by a configuration to which the algorithm of the present embodiment (covariance reorganization process described above) is applied, the horizontal axis indicates the number of epochs (calculations), and the vertical axis indicates the positioning error. Show. FIG. 8B shows a test result by a configuration in which the error covariance matrix P is initialized every time the GPS satellite 10 _i is switched. All the calculation results are executed using the same satellite orbit data in which switching of the GPS satellites 10 _i (i ≠ 0) excluding the reference satellite occurs frequently.

When the algorithm of the present embodiment is not applied, as shown in FIG. 8B, when the GPS satellite 10 _i is switched, a large accuracy error occurs and the variation of the solution is large. When the algorithm of this embodiment is applied, as shown in FIG. 8A, the dispersion of the solution is small, and it becomes possible to obtain a solution with good accuracy.

  The preferred embodiments of the present invention have been described in detail above. However, the present invention is not limited to the above-described embodiments, and various modifications and substitutions can be made to the above-described embodiments without departing from the scope of the present invention. Can be added.

  For example, in the above-described embodiment, the Kalman filter is applied to the state equation of the above equation (9) and the observation equation of the above equation (10), but the present invention uses other estimation methods such as the least square method. The present invention can also be applied to the applied configuration. For example, in the case of the least square method, similarly, the reorganization processing similar to the above may be applied to the covariance (and / or the variance of the diagonal components) of the non-diagonal components of the error matrix.

  In the above-described embodiment, the known input U is introduced into the state equation of the above equation (9) so that the integer value bias can be determined with high accuracy in a short time even while the mobile station 30 is moving. The dynamic movement of the mobile station 30 may be compensated by other methods, or the compensation may be simply omitted (that is, there is no known input U).

  In the above-described embodiment, the influence of the initial phase of the oscillator and the clock error in the GPS receivers 22 and 32 is eliminated by taking the double phase difference as described above. The configuration may be a single phase difference that can eliminate only the initial phase and the GPS clock error, or a configuration that does not take any phase difference. Further, in this embodiment, the ionospheric refraction effect, the tropospheric refraction effect, and the influence of multipath are ignored, but these may be taken into consideration.

In the above description, for convenience, there is a case that the reference satellite to the GPS satellites 10 _0, depending on the position of the mobile station 30 and the reference station 20, the other GPS satellites ₁₀ i (= 1, 2, ·・ ・) Can be a reference satellite.

  In the above description, a vehicle is given as an example of the mobile station 30, but the mobile station 30 may be a hawk lift, robot, receiver 32, and / or arithmetic unit in which the receiver 32 and / or the arithmetic unit 40 is mounted. An information terminal such as a mobile phone incorporating the device 40 is included.

  In the above-described embodiment, constants are used for other covariance matrices (for example, Q and R), so that reorganization processing for the error covariance matrix P is unnecessary, but constants are not adopted. In this case, a similar reorganization process may be applied to other covariance matrices.

1 is a configuration diagram of a carrier phase GPS positioning system according to the present invention. It is a more detailed block diagram of the carrier wave phase type GPS positioning system of FIG. 2 is a functional block diagram showing an embodiment of a position detection device 34 according to the present invention mounted on a mobile station 30. FIG. It is a figure which shows the relationship between a world coordinate system and a local coordinate system, and the relationship between a local coordinate system and a body coordinate. It is a flowchart of the process implement | achieved by the position detection apparatus 34 of a present Example. It is explanatory drawing of the reorganization process of the error covariance matrix P accompanying the switching of the GPS satellite 10 _i . It is an illustration of a reorganization of the state variable η accompanying switching of the GPS satellites 10 _i. It is test data which demonstrates the high position detection accuracy implement | achieved by the position detection apparatus 34 by a present Example.

Explanation of symbols

DESCRIPTION OF SYMBOLS 10 GPS satellite 20 Reference station 22 Reference station side GPS receiver 30 Mobile station 32 Mobile station side GPS receiver 34 Position detector 40 Calculator 42 Satellite position calculation part 44 Dynamic state quantity introduction part
48 Integer Bias Estimator

Claims (10)

A position detection device that detects an integer value bias included in an integrated value of a carrier wave phase of a satellite signal observed by a mobile station every predetermined period, and detects the position of the mobile station,
When the satellites that can be observed by the mobile station change in this cycle, an integer value based on the observation data of satellites that can be observed in this cycle and the observation data of satellites that can be observed continuously from the previous cycle A position detecting apparatus, wherein a bias is estimated, and the covariance relating to the continuously observable satellite derived in the previous cycle is used for the estimation. A position detection device that detects an integer value bias included in an integrated value of a carrier wave phase of a satellite signal observed by a mobile station every predetermined period, and detects the position of the mobile station,
Update the covariance matrix used to estimate the integer bias using the covariance associated with each satellite derived in the previous period,
When a new satellite becomes observable in the current cycle, a predetermined initial value is added to the covariance matrix as a covariance related to the new satellite.   The position detection apparatus according to claim 2, wherein when a satellite that can be observed in the previous cycle becomes unobservable in the current cycle, the covariance related to the satellite that has become unobservable is deleted from the covariance matrix.   The position detection device according to claim 1, which is mounted on a vehicle.   The position detection apparatus according to claim 4, further comprising a detection unit that detects a dynamic state quantity related to the movement of the vehicle, and uses the detection result of the dynamic state quantity for estimation of an integer value bias. A position detection device that detects an integer value bias included in an integrated value of a carrier wave phase of a satellite signal observed by a mobile station every predetermined period, and detects the position of the mobile station,
A determination means for determining a satellite that can be observed by the mobile station based on a predetermined determination criterion;
Based on the determination result by the determination means, for the satellites that can be observed in the previous cycle and the current cycle, the satellite that can be observed for the first time in the current cycle using the covariance of the satellite derived in the previous cycle. On the other hand, using a predetermined initial value, the covariance matrix generating means for generating a covariance matrix related to all satellites that can be observed in the current cycle,
A position detection apparatus that estimates an integer value bias and updates the covariance matrix using the covariance matrix and observation data relating to each satellite obtained in the current cycle. A position detection method for detecting a position of a mobile station by estimating an integer value bias included in an integrated value of a carrier wave phase of a satellite signal observed by the mobile station every predetermined period,
When the satellites that can be observed by the mobile station change in this cycle, an integer value based on the observation data of satellites that can be observed in this cycle and the observation data of satellites that can be observed continuously from the previous cycle A position detection method characterized in that a bias is estimated, and the covariance relating to the continuously observable satellite derived in the previous cycle is used for the estimation. A position detection method for detecting a position of a mobile station by estimating an integer value bias included in an integrated value of a carrier wave phase of a satellite signal observed by the mobile station every predetermined period,
Update the covariance matrix used to estimate the integer bias using the covariance associated with each satellite derived in the previous period,
When a new satellite becomes observable in the current cycle, a predetermined initial value is added to the covariance matrix as a covariance related to the new satellite. A position detection method for detecting a position of a mobile station by estimating an integer value bias included in an integrated value of a carrier wave phase of a satellite signal observed by the mobile station every predetermined period,
Determining satellites that can be observed by the mobile station based on predetermined criteria;
Based on the determination result by the determination means, for the satellites that can be observed in the previous cycle and the current cycle, the satellite that can be observed for the first time in the current cycle using the covariance of the satellite derived in the previous cycle. On the other hand, using a predetermined initial value, generating a covariance matrix for all satellites that can be observed in the current cycle;
A position detection method comprising: estimating an integer value bias using the covariance matrix and observation data relating to each satellite obtained in the current cycle and updating the covariance matrix.   A storage medium storing a computer-readable program for executing the position detection method according to claim 7.

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