JP2009041932A - Mobile object positioning apparatus - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To obtain a position of a mobile object by using a proper error variance in response to a reception condition of a satellite radio wave. <P>SOLUTION: A mobile object positioning apparatus of the invention comprises: an inertial navigation positioning means for obtaining the position of the mobile object by an inertial navigation; a satellite navigation positioning means for obtaining the position of the mobile object by a satellite navigation; a state quantity estimating means for considering an observation quantity as a relationship between positioning results of the inertial navigation positioning means and the satellite navigation positioning means, considering a state quantity as a correction parameter used in the inertial navigation positioning means, using the error variation of the positioning result of the satellite navigation positioning means, and estimating the state quantity; a means for reflecting the state quantity estimated by the state quantity estimating means to positioning in the inertial navigation positioning means; and a correcting means for correcting the error variance in response to the reception condition of the satellite radio wave received by the mobile object. <P>COPYRIGHT: (C)2009,JPO&INPIT

Description

  The present invention relates to a positioning device for a moving body that is mounted on a moving body and measures the position of the moving body.

  Conventionally, position error variance obtained from satellite navigation (GPS) and position error variance obtained from inertial navigation (self-contained navigation: INS) are derived, and the proportional distribution coefficient corresponding to the inverse ratio of both is derived. A technique for integrating GPS position information and INS position information is known (see, for example, Patent Document 1).

Further, in the above-mentioned Patent Document 1, the GPS position information and the INS position information are simply combined at the final stage, but the vehicle position is more closely coordinated by GPS / INS coordinated positioning using both satellite navigation and inertial navigation. There is also known a vehicle position measurement device that measures the position of the vehicle (see, for example, Patent Document 2). Patent Document 2 discloses a drift correction method for an inertial navigation device and an offset correction method for a satellite navigation device.
JP-A-9-72746 JP-A-1-316607

  By the way, when positioning a moving body position using GPS / INS coordinated positioning, correction parameters such as drift of an inertial navigation apparatus are estimated and corrected using error variance of the moving body position measured by satellite navigation. It is useful to do.

  However, when the error variance of the mobile object position measured by satellite navigation is used as it is (that is, when it is used without correction), an inappropriate error variance is used depending on the reception state of the satellite radio wave received by the mobile object. As a result, the positioning accuracy may deteriorate.

  Therefore, an object of the present invention is to provide a mobile positioning device that can measure the position of a mobile body using an appropriate error variance according to the reception state of satellite radio waves received by the mobile body.

In order to achieve the above object, a first invention is a positioning device for a moving body that is mounted on a moving body and measures the position of the moving body.
Inertial navigation positioning means for positioning the position of the moving body by inertial navigation;
Satellite navigation positioning means for positioning the position of the moving body by satellite navigation;
The relationship between the positioning result of the satellite navigation positioning means and the positioning result of the inertial navigation positioning means is an observation amount, the correction parameter used in the inertial navigation positioning means is a state quantity, and the error of the positioning result of the satellite navigation positioning means State quantity estimation means for estimating the state quantity using variance;
Means for reflecting the state quantity estimated by the state quantity estimating means in the positioning of the inertial navigation positioning means;
And correction means for correcting the error variance according to a reception state of satellite radio waves received by the mobile body.

2nd invention is the positioning apparatus for moving bodies which concerns on 1st invention,
The correction means does not correct the error variance when a predetermined number or more of satellites are captured, and corrects the error variance when less than a predetermined number of satellites are captured.

3rd invention is the positioning apparatus for moving bodies which concerns on 1st or 2nd invention,
The correction means uses the position of the moving body measured by the inertial navigation positioning means at a period corresponding to an observation period in which a predetermined number or more of satellites are captured as a base point for movement to estimate the position of the subsequent moving body Comparing the estimated position of the moving object estimated by the moving object position estimating means with the positioning position of the moving object measured by the inertial navigation positioning means at a period corresponding to the estimated position. The error variance is corrected based on the comparison result.

4th invention is the positioning apparatus for moving bodies which concerns on 3rd invention,
The mobile object position estimating means estimates the position of the mobile object having a period corresponding to an observation period in which less than a predetermined number of satellites are captured.

5th invention is the positioning apparatus for moving bodies which concerns on 3rd or 4th invention,
The correction means derives a difference between the estimated position and the positioning position using at least two orthogonal direction components, and based on the derived difference between the direction components, the error variance relating to each corresponding direction component is calculated. It is characterized by correcting.

6th invention is the positioning apparatus for moving bodies which concerns on 5th invention,
The correction means corrects the error variance in a direction in which the error variance increases at a higher rate when the derived difference is large than when the derived difference is small.

7th invention is the positioning apparatus for moving bodies which concerns on any invention among the 1st-6th,
The correction means derives an index value indicating the reception state of the satellite radio wave in at least two orthogonal directions based on the reception result of the satellite radio wave, and corresponding each of the corresponding values based on the derived index value of each direction component The error variance related to the direction component is corrected.

An eighth invention is the positioning device for a moving body according to the seventh invention,
The index value is based on the number of satellites existing within a predetermined range with respect to each direction and the reception intensity of satellite radio waves from each satellite in the mobile body.

  ADVANTAGE OF THE INVENTION According to this invention, the positioning apparatus for moving bodies which can position the position of a moving body using the suitable error dispersion | distribution according to the reception state of the satellite electromagnetic wave received with a moving body is obtained.

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

  FIG. 1 is a system configuration diagram showing a vehicle positioning system 100 including an embodiment of a mobile positioning apparatus according to the present invention.

  In the following, a vehicle position positioning system that appropriately measures the position of a vehicle as a moving body will be exemplified, but the present invention is applicable to any moving body other than a vehicle. Other mobile objects may include motorcycles, railways, ships, aircraft, hawk lifts, robots, and information terminals such as mobile phones that move as people move.

  The vehicle position positioning system 100 includes a satellite navigation positioning device 110, an inertial navigation positioning device 200, a Kalman filter (state estimator) 120, a vehicle model 130, and an error variance correction unit 140 as main components.

  The satellite navigation positioning device 110 includes a GPS receiver and a GPS antenna (not shown) as main components. The GPS receiver of the satellite navigation positioning device 110 measures the vehicle position and vehicle speed based on the satellite signal input via the GPS antenna. The vehicle position and the vehicle speed may be measured by a so-called single positioning method. Here, it is assumed that the vehicle position and the vehicle speed are obtained by a latitude, longitude, and altitude coordinate system (llh and NED). In addition, the GPS receiver calculates an error variance of the vehicle position and the vehicle speed in the positioning process. The error variance is derived for each component of latitude, longitude, and altitude. Any appropriate method may be adopted as a method for calculating the error variance. The error variance calculated by the satellite navigation positioning device 110 is input to the error variance correction unit 140 for each positioning cycle.

  As shown in FIG. 1, the inertial navigation positioning device 200 is based on an output signal of an IMU (inertial measurement unit) 202 including a triaxial acceleration sensor and a triaxial angular velocity sensor, and the vehicle position, speed, and vehicle attitude (azimuth angle). Is calculated. The vehicle position positioning method by inertial navigation can be various and any method can be used. For example, the vehicle position is obtained by integrating the output value of the acceleration sensor twice by performing posture conversion, gravity correction, and Coriolis force correction, and the moving distance obtained by the two-time integration is calculated as the previous value of the vehicle position (vehicle position positioning system). It may be derived by adding up to the previous value feedback of 100 final positioning results. Here, also in the inertial navigation positioning apparatus 200, the vehicle position and the vehicle speed are obtained by a coordinate system (NED) of latitude, longitude, and altitude. The vehicle position and vehicle speed (INS temporary positioning result) measured by the inertial navigation positioning device 200 are the difference values between the vehicle position and vehicle speed (GPS positioning result) measured by the satellite navigation positioning device 110 for each positioning cycle. And the difference value is input to the Kalman filter 120. That is, the difference in vehicle position and the difference in vehicle speed are input to the Kalman filter 120 as the observation amount z. At this time, the GPS positioning result and the INS temporary positioning result are differenced in a time-synchronized manner (for example, the difference is taken in synchronization with GPS time as a reference).

The Kalman filter 120 receives the difference value between the GPS positioning result and the INS temporary positioning result as an input, and corrects the INS correction that is the state quantity so as to be the most probable value depending on the reliability of the GPS positioning result and the INS temporary positioning result. Estimate the value η. The INS correction value η may include correction values related to vehicle attitude, bias of the acceleration sensor and angular velocity sensor, and drift, in addition to correction values related to the vehicle position and speed. In the Kalman filter 120, for example, the INS correction value η is estimated as follows. The state equation is set as follows.
η (t _n ) = F · η (t _n−1 ) + G · u (t _n−1 ) + Γ · w (t _n−1 )
Here, η (t _n ) represents a state variable at time t = t _n , and u (t _n−1 ) and w (t _n−1 ) respectively represent time t = t _n−1. Are known inputs and disturbances (system noise: normal white noise). η (t _n ) represents errors δr (INS) and δv (INS) of the vehicle estimated position r (INS) and the vehicle estimated speed V (INS) estimated by the inertial navigation positioning device 200, and the inertial navigation positioning device 200. The vehicle posture error δε (INS) estimated by the above equation, the IMU 202 angular velocity sensor bias error δb, the IMU 202 acceleration sensor drift error δd, the vehicle tire radius error δs, and the like may be included.

The observation equation is set as follows.
z (t _n ) = H (t _n ) · η (t _n ) + v (t _n )
The observation amount z (t _n ) is a difference value between the GPS positioning result and the INS temporary positioning result at time t = t _n−1 . H (t _n ) is an observation matrix, and v (t _n ) is an observation noise.

  The vehicle model 130 is a model that estimates the position of the vehicle using outputs from various on-vehicle sensors as inputs. Various methods for constructing this type of vehicle model have been proposed, and any method may be used. The illustrated vehicle model 130 is a model that estimates the position of the vehicle by estimating the amount of movement of the vehicle from a base point (described later) whose position is known, using the output of the wheel speed sensor 132 as an input. Here, also in the vehicle model 130, it is assumed that the estimated vehicle position is obtained by a coordinate system (NED) of latitude, longitude, and altitude. When the movement amount of the vehicle is calculated in another coordinate system such as a fixed earth coordinate system based on WGS84, for example, the movement amount is converted into coordinates, and the converted movement amount is converted into longitude and altitude coordinates. By integrating the base point of the system, the estimated vehicle position in the longitude and altitude coordinate system can be calculated. The vehicle position estimated by the vehicle model 130 is input to the error variance correction unit 140.

  The error variance correction unit 140 corrects the error variance input from the satellite navigation positioning device 110 according to the reception state of the satellite radio wave received by the vehicle. The error variance correction unit 140 inputs the corrected error variance to the Kalman filter 120. In the Kalman filter 120, the error variance input from the error variance correction unit 140 is used as the variance of the observation noise, and the state quantity (INS correction value η) is estimated. The error variance correction process of the error variance correction unit 140 will be described in detail later.

  FIG. 2 is a flowchart showing a positioning calculation process realized by the vehicle positioning system 100 of the present embodiment.

  In step 300, the output value of the IMU 202 (eg, acceleration in the three-axis direction and angular velocity about the three axes) is sampled. The output value of the IMU 202 may be corrected based on the INS correction value η estimated by the Kalman filter 120 in step 350 described later. That is, the bias or drift error of the output value of the IMU 202 may be corrected.

  In step 310, the inertial navigation positioning apparatus 200 derives the estimated vehicle position, estimated vehicle speed, posture, and the like based on the output value of the IMU obtained in step 300.

In step 320, the Kalman filter 120 performs time update of the Kalman filter 120. The time update of the Kalman filter 120 is expressed as follows, for example.
η (t _n ) ⁽⁻⁾ = η (t _n−1 ) ⁽⁺⁾ + u (t _n−1 )
P (t _n ) ⁽⁻⁾ = F · P (t _n−1 ) ⁽⁺⁾ · F ^T + Γ · Q (t _n−1 ) · Γ ^T
P is a covariance matrix of prediction / estimation errors, and Q is a covariance matrix (positive definite symmetric matrix) of disturbance w. Symbols (+) and (-) represent before and after the update.

In step 330, an observation matrix H (t _n ) is calculated based on the observation amount z (t _n ) of the current cycle (t _n ).

In step 340, the Kalman gain _Kk is calculated as follows.
^{_{K (t n) = P (}} t n) (-) · H T (t n) · (H (t n) · P (t n) (-) · H T (t n) + R (t n)) ^-1
Here, R (t _n ) is a dispersion matrix of observation noise. R (t _n ) is generated by the error variance correction unit 140 and is as follows.
R (t _n ) = M _k (t _n ) · W _k (t _n )
Here, M _k (t _n ) is a distributed update matrix with zero off-diagonal components, and the default is a unit matrix. The diagonal component of the distributed update matrix M _k (t _n ) is the distributed update gain, which will be described in detail later. W _k (t _n ) is a matrix with zero off-diagonal components, and each component of error variance (latitude component, longitude component, altitude component) calculated by the satellite navigation positioning device 110 is included in the diagonal component. Assigned.

In step 350, based on the Kalman gain K (t _n ) obtained in step 340, the state quantity η (t _n ) is calculated as follows.
η (t _n ) ⁽⁺⁾ = η (t _n ) ⁽⁻⁾ + K (t _n ) · (z (t _n ) −H (t _n ) · η (t _n ) ⁽⁻⁾ )
In step 360, error correction is performed based on the state quantity η (t _n ) derived in step 350 described above. That is, bias correction and drift correction of the output value of the IMU 202 are performed, and the inertial navigation positioning device 200 corrects the estimated vehicle position r (INS), estimated vehicle speed V (INS), and attitude. As a result, the estimated vehicle position and the like after error correction are obtained as the final positioning result (GPS / INS cooperative positioning result) of the current cycle. Note that the processing in steps 300 to 370 described above may be repeatedly executed based on the output value of the IMU 202 in that cycle until, for example, the state quantity η (t _n ) converges. Also, the scaling factor (vehicle model) of the wheel speed sensor 132 may be corrected based on the estimated value of the tire radius error δs included in the state quantity η (t _n ).

In step 370, the covariance matrix P is updated as follows based on the Kalman gain K (t _n ) obtained in step 340 above.
P (t _n ) ⁽⁺⁾ = P (t _n ) ⁽⁻⁾ −K (t _n ) · H (t _n ) · P (t _n ) ⁽⁻⁾
FIG. 3 is a flowchart showing the main processing realized by the vehicle positioning system 100 of the present embodiment.

  In step 400, the error variance correction unit 140 determines whether the number of satellites (captured satellites) received by the GPS receiver of the satellite navigation positioning device 110 is equal to or greater than a predetermined number. The predetermined number is a number sufficiently larger than the minimum number of satellites necessary for positioning by the satellite navigation positioning device 110, and may be a number in the range of 8 to 10, for example. Even if it can be determined that the vehicle is present in an area where there are no radio wave obstacles such as intersections or low-rise urban areas based on map data, the number of captured satellites is estimated to be greater than or equal to a predetermined number. Good. Or conversely, when it can be determined that the vehicle exists in an area where a high-rise building or the like stands, the number of captured satellites may be estimated to be less than a predetermined number. If the number of captured satellites is equal to or greater than the predetermined number, the process proceeds to step 402. If the number of captured satellites is less than the predetermined number, the process proceeds to step 408. Even if the number of captured satellites is less than the predetermined number, if the number of captured satellites is less than the minimum number of satellites (for example, 4) required for positioning by the satellite navigation positioning device 110, the error variance of the current cycle cannot be obtained. This cycle of processing ends. In other words, if the number of captured satellites is less than the predetermined number and the number of captured satellites is equal to or greater than the minimum number of satellites necessary for positioning by the satellite navigation positioning device 110, the process proceeds to step 408.

  In Step 402, the error variance correction unit 140 sets the flag Flag for the current cycle to ON.

In step 404, when the flag Flag_old of the previous cycle is OFF, the error variance correction unit 140 resets the variance update matrix M _k (t _n ) of the current cycle (t _n ) to a unit matrix. In this case, the observation noise variance matrix R (t _n ) is a matrix W _k (t _n ) based on the error variance input from the satellite navigation positioning device 110 in the current cycle. That is, the error variance input from the satellite navigation positioning device 110 in the current cycle is not substantially corrected.

In step 406, in the inertial navigation positioning device 200 and the Kalman filter 120, the vehicle position is determined using the distributed update matrix M _k (t _n ) generated in step 404 according to the positioning calculation process in FIG. Is done. That is, the vehicle position is measured using the matrix W _k (t _n ) based on the error variance input from the satellite navigation positioning device 110 in the current cycle as the observation noise variance matrix R (t _n ). The vehicle position obtained as a result (GPS / INS cooperative positioning result) is used as a base point for future positioning. Here, when there are more than a predetermined number of captured satellites continuously for a plurality of cycles, the vehicle position measured with a cycle in which the error variance input from the satellite navigation positioning device 110 is minimized (minimum) is used as a base point. Also good. For example, the time required for passing the intersection is predicted from the vehicle speed at the time of passing the intersection and the map data of the intersection (map data indicating the size of the intersection, etc.), and a buffer corresponding to the predicted passing time is created. Then, the error variance (vehicle position error variance) input from the satellite navigation positioning device 110 in each cycle during the predicted transit time and the GPS / INS cooperative positioning result obtained in each cycle during the forecast transit time are saved as needed. The error variance is filtered. When it is determined that the vehicle has reached the end of the intersection (by comparing the GPS / INS coordinated positioning result with the map data, etc.), the GPS / INS coordinated positioning result related to the cycle in which the error variance is minimized from the buffer. It may be extracted and used as a base point.

  In step 408, the error flag correction unit 140 sets the flag for the current cycle to OFF.

In step 410, the error variance correction unit 140 multiplies the error variance W _k (t _n ) input from the satellite navigation positioning device 110 in the current cycle by the variance update matrix M _k (t _n ) to reduce the observation noise. A variance matrix R (t _n ) is generated. That is, the error variance input from the satellite navigation positioning device 110 in the current cycle is substantially corrected. Then, in the inertial navigation positioning device 200 and the Kalman filter 120, the vehicle position is measured according to the positioning calculation process of FIG. 2 described above, using the observation noise variance matrix R (t _n ) generated by the error variance correction unit 140. The That is, a matrix obtained by multiplying the error variance input from the satellite navigation positioning device 110 in the current cycle by the variance update matrix M _k (t _n ) is used as the observation noise variance matrix R (t _n ), and the vehicle position ( GPS / INS cooperative positioning result) is measured.

  In step 412, when the flag Flag_old in the previous cycle is on, the error variance correction unit 140 sets the vehicle position (GPS / INS cooperative positioning result) obtained in step 406 in the previous cycle as a base point. .

  In step 414, the error variance correction unit 140 supplies the information about the base point together with the GPS / INS coordinated positioning result obtained in step 404 or 410 to the vehicle model 130, or in a memory accessible by the vehicle model 130. Saved. In addition, the flag Flag_old is updated. That is, in preparation for the next cycle processing, the flag Flag_old is updated as the flag Flag of the current cycle.

  In step 416, the error variance correction unit 140 determines whether or not the flag Flag for the current cycle is on. If the flag for the current cycle is on, that is, if the number of captured satellites for the current cycle is greater than or equal to a predetermined number, the processing for the current cycle ends. In this case, the vehicle position obtained in step 404 is supplied to, for example, a navigation device (not shown) as a final positioning result (GPS / INS cooperative positioning result) of the current cycle. On the other hand, when the flag for the current cycle is OFF, that is, when the number of captured satellites for the current cycle is less than the predetermined number, the process proceeds to step 418.

  In step 418, in the vehicle model 130, the vehicle position is estimated using the base point set in step 412 above. For example, the vehicle position in the current cycle is estimated based on the position (known) of the base point and the amount and direction of movement from the base point. For estimation of the vehicle position, instead of or in addition to the vehicle model 130, it is obtained from map data of the navigation device, imaging data of the in-vehicle camera, data obtained by inter-vehicle communication, and various facilities (infrastructure) installed on the roadside. Data or the like may be used.

  In Step 420, the error variance correction unit 140 calculates the difference abs (dφ) and the longitude component of the latitude component between the GPS / INS cooperative positioning result obtained in Step 410 and the estimated vehicle position obtained in Step 418. The difference abs (dλ) is calculated. In addition to this, a difference (dh) between altitude components may be calculated.

In step 422, the variance update matrix M _k (t _n ) is set in the error variance correction unit 140 according to the difference abs (dφ) and the lateral difference abs (dλ) obtained in step 420. The For example, the diagonal component of the dispersion update matrix M _k (t _n ) relating to the vehicle position ((error dispersion of vehicle position), that is, the dispersion update gain is (1 + K _φ · abs (dφ), 1 + K _λ · abs (dλ 1 + K _h · abs (dh)) If the difference (dh) in the altitude component is not calculated in the above step 420, the variance update gain is (1 + K _φ · abs (dφ)). 1 + K _λ · abs (dλ), 1) where K _φ , K _λ and K _h represent predetermined coefficients (gains), which may be fixed values or variable values. The dispersion updating gain obtained in this way is reflected in the processing of step 410. As a result, the estimated vehicle position after error correction is the final positioning result of this cycle ( GPS / INS cooperative positioning result) The processing in steps 410, 420, and 422 may be repeatedly executed based on the observed amount z and error variance of the cycle until, for example, each difference (and thus the variance update gain) converges. The obtained positioning result (GPS / INS cooperative positioning result) in the final cycle is supplied to a navigation device (not shown), for example.

  FIG. 4 is a plan view schematically showing a road environment in which a vehicle moves, showing an example of a typical scene in which the process of FIG. 3 is executed. In FIG. 4, a black circle mark represents a base point (see steps 406 and 412 in FIG. 3), and a cross mark represents an estimated vehicle position estimated based on the base point by the vehicle model 130 (see step 418 in FIG. 3). The black triangle mark represents the GPS / INS cooperative positioning result (see step 410 in FIG. 3). In the road environment shown in FIG. 4, high-rise buildings stand at each corner of the intersection. Here, when the vehicle is located at the intersection (the position of the solid line in the figure), the number of captured satellites exceeds a predetermined number, and accordingly, the base point is calculated and set, and after the vehicle passes the intersection (the dotted line in the figure) After the position), the number of captured satellites will be less than a predetermined number. Also, the vertical direction in FIG. 4 is the latitude direction (substantially corresponding to the north-south direction), and the left-right direction in FIG. 4 is the longitude direction (substantially corresponding to the east-west direction). Further, in FIG. 4, for comparison, a region representing the error variance corrected by the present embodiment and a region representing the error variance not corrected are schematically shown as elliptical regions.

In the example of FIG. 4, after the vehicle passes the intersection, the difference between the GPS / INS cooperative positioning result and the estimated vehicle position gradually increases. At this time, the difference abs (dλ) of the longitude component becomes the difference abs of the latitude component. It is larger than (dφ). In this case, in this embodiment, the dispersion update gain related to the longitude component is corrected to be larger than the dispersion update gain related to the latitude component. That is, the correction ratio of the dispersion update gain related to the longitude component is larger than the correction ratio of the dispersion update gain related to the latitude component. Therefore, if K _φ and K _λ have the same value, the dispersion update gain related to the longitude component is larger than the dispersion update gain related to the latitude component. As described above, according to the present embodiment, the difference between the GPS / INS coordinated positioning result and the estimated vehicle position is decomposed into the latitude direction and the longitude direction (alternatively the altitude direction), and based on the difference between the directions. Thus, the error variance (vehicle location error variance) input from the satellite navigation positioning device 110 can be corrected to an appropriate value.

  In this embodiment, as described above, the difference between the GPS / INS cooperative positioning result and the estimated vehicle position is decomposed into the latitude direction and the longitude direction (altitude direction selectively). You may disassemble in the direction. For example, the difference between the GPS / INS cooperative positioning result and the estimated vehicle position may be decomposed in the vehicle traveling direction (or front-rear direction) and the lateral direction. That is, when the GPS / INS coordinated positioning result and the estimated vehicle position are calculated in, for example, a fixed earth coordinate system based on WGS84, the difference abs (dx) in the traveling direction of the vehicle and the difference abs (dy) in the lateral direction May be calculated instead of the difference abs (dφ) of the latitude component and the difference abs (dλ) of the longitude component. Similarly, the difference abs (dz) in the vertical direction of the vehicle may be calculated instead of the difference (dh) in the altitude component.

FIG. 5 is a flowchart showing an example of the variable setting process of the above-described variance update gain coefficients K _φ and K _λ by the error variance correction unit 140. FIG. 6 is an explanatory diagram of FIG. 5 and shows distance threshold values in the latitude direction and the longitude direction.

  Referring to FIG. 5, in step 500, the radio field intensity is equal to or greater than a predetermined threshold based on the information on the radio field intensity and satellite position of each GPS satellite received by the satellite navigation positioning device 110, and the position in the latitude direction The number C1 of GPS satellites within the predetermined threshold distance (latitude direction threshold distance) is calculated. The information on the satellite position may be based on satellite orbit information (ephemeris or almanac) included in the navigation message. Here, the latitude threshold distance may be a distance (range) having a certain width with reference to the latitude direction, as shown in FIG.

  In step 502, similarly, based on the information on the radio wave intensity and the satellite position of each GPS satellite received by the satellite navigation positioning device 110, the radio wave intensity is equal to or greater than a predetermined threshold, and the position in the longitude direction is a predetermined threshold distance. The number C2 of GPS satellites within the range is calculated. Here, as shown in FIG. 6, the longitude direction threshold distance may be a distance (range) having a certain width with respect to the longitude direction.

  In step 504, the number of satellites C1 calculated in step 500 is compared with the number of satellites C2 calculated in step 502. If C1-C2 is larger than the predetermined satellite number threshold, the process proceeds to step 506. . Note that the satellite number threshold value may represent a relatively significant difference of, for example, 5 or more.

  In step 506, since C1-C2 is larger than a predetermined satellite number threshold value, it is determined that the radio wave condition is good in the latitude direction.

In step 508, the radio wave condition in the latitudinal direction is good, and set small coefficient K _phi of distributed update gain according to the latitudinal direction, the correction ratio of the error variance of the latitudinal direction (the error variance of the vehicle position) is small Is done. This is because the total position dispersion when N GPS satellites having the same positioning dispersion σ ² can be observed can be expressed by σ ² / (N−1), and the dispersion decreases as N increases. is there. That is, for example, when the number of GPS satellites that can be observed in the latitude direction is larger than the number of GPS satellites that can be observed in the longitude direction, the positional dispersion in the latitude direction becomes small.

Note that the flowchart of FIG. 5 relates to the process of reducing the correction ratio of the error variance in the latitude direction, but the same applies to the process of reducing the correction ratio of the error variance in the longitude direction. That is, when C2-C1 is greater than the predetermined satellite number threshold, determines that the radio wave condition in the longitudinal direction is good, and set small coefficient K _lambda of distributed update gain according to the longitude, the longitude The correction ratio of the error variance (vehicle position error variance) may be reduced. If | C1-C2 | is smaller than the satellite number threshold value, the coefficients K _φ and K _λ of the dispersion updating gains may be maintained at predetermined default values.

The processing shown in FIG. 5 relates to a method for setting the coefficients K _φ and K _λ of the dispersion updating gain used in step 422 of the above-described processing of FIG. 3, but is independent of the processing of FIG. May be realized. For example, the variance update gain may be (1 + K _φ , 1 + K _λ , 1 + K _h ), and the difference abs (dφ) or the like may not be calculated. In this case, for example, when the radio wave condition is good in the latitude direction, by setting the coefficient K _φ of the dispersion updating gain to be small (for example, by setting the coefficient K _φ to zero), the error variance in the latitude direction can be reduced. The correction ratio may be reduced.

  In the above-described embodiment, the “correction means” in the appended claims is realized by the error variance correction unit 140 and the vehicle model 130, and the “moving body position estimation means” in the claims is: This is realized by the vehicle model 130.

  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, an example in which the present invention is applied to the GPS has been shown. However, the present invention can also be applied to a satellite system below the GPS, for example, another GNSS (Global Navigation Satellite System) such as Galileo. is there.

1 is a system configuration diagram showing a vehicle positioning system 100 including an embodiment of a mobile positioning device according to the present invention. It is a flowchart which shows the positioning calculation process implement | achieved by the vehicle position positioning system 100 of a present Example. It is a flowchart which shows the main processes implement | achieved by the vehicle position positioning system 100 of a present Example. It is explanatory drawing of the process of FIG. 10 is a flowchart illustrating an example of a variable setting process of variance updating gain coefficients K _φ and K _λ by an error variance correction unit 140. It is explanatory drawing of the process of FIG.

Explanation of symbols

DESCRIPTION OF SYMBOLS 100 Vehicle positioning system 110 Satellite navigation positioning apparatus 120 Kalman filter 130 Vehicle model 140 Error dispersion correction part 200 Inertial navigation positioning apparatus

Claims (8)

In a mobile positioning device that is mounted on a mobile body and measures the position of the mobile body,
Inertial navigation positioning means for positioning the position of the moving body by inertial navigation;
Satellite navigation positioning means for positioning the position of the moving body by satellite navigation;
The relationship between the positioning result of the satellite navigation positioning means and the positioning result of the inertial navigation positioning means is an observation amount, the correction parameter used in the inertial navigation positioning means is a state quantity, and the error of the positioning result of the satellite navigation positioning means State quantity estimation means for estimating the state quantity using variance;
Means for reflecting the state quantity estimated by the state quantity estimating means in the positioning of the inertial navigation positioning means;
A mobile positioning apparatus comprising: correction means for correcting the error variance according to a reception state of satellite radio waves received by the mobile body.   The correction means does not correct the error variance when a predetermined number or more of satellites are acquired, and corrects the error variance when less than a predetermined number of satellites are acquired. Positioning device for mobile objects.   The correction means uses the position of the moving body measured by the inertial navigation positioning means at a period corresponding to an observation period in which a predetermined number or more of satellites are captured as a base point for movement to estimate the position of the subsequent moving body Comparing the estimated position of the moving object estimated by the moving object position estimating means with the positioning position of the moving object measured by the inertial navigation positioning means at a period corresponding to the estimated position. The mobile positioning device according to claim 1, wherein the error variance is corrected based on the comparison result.   The said mobile body position estimation means is a positioning apparatus for mobile bodies of Claim 3 which estimates the position of the said mobile body of the period corresponding to the observation period when less than the predetermined number of satellites were acquired.   The correction means derives a difference between the estimated position and the positioning position using at least two orthogonal direction components, and based on the derived difference between the direction components, the error variance relating to each corresponding direction component is calculated. The mobile positioning device according to claim 3 or 4, wherein correction is performed.   The correction means corrects the error variance in a direction in which the error variance increases at a higher rate when the derived difference is large than when the derived difference is small. Positioning device for mobile objects.   The correction means derives an index value indicating the reception state of the satellite radio wave in at least two orthogonal directions based on the reception result of the satellite radio wave, and corresponding each of the corresponding values based on the derived index value of each direction component The positioning device for a moving body according to any one of claims 1 to 6, wherein the error variance related to the direction component is corrected.   8. The mobile positioning apparatus according to claim 7, wherein the index value is based on the number of satellites existing within a predetermined range with respect to each direction and the reception intensity of satellite radio waves from each satellite in the mobile body.

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