JPH10111137A - GPS navigation device - Google Patents

Abstract

(57) [Summary] [Problem] To provide a GPS navigation device that can detect gradient information accurately and inexpensively without a dedicated sensor, and can improve location accuracy and route guidance performance. A pseudorange change rate output from a GPS receiver, other satellite information, and a gyro sensor are provided.
The gradient of the moving direction of the moving object is calculated from the moving direction of the moving object measured using 0 and the speed of the moving object measured by the vehicle speed sensor 312. Further, the gradient data is added to the road link information based on the gradient data. If there is no, add it.If there is, improve the position detection accuracy by matching the information by map matching process.In addition, the gradient data is used for bird's-eye view display on the map display screen, making the display more intuitive Make it easy to understand.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a GPS (Global Positioning System) device provided on a moving body and various sensors for detecting the movement of the moving body and combining the detected signals to obtain the position of the moving body. The present invention relates to a GPS navigation device that can improve the accuracy of information and the like.

[0002]

2. Description of the Related Art There is a GPS positioning device as one of the positioning devices. This GPS positioning device usually receives signals from three or more GPS satellites simultaneously, and generates pseudorange data including the time offset of the GPS receiver between each GPS satellite and a receiving point, and position data of each GPS satellite. Thus, the position of the receiving point is calculated.

A conventional GPS navigation device uses this GPS positioning device. The calculated position of a receiving point, for example, the current position of a moving object equipped with the GPS navigation device is displayed on a map around the position. Is displayed superimposed on.

Further, in recent years, a GPS navigation device having a route guidance function for automatically guiding a route according to a destination of an input moving object has been proposed.

[0005]

However, the conventional GPS
In the navigation device, in order to receive the GPS satellite signal on the ground, the GPS satellite must be above the horizon as viewed from the receiving point. That is, the receivable G
The arrangement of PS satellites will always be limited to a spatially biased range. This means that the error in the vertical direction is larger than the error in the horizontal direction when viewed from the receiving point according to the principle of the survey.

[0006] That is, the latitude, longitude, and altitude output from the GPS receiver included in the conventional GPS navigation apparatus show a greater measurement error in altitude than the latitude and longitude. The measurement error in the component in the vertical direction increases as compared with the azimuth and speed of. Therefore, for example, it is difficult to accurately grasp a moving state accompanied by an increase or decrease in altitude.

On the other hand, as one of the GPS navigation devices, there is a car navigation system for measuring the current position of an automobile. Also in the map information used when displaying the positioning result in this car navigation system, priority is given to the accuracy in the plane direction. That is, there is no vertical altitude information, or even if there is, it is topographical information and does not always coincide with the altitude or gradient of the road on which an automobile or the like actually runs.

As described above, the vertical component has been neglected in both the measurement and display of the position in the GPS navigation device, and the following problems have occurred.

On the measurement side, if there is a road directly below an elevated road, there is a problem that it is difficult to distinguish which road is running. This greatly affects the performance of the route guidance function provided in the conventional car navigation system, in which the guidance content needs to be changed depending on whether the vehicle is on the upper or lower road. Further, even when the upper and lower roads are displaced in a plane, there is another problem that unless the information in the vertical direction is used, which road is located can be identified only to the level of the measurement accuracy in the plane direction.

On the other hand, on the display surface, there is a three-dimensional display (pseudo) as a display method closer to the actual running state, but as described above, when there is no altitude information, or when altitude information is present, it is limited to topographic map information. In such a case, it is difficult to display a realistic three-dimensional display.

The present invention has been made in view of the above-mentioned problems, and can accurately detect information on a change in the vertical direction of a moving body, that is, so-called gradient information, without using a dedicated sensor therefor. It is an object to provide a GPS navigation device. Also, by obtaining the above-mentioned gradient information, a GP that enables distinction between an elevated road and a road under the elevated road and enables a more realistic three-dimensional display.
It is an object of the present invention to provide an S navigation device.

[0012]

In order to achieve the above object, the present invention provides a GPS navigation device, comprising:
Pseudo-distance change rate measuring means for measuring a pseudo-distance change rate for each GPS satellite from the S signal, and moving body speed / azimuth measuring means for measuring at least one of the speed and the direction of the moving body without using a GPS signal The mobile object position determined by the GPS positioning means, the satellite information on at least one receivable GPS satellite obtained by the satellite information obtaining means, and the satellite information on the at least one receivable GPS satellite. From the pseudo distance change rate obtained by the pseudo distance change rate measuring means and at least one of the speed and direction of the moving body measured by the moving body speed / azimuth measuring means, the speed vector of the moving body from the horizontal plane is calculated. A moving body velocity vector gradient calculating means for calculating an angle (hereinafter, referred to as a gradient);

[0013] In the present invention, the gradient information obtained from the moving body velocity vector gradient calculating means is used as the G information.
It may be configured to further include a gradient information transmitting unit that notifies a user of the PS navigation device.

Further, in the above-mentioned present invention, there is further provided a display means for displaying the current position of the determined moving body, wherein the gradient information transmitting means corresponds to the schematically displayed moving body corresponding to the gradient amount. A configuration in which the state of being tilted by an amount is displayed on the display means to notify the user is also possible.

In the present invention, a storage means for storing map data including gradient information on each road on which the moving body moves, gradient information obtained from the moving body velocity vector gradient calculating means, A configuration may also be provided that further includes a moving object position estimating means for estimating the position of the moving object based on the degree of matching with the information of the map data corresponding to the gradient information.

In the present invention, when the map data is stored in the storage means so that the gradient information contained therein can be rewritten or added, the moving object velocity vector gradient calculation is performed. Means may be provided for collating the gradient information obtained from the means with the corresponding information of the map data, and performing correction or addition according to the degree of the collation.

Further, in the present invention, image data for displaying a predetermined display mark indicating the estimated position of the moving object on a map image based on map data of a predetermined range area including the position is displayed. And display means for displaying the generated image data, wherein the map image in the image data has a gradient corresponding to the gradient information contained in the map data. It may be configured to include the image shown.

In the present invention, the receivable G
When there are a plurality of PS satellites, at least one of the plurality of GPS satellites used in the processing by the moving object velocity vector gradient calculating means is selected according to a predetermined selection criterion.
A satellite selecting means for selecting one of the GPS satellites is provided to preferentially select a satellite having a large elevation angle of the satellite position, or a satellite having an azimuth angle of the satellite position closer to the traveling direction of the moving object or 180 degrees opposite thereto. May be preferentially selected.

In the present invention, when two or more GPS satellites are selected, the moving object velocity vector gradient calculating means calculates a gradient value for each of the selected two or more GPS satellites. Then, the gradient of the velocity vector of the moving object may be obtained by simply averaging these gradient values or by averaging using a weight assigned according to the satellite position.

In the present invention, the moving body speed / azimuth measuring means may be a vehicle speed sensor for measuring a rotation state of wheels of the automobile, or a gyro for detecting a rotational angular velocity caused by a change in the moving azimuth of the moving body. It may be configured to include a sensor and a means for determining the moving direction using at least one of the road link directions in the map data.

Further, in the present invention, the moving body is an automobile, and the moving body speed / azimuth measuring means has a vehicle speed sensor for measuring a rotation state of wheels of the automobile and a gyro sensor for detecting a rotational angular velocity. When the speed and the direction of the moving object are measured by these sensors, the moving object speed vector gradient calculating means is configured to detect each GPS signal.
For a satellite, from the mobile object position and the satellite information,
The elevation angle and azimuth angle of the satellite measured in the coordinate system with the position of the moving object as the origin are obtained, and the line-of-sight component from the moving object to the satellite in the velocity vector of the satellite is calculated, and the obtained elevation angle of the satellite is obtained. And the azimuth angle, the line-of-sight component of the calculated satellite speed vector, the measured speed and azimuth of the moving object, and the measured pseudorange change rate, to calculate the gradient of the moving object speed vector. It is good also as composition.

[0022]

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS Hereinafter, embodiments of a GPS navigation device to which the present invention is applied will be described with reference to the drawings. In the following embodiments, it is assumed that the GPS navigation device is mounted on a moving object that moves on the ground surface such as an automobile.

A first embodiment of a GPS navigation device to which the present invention is applied is a navigation device for a car, and as a hardware configuration, for example, as shown in FIG. 2, a GPS radio signal from a GPS satellite is used. Antenna unit 302 including antenna for receiving, antenna unit 302
A GPS receiver 304 that performs positioning of a receiving point (hereinafter, referred to as a current position or position of a moving object) or a pseudo-range change rate measurement from a reception signal output from the GPS receiver 304, and an output result from the GPS receiver 304 A controller 300 implemented by an arithmetic processing circuit such as a microcomputer, for example, that calculates a moving speed vector of the moving body to estimate the position of the moving body and controls peripheral devices.

The apparatus according to the present embodiment further includes a gyro sensor 31 for detecting an amount of change in direction (rotational angular velocity) of the moving body.
0, the map memory 306 for storing road map data using a CD-ROM or the like, and the current position of the moving object estimated by the controller 300 is displayed to the user by superimposing it on the peripheral map read from the map memory 306. Yes, CRT
And a display device 308 including a liquid crystal display.

The gyro sensor 310 measures the rotational angular velocity of a rotational motion caused by a change in the traveling direction of a moving body to which the sensor is attached without measuring the terrestrial magnetism. It is composed of a gyro. Also, the map memory 306
Is a DVD-R as described in a third embodiment described later.
It may be constituted by a rewritable memory such as AM.

The apparatus according to the present embodiment further has a vehicle speed sensor 312 for detecting the moving speed of the moving body by, for example, measuring the rotation state of the wheels of the moving body. In the case where the vehicle body, which is a moving body, is provided with a means for detecting information on vehicle speed, instead of newly providing a vehicle speed sensor 312, a means for obtaining the vehicle speed information may be provided. . In any case, as described later, in order to obtain gradient information with higher precision, about several percent of a wheel speed sensor that is normally used as a vehicle speed sensor 312 and that detects a rotation speed of a tire of an automobile is used. Speed information that can achieve accuracy is desirable.

Next, each component in the present embodiment will be described in detail with reference to FIG.

In this embodiment, the antenna section 302
As shown in FIG. 1, among the GPS signals from a plurality of GPS satellites received by the antenna 4a and the GPS signal received by the antenna 4a,
And a radio wave receiving unit 4 for selecting and outputting only a signal.

Based on the output signal from the radio wave receiving unit 4, the GPS receiver 304 generates a pseudo-range corresponding to the temporal change rate of the pseudo-range between the GPS satellite 2 corresponding to the received GPS signal and the moving object. It has a pseudo distance change rate measuring unit 8 that measures the distance change rate for each GPS satellite.

The pseudo distance change rate measuring unit 8 is, for example, a GP.
By measuring the Doppler frequency of the carrier of the GPS signal, which is changing due to the Doppler effect corresponding to the relative speed between the S satellite and the moving object, and comparing the measured value with a known transmission frequency of the carrier, The pseudorange change rate is measured.

The GPS receiver 304 further includes satellite information relating to the orbit of a GPS satellite corresponding to the received GPS signal, and GPS information, similarly to a known GPS positioning device.
From the satellite information and the pseudo distance measuring unit 9 for measuring the pseudo distance (range) information between the PS satellite and the mobile object, respectively, and from the result measured by the measuring unit 9, when the normal positioning is possible (for example, the reception is possible) (When the number of GPS satellites is 3 or more),
G that measures the current position of a moving object by performing known GPS positioning
From the results measured by the PS positioning unit 7 and the pseudo distance change rate measurement unit 8, a speed vector calculation unit 6 that calculates the speed vector of the moving object, and a DOP (Dilu as an index of positioning accuracy)
and a measurement section (not shown) of the measurement of Precision.

In this embodiment, the antenna unit 302
The radio wave receiving unit 4 selects only the GPS signal whose signal strength is equal to or more than a predetermined value and transmits the selected signal to each of the units 8 and 9 included in the GPS receiver 304. The configuration of the GPS receiver 304 is not limited to this. Instead of such a configuration,
For example, the radio wave receiving unit 4 amplifies all the received signals and
The GPS signal transmitted to the PS receiver 304 and determined to be in a good reception state may be transmitted to the pseudorange change rate measuring unit 8 and the satellite information and pseudorange measuring unit 9.

The controller 300 has a satellite selection unit 10 for selecting a satellite to be used for calculating the gradient of the moving object in accordance with the satellite information and the reception state of the GPS signal obtained by the pseudorange measurement unit 9. The mobile object direction estimating unit 14 that obtains the pseudorange change rate of the satellite selected by the satellite selecting unit 10 from the measurement result of the measuring unit 8 and separately estimates the mobile object direction, and the mobile object speed estimating unit that estimates the mobile object speed 16, a moving body speed vector gradient calculating unit 12 that calculates the gradient of the moving direction of the moving body by combining information from the moving body direction estimating unit 14 and the moving body speed estimating unit 16, and a moving body speed vector gradient calculating unit 12 The mobile object position estimating unit 18 that estimates the position of the mobile object by comprehensively evaluating the information of the mobile object direction estimating unit 14, the mobile object speed estimating unit 16, the GPS positioning unit 7, and the map memory 306. To.

The controller 300 further generates image data for displaying a map of the moving object position estimated by the moving object position estimating unit 18 and an area including the moving object position, and sends the image data to the display device 308. Having.

When there are a plurality of satellites that can be applied to the calculation processing by the moving object velocity vector gradient calculation unit 12, the satellite selection unit 10 selects one or a plurality of satellites based on a predetermined reference. For example, the satellite having the larger elevation angle data of the satellite information and the satellite information obtained by the pseudo distance measuring unit 9 is preferentially selected. Alternatively, a satellite whose azimuth data of the satellite information is closer to the traveling direction of the moving object or the opposite direction may be preferentially selected. When selecting, the satellite selection unit 10 does not necessarily need to select one from a plurality of applicable satellites, and based on the elevation data and azimuth data as described above, An average gradient may be obtained in a weighted form by a gradient calculation method described later. A detailed selection method will be described later.

The moving object velocity vector gradient calculating section 12 obtains the pseudo distance change rate of the satellite selected by the satellite selecting section 10 from the pseudo distance change rate measuring section 8 and moves the pseudo distance change rate information separately. Moving body direction estimating unit 1 for estimating body direction
4 and information from the moving object speed estimating unit 16 for estimating the moving object speed, the gradient of the moving direction of the moving object is calculated by a method described later. A detailed gradient calculation method will be described later.

The azimuth estimation unit 14 determines the rotation angle of the gantry from the final azimuth (the most recent azimuth) determined by the velocity vector calculation unit 6 when the normal positioning is possible. The angular velocity measured in 310 is obtained by integrating over time, and the traveling direction of the moving object is calculated by adding the obtained rotational angle and the final direction.

The moving body speed estimating section 16 calculates the vehicle speed by measuring the traveling distance per unit time from the tire rotation rate by the vehicle speed sensor 312 for measuring the rotation of the wheels of the moving body.

The moving object position estimating unit 18 is preset by sequentially connecting and time integrating the moving object speed vectors obtained by the moving object direction estimating unit 14 and the moving object speed estimating unit 16. The moving position of the moving body from the initial position is obtained, and the position data, the gradient value output from the gradient calculating unit 12 and the position data output from the GPS positioning unit 7 are obtained.
The position of the moving object is comprehensively estimated by collating with the information in the map memory 306.

The display processing unit 22 reads out the obtained peripheral map information of the current position of the moving object from the map memory 306, generates image data for superimposing and displaying them, and sends it to the display device 308. .

Next, one of the characteristic constitutions of the present invention,
The principle of gradient calculation in the moving body velocity vector gradient calculation unit 12 will be described with reference to FIGS.

Normally, the pseudorange (range) ρ between the GPS satellites 2 arranged as shown in FIG. 3 and the current position (reception point) of the mobile unit 210 is given by the following equation.

[0043]

(Equation 1)

Here, B is a time offset between the clock of the GPS receiver 304 and the clock of the GPS satellite 2, and x, y, and z are coordinate values in a predetermined coordinate system indicating the current position (reception position) of the moving object. , U, V, W are coordinate values in the coordinate system indicating the satellite positions.

In normal positioning, the above equation (1) can be made as many as the number of receivable GPS satellites, and U, V, and W are known from satellite information (almanac data or ephemeris data) included in the satellite signal itself. , Pseudo distance ρ
Can be measured from the clock difference at the time of transmission of the received GPS signal radio wave.

Therefore, the GP from four GPS satellites
The four unknowns x, y, z, and B can be obtained by receiving the S signal and solving the four equations formed by setting the above equation 1 as simultaneous equations for each GPS signal. This is called three-dimensional normal positioning.

In the above coordinate system, if the coordinates (for example, z) in the height direction of the moving object are known on the earth's surface, the position can be specified based on information of three GPS satellites.
This is what is called two-dimensional normal positioning.

Next, a method for calculating the velocity vector of the moving body based on the position of the moving body calculated in this manner will be described.

The pseudorange change rate ρ obtained by integrating the above equation 1 with time.
The dot (hereinafter, the time derivative of the variable is referred to as “dot”) is given by the following equation.

[0050]

(Equation 2)

The above equation (2) is applied to a GPS capable of receiving a GPS signal.
Simultaneously the number of satellites, x dots, y dots, z dots,
Solve B dots as unknowns. At this time, x, y, z, and B in Equation 2 substitute the solution of Equation 1 above. Also, U
The dots, V dots, and W dots are known from satellite information included in the GPS signal. The ρ dot is, for example, G
It can be obtained by measuring the Doppler frequency of the transmission wave of the PS signal.

Also here, since the moving body moves on the surface of the earth, if the coordinate value in the height direction is assumed to be constant (for example, z dot = 0), it is based on the information of three GPS satellites. , A two-dimensional velocity vector of the moving object can be specified.

As described above, if the number of receivable GPS satellites is at least three or more, the speed vector calculation unit 6 uses the information on the current position of the moving object obtained by the known GPS positioning, the pseudorange change rate, and the like. Thus, the velocity vector of the moving object for expressing the motion of the moving object, that is, the vehicle speed and the traveling direction can be obtained. In addition, receivable GPS
If the number of satellites is four or more, it is also possible to calculate the moving speed in the z direction (vertical direction) although the accuracy is low, in addition to the above.

By transforming the above equation (2), the following equation (3) is obtained.
Is obtained.

[0055]

(Equation 3)

Here, as shown in FIG.
Vu 212 is the velocity vector of the satellite 2 and the moving body 210, respectively, and θs204 and θu214 are the line-of-sight direction vector 220 and the moving velocity vector V from the moving body to the satellite, respectively.
s202 and Vu212. In FIG. 3, for the sake of explanation, both movement vectors appear to exist on the paper.
There is no such restriction, and the vector is oriented in any direction.

(Ρ−B) is the actual distance 222 between the GPS satellite 2 and the receiving point 210 (moving body) as shown in FIG. , Its time derivative (ρdot−Bdot), corresponds to the Doppler shift amount in the Doppler effect.

That is, the rate of change of the actual distance between the GPS satellite 2 orbiting the earth and the moving object 210 is equal to the difference between the line-of-sight components of the velocity vectors of the two.

In FIG. 3, the positions of the satellite and the moving body are indicated by an absolute coordinate system which does not involve any of the satellite and the moving body. As shown in FIG. The coordinate system shown in FIG. 4 is defined by a three-dimensional coordinate system in which the moving body 210 is placed at the origin, the east-north direction is the X-axis and the Y-axis direction, and the height direction is the Z-axis direction. . Further, for example, a roll angle corresponding to a bank of a road does not need to be considered because it does not affect the moving body velocity vector.

In FIG. 4, the symbol β is an elevation angle which is an angle in the height direction of the GPS satellite 2, γ is a gradient which is an angle in the height direction of the moving body, and α and θ are the satellite 2 and the moving body, respectively. 2
10 represents the azimuth on the earth's surface. In addition,
The coordinate position and vector amount known in FIG. 3 can be obtained by coordinate conversion.

The cos θu of the above equation (3) is expressed in detail from the relationship shown in FIG. cosθu is the unit vector E of the user velocity vector
u:

[0062]

(Equation 4)

And the satellite gaze direction unit vector Eu-s:

[0064]

(Equation 5)

Is expressed as an inner product of

[0066]

(Equation 6)

Is obtained. Therefore, the above equation 3 becomes

[0068]

(Equation 7)

Is rewritten as

Sin γ and cos γ are series-expanded, and the assumption that the gradient γ on the path along which the mobile body moves is usually sufficiently small (10 degrees or less) is ignored, and the third and subsequent powers are ignored.
When −γ · γ / 2 is set, the following expression is obtained.

[0071]

(Equation 8)

By transforming the above equation (8),

[0073]

(Equation 9)

This is in the form of a quadratic equation relating to γ.
Here, A = cosβcos (θ−α), and represents cosθu when the gradient γ = 0. Solving this,

[0075]

(Equation 10)

Is obtained. This is the basic expression used in this embodiment for determining the gradient γ. In the equation, ± indicates that γ = 0, and if the satellite targeted by + is behind the car 210 (90 ° <θ−α <270 °), the satellite targeted by − is the car 210. (0 degree <θ-α <90
Degree, 270 degrees <θ-α <360 degrees).

In the above equation (10), the line-of-sight component Vs · cos θs of the velocity vector Vs of the GPS satellite 2, the elevation angle β and the azimuth α of the satellite 2 are obtained for the GPS satellite 2 that can be received at the present time. It is known because it can be derived from the satellite information and the latest position of the moving object already obtained at the present time.

That is, the satellite information includes information on the current position and velocity vector of the satellite. Therefore, a line-of-sight direction vector is first obtained from the satellite position information and the current position of the moving object, and Vs · cos θs can be obtained from a vector product of the line-of-sight direction vector and the satellite velocity vector. The elevation angle β and azimuth α of the satellite
Can be obtained by performing coordinate transformation from the satellite position in the absolute coordinate system shown in FIG. 3 to a coordinate system having the moving body 210 shown in FIG. 4 as an origin.

Here, the position of the moving object is estimated at a predetermined position determination cycle, and the latest moving object position obtained by the moving object position estimating section 18 at the present time can be used. That is, the GPS satellite 2 and the mobile unit 210
Is usually about 20,000 km apart, and from this positional relationship, if the accuracy of the position of the moving body 210 is on the order of several hundred meters, it is sufficient for use of the present embodiment.

The B dot, which is the rate of change of the time offset, can be calculated and known in a normal positioning state in which three or more GPS satellites can be received. Further, if the B dot is assumed to be constant and the value of the B dot calculated in the normal positioning state is used, this can also be known. This assumption of B dot constant is actually sufficient in a short time.

The traveling azimuth angle θ of the moving object is obtained by integrating the rotation angular velocity of the moving object measured by the gyro sensor 310 with time to the azimuth angle θgps obtained by the velocity vector calculating section 6 and sequentially adding the angular velocity. It can be calculated as the latest traveling direction of the moving object.

The moving speed Vu of the moving body can be obtained by measuring the traveling distance per unit time by the vehicle speed sensor 312 for measuring the rotation of the wheels of the moving body and calculating the vehicle speed. Generally speaking, compared to speed information obtained from GPS normal positioning,
The vehicle speed can be determined with higher accuracy.

In summary, regardless of whether or not normal positioning of GPS is possible, GPs from one or more GPS satellites
By receiving the S signal and measuring the pseudorange change rate ρ dot, the gradient γ in the traveling direction of the moving object can be calculated for each GPS satellite from the above equation (explicitly).

The moving body velocity vector gradient calculating section 12 of the present embodiment uses the high-precision velocity information obtained from the vehicle speed sensor 312 to calculate the gradient of the moving velocity vector from the relative relationship between the GPS satellite 2 and the moving body 210. It seeks information. According to the gradient calculation method of the present embodiment, the determination accuracy of the vertical component of the GPS velocity vector, which is difficult to obtain with high accuracy due to the characteristics of the GPS positioning, described in the above “Problems to be Solved by the Invention” It can be complemented by the high accuracy of the vehicle speed sensor 312.

Further, according to the gradient calculation method of the present embodiment, the gradient can be obtained for each GPS satellite that could receive the signal in principle. Find a high-precision gradient, or select multiple satellites within a certain range,
A plurality of gradient values obtained for these satellites can be averaged to obtain a more accurate gradient.

In the present embodiment, the case where the moving speed of the moving object can be determined with high accuracy without using the GPS satellites has been described as an example, but the present invention is not limited to this configuration. For example, when the azimuth of the moving object can be obtained with high accuracy without using the GPS satellites instead of the speed of the moving object, the inclination of the moving object is obtained using this azimuth similarly to the present embodiment. be able to. In this case, for example, the vehicle speed Vu of Formula 10 may be determined from the vehicle speed determined by the GPS satellites and the azimuth determined with high accuracy.

Next, the processing procedure in the GPS navigation device of the present embodiment will be described with reference to the flowcharts of FIGS.

The main processing procedure in this embodiment is repeated at a predetermined time period. For example, as shown in the general flow of FIG. 5, first, the GPS navigation device of this embodiment is turned on ( After step 40), a predetermined predetermined initial process (step 42) is performed. At the time of this initial processing, initial positioning by the GPS positioning unit 7 is also performed, and satellite information including the orbit information (almanac data and the like) of the GPS satellite 2 is also obtained.

In the following embodiment, it is assumed that three or more GPS satellites can be received at the time of initial positioning of the GPS receiver 304, and normal positioning using these satellites can be performed. Further, in the case where the normal positioning is not possible at the time of the initial positioning of the GPS receiver 304, the user may manually input the current position.

In step 44, the current position is determined by using the position obtained by the moving object position estimating section 18 in the previous processing according to the present processing procedure, or if there is no previous position, using the initial positioning result of the GPS positioning section 7. Set automatically.

In step 46, the display processing section 22 reads the map data of the area including the current position set above from the map memory 306, and further displays the current position of the moving object on the map indicated by the map data. The image data is generated and transmitted to the display device 308 so that the predetermined mark is displayed in a superimposed manner.

Thereafter, in step 48, the following interrupt processes 50, 60, 65 and 70 are permitted. The moving body direction calculation interrupting process 50 is a process that is performed at intervals of a predetermined time Δt, and the moving body direction estimating unit 14 estimates the direction of the moving body from the data obtained by the gyro sensor 310.

The moving object speed calculation interrupting process 60 is also a process that is performed at intervals of a predetermined time Δt, and the speed of the moving object is estimated by the moving object speed estimating section 16 from the data obtained by the vehicle speed sensor 312.

The moving object gradient calculation interrupting process 65 includes a calculation result obtained by the moving object direction calculation interrupting process 50, a calculation result obtained by the moving object speed calculation interrupting process 60, and a pseudo distance change from the GPS receiver 304. Each time the GPS receiver 304 acquires and outputs the data from the data related to the rate or the like, the moving body velocity vector gradient calculating unit 12 calculates the gradient in the traveling direction of the moving body based on the above equation (10).

In the moving body position estimating interrupt processing 70, the calculation result in the moving body direction calculation interrupt processing 50, the calculation result in the moving body speed calculation interrupt processing 60, and the moving body gradient calculation interrupt processing 65. Is compared with the result of positioning by the GPS receiver 304 and the information in the map memory 306 to estimate the current position of the moving object.

In step 52, the moving body position estimating section 18
Is further compared with the position of the moving object estimated in the moving object position estimation interrupt processing 70 and the position of the moving object set in step 44 to determine whether the current position of the moving object is moving. I do. As a result, if it is moving (Yes in step 52), the process proceeds to step 54, where the display processing unit 22 changes the display of the current position, and if necessary, updates the map. If the user has not moved (No in Step 52), the processes in and after Step 50 are repeated.

Next, a description will be given of a processing procedure of the moving body direction calculation interrupting process 50 executed by the moving body direction estimating unit 14 at regular time intervals Δt.

In this processing, as shown in FIG. 6, first, in step 55, if the number of receivable GPS satellites is three or more, calculation is made in step 80 of a moving object position estimation interruption processing 70 described later. GPS azimuth θgps and rotational angular velocity ω (= dθ / d) measured by gyro sensor 310
t). The number of GPS satellites that can be received is 3
If the number is less than the number, the GPS azimuth obtained in the moving object position estimation interrupt processing 70 is used instead of
The GPS orientation θgps obtained in the previous process is used.

In step 56, the GPS azimuth θgps is
The rotational angular velocity ω is integrated over time and added by the following equation including the predetermined correction coefficients a and b.

[0100]

Equation 11 θgps = θgps + (a × ω−b) × Δt The correction coefficients a and b are the gyro sensor 31 to be used.
This is set according to 0. For example, when it is not necessary to correct the gyro error at all, a = 1 and b = 0 may be set.

Next, the processing procedure of the moving object speed calculation interrupting process 60 executed by the moving object speed estimating section 16 every fixed time Δt will be described.

In this process, as shown in FIG. 7, first, at step 61, a difference ΔP from the previous value is calculated from the pulse count number output from the vehicle speed sensor 312 and corresponding to the rotation speed of the wheel. Further, in step 62, the velocity Vu and the distance Du are calculated by multiplying ΔP by the vehicle speed conversion coefficient F1 and the distance conversion coefficient F2, respectively, using the following equation.
Is calculated.

[0103]

Vu = F1.times..DELTA.P / .DELTA.t Du = F2.times..DELTA.P Next, a description will be given of a processing procedure of the moving body gradient calculation interrupt processing 65 executed by the moving body velocity vector gradient calculating section 12 at regular time intervals .DELTA.t. I do.

In this processing, as shown in FIG. 8, the latest movement first known at that time in step 651, for example, the latest movement obtained by the previous processing of the moving body position estimation interrupt processing 70 described later. Enter your body position. Further, in step 652, the traveling azimuth θ and the moving speed (vehicle speed) Vu based on the data obtained from the sensor on the moving body 210 side are calculated as follows:
Input is made from the moving body direction estimating unit 14 and the moving body speed estimating unit 16.

Next, in a satellite selection process performed by the satellite selection unit 10 in step 653, a satellite suitable for calculating the moving direction gradient of the moving object is selected. A specific example of the satellite selection process will be described in detail in a second embodiment below.

Next, at step 654, step 65
For the satellite selected in step 3, the satellite azimuth α, satellite elevation angle β, pseudorange change rate ρ dot, and clock error change rate B dot, which are satellite information on the GPS satellite side and data such as the pseudorange change rate, are input. I do.

Further, in step 655, a line-of-sight vector is obtained from the satellite position included in the satellite information of the selected satellite and the position of the moving object input in step 651, and the line-of-sight vector and the satellite The line-of-sight component Vs · cos θs of the satellite speed vector is calculated from the satellite moving speed vector included in the information.

Finally, in step 656, the values obtained in the above-described steps are put into the above equation (10), and the gradient in the moving direction of the moving object is calculated for each of the selected satellites.

Next, a description will be given of a processing procedure of the moving object position estimation interrupt processing 70 executed by the moving object position estimating section 18 at regular time intervals Δt.

In this processing, as shown in FIG. 9, first, in step 72, the satellite information and the position data Xg, Yg, Zg obtained by the normal positioning by the GPS are input. Heading direction θgps, speed V
u and the gradient γ are obtained from the results of the calculation interruption processes 50, 60 and 65.

In step 76, it is determined whether or not the current positioning by GPS is possible (the number of received satellites is 3 or more). When normal positioning is possible (Yes in step 76)
Is obtained by obtaining three velocity vector components by the velocity vector calculation unit 6 and using the horizontal components Vx and Vy among them, in step 8
At 0, the traveling direction of the moving object is calculated by the following equation.

[0112]

Equation 13 θgps = tan ~ ¹ (Vy / Vx) The azimuth calculated by the above equation may be directly replaced with θgps. In this case, means for complementing the error between the GPS and the gyro sensor may be further provided.

If the number of receivable GPS satellites is one or two (No in step 76), the azimuth is not reset by the GPS velocity vector in step 80, and
The moving body direction is determined only by integrating the angular velocity based on the gyro data in the moving body direction calculation interrupting process 50.

Thereafter, in step 82, the moving distance components ΔX and ΔY of the moving body on the horizontal plane are calculated from the moving body azimuth θgps, the moving body speed Vu, and the interruption time interval Δt.
In step 84, the current position coordinates X and Y obtained in the previous processing are added to each other to obtain new positions X and Y of the moving body.

The positions X and Y obtained in this way are compared with the GPS positioning positions Xg, Yg and Zg output from the GPS positioning unit 7 when the GPS normal positioning is possible in Step 86, and if they are far apart (Step 86). Yes
Goes to step 88 and is reset to the GPS positioning positions Xg and Yg. After step 88 and step 86
In the case of No, the process enters the map matching process of step 90.

An example of the map matching processing 90 is as follows.
This will be described with reference to FIG.

First, the current position X, Y, the moving body azimuth θgps and the gradient γ are input in step 91, and then in step 92
The road data near X and Y is read from the map memory 306.

Next, at step 93, the current position X,
Road links within a predetermined distance from Y are specified, and a search is started for all road links within these ranges. At this time, one of the road links within a predetermined distance is selected, and the positions of the legs of the perpendicular dropped on the selected road link are set as Xm and Ym.

In step 94, the moving body direction θgps and the link direction are compared with the selected road link, and if they match within a predetermined value, the process proceeds to step 95. Then, in step 95, if link gradient information is provided as one of the road link data,
The link gradient and the moving object gradient γ are compared, and if both match within a predetermined value, it is considered that the vehicle is traveling on a road corresponding to a road link corresponding to the link gradient,
In step 96, the current position is X on the road link.
The moving object position is matched with m and Ym.

Then, Xm and Ym on the road link are output as the current position X and Y of the moving object as the final estimation result of the moving object position estimation interrupt processing 70. At this time, not only the position but also the direction of the moving object may be replaced with the direction of the road link. Thereby, even if the state in which the azimuth cannot be reset in step 80 of FIG. 9, that is, the state where the normal positioning of the GPS cannot be performed, continues for a long time, it is possible to prevent a large error from occurring in the azimuth of the moving body.

If the result of any of steps 94 and 95 is No, the process proceeds to step 97, and
Determine if all road links have been checked,
When the check is not completed (No in step 97)
Then, the process returns to step 93, and the same comparison is attempted for another road link.

When it is determined that the steps 94 and 95 are not simultaneously satisfied for all the road links within the predetermined distance searched in the step 93 and that there is no road link to be matched (Yes in the step 97).
Is output as the final estimation result of the moving object position estimation interrupt processing 70 while the current positions X and Y remain input values.

According to the present embodiment, as shown in the map matching processing procedure of FIG. 10, conventionally, a road link to be matched is determined based on the proximity of the position (step 93) and the degree of matching of the azimuth (step 94). In addition to being determined,
In step 95, the traveling direction gradient of the moving object can be newly introduced into the collation item, and more accurate map matching can be performed. For example, it is possible to identify an elevated road and an under-elevated road that have the same position and the same direction in plan view, and the route guidance function that greatly changes the guidance content depending on whether you are traveling on the upper or lower road is a significant performance Improvement can be achieved.

Further, according to the present embodiment, when acquiring the gradient information, the gradient information can be realized at low cost without newly adding a dedicated sensor, and can be understood from the gradient calculation formula shown in the equation (10). GPS information can be entered into the self-contained navigation system in the direction and speed of the moving object.
The gradient can be calculated with higher accuracy than the gradient information calculated using only the velocity vector obtained by the positioning.

In the present embodiment, the gradient of the road has been described. However, by connecting the gradient information obtained as described above, the altitude of the road or the ground surface on which the moving body has moved with respect to the predetermined reference point is determined. And the altitude information may be used instead of the gradient information.

Next, a second embodiment of the GPS navigation device to which the present invention is applied will be described.

This embodiment has the same configuration, operation and effects as those of the first embodiment, except for the details of the satellite selection processing (step 653 in FIG. 8) in the first embodiment. Hereinafter, a specific example of this satellite selection processing will be described with reference to FIGS.
2 will be described.

In the first example of the satellite selection processing 653-1, as shown in FIG. 11, first, at step 140, one of the receivable GPS satellites is selected, and the satellite information on this satellite is obtained. I do.

Next, in step 141, the position of the satellite included in the satellite information is converted from the absolute coordinate system (see FIG. 3) to the coordinate system using the moving object position input in step 651 in FIG. 8 as the origin. (See FIG. 4), and step 142
Calculates the azimuth α and the elevation β of the receiving satellite. In the processing of this example, since only the elevation angle β is considered when selecting a satellite, a configuration may be used in which only the elevation angle is obtained by a method other than coordinate conversion.

Next, in steps 144, 146, and 148, only the GPS satellite having the maximum elevation angle β is selected.

The basis of the above-mentioned satellite selection criterion is that it is basically necessary to accurately estimate the change in the vertical direction in order to improve the gradient calculation accuracy. Therefore, in the present embodiment, the GP measured using the range rate between the range between the GPS satellite and the moving object on the earth and the rate of change thereof is used.
In S, a satellite arrangement sensitive in the vertical direction, that is, a satellite having a high elevation angle is selected. However, the elevation angle of 90 degrees is a singular point because the denominator A (= cosβcos (θ−α)) becomes zero, as can be understood from the gradient calculation formula of the above equation (10). Must be excluded.

As shown in FIG. 12, in the second example 653- 2 of the satellite selection processing, the azimuth θ of the moving object is first obtained in step 150, and the azimuth α of the receiving satellite is obtained in steps 151, 152 and 153. And the elevation angle β. In addition,
In this example, since only the azimuth α of the satellite is used for the selection determination, only the azimuth α of the satellite may be obtained by another method.

In steps 154, 155, and 156, the azimuth α of the satellite is set to
Only those GPS satellites that are close to the opposite direction and fall within a predetermined angle range are selected.

As described above, the basis of the satellite selection criterion is that, in order to improve the gradient calculation accuracy, it is necessary to accurately estimate the change in the vertical direction, and the change in the traveling direction of the moving body in the horizontal plane is also required. That is, it is necessary to estimate accurately. Therefore, in the GPS that measures the range between the GPS satellite and the moving object on the earth and the range rate of the rate of change, the satellite arrangement sensitive to the moving direction of the moving object, that is, the azimuth angle α of the satellite moves. GP close to the body's direction of travel θ or 180 degrees opposite
The S satellite will be selected.

Here, as described in the equation for calculating the gradient of the above equation (10), ± indicates that the satellite whose target is + is located on the rear side of the car (90 degrees <θ-α <270 degrees). When the target satellite is in front of the car (0 degree <θ-α <90 degrees, 270
Degree <θ-α <360 degrees). From this, assuming that the two satellites in the traveling direction and the opposite direction are selected as the satellites suitable for the gradient calculation based on the selection criterion of the satellite selection processing 653-2, the gradient calculation error between the two becomes true. It tends to be positive and negative at the border. If such a property is used, it is possible to select a satellite in which the gradient calculation errors of the above equation 10 are mutually corrected by averaging the gradient calculation values of the two.

According to the present embodiment, the satellite arrangement conditions suitable for the gradient calculation are clarified from the basic formula for gradient calculation of the above equation (10), and the satellites according to the criteria are preferentially selected. , The accuracy of calculating the gradient can be further improved.

At this time, as described above, it is not always necessary to reduce the number of applicable satellites to one, and each satellite information is weighted based on the elevation data and the azimuth data. By selecting a plurality of satellites in such a manner and obtaining an average gradient according to the data from these satellites and the weight of each data, the gradient may be made more accurate.

Further, as is apparent from the above-described basic expression for calculating the gradient, the gradient can be calculated in principle if one or more satellite signals can be received. Therefore, if an optimal satellite that meets the satellite selection conditions of the present embodiment is selected, the GPS
Without being limited to the normal positioning conditions, it is possible to always perform highly accurate gradient calculation.

Next, a third embodiment to which the present invention is applied will be described.

This embodiment has the same configuration, operation and effects as those of the first embodiment, except for the details of the map matching processing (step 90 in FIG. 9) in the first embodiment. Hereinafter, a specific example of the map matching processing will be described with reference to FIG.

The processing procedure shown in FIG. 13 differs from the map matching processing procedure shown in FIG. 10 in steps 94-1 and 94-2.
The other processing procedures are the same as those in FIG. That is, in FIG. 10, it is assumed that the road link data includes gradient data, but here, a process in a case where there is no gradient data is added.

In this processing, it is determined in step 94-1 whether or not there is gradient data in the target road link data. If so, the processing proceeds in the same flow as in FIG. If there is no gradient data, the process proceeds to step 94-2, and the calculated gradient data is written in the target link data storage portion of the map memory 306 (see FIG. 2). Thereafter, since the matching based on the gradient data cannot be performed, the matching state is determined only by the matching based on the position and the azimuth as in the related art (step 96).

In the present embodiment, the map memory 306 is used.
It is assumed that the storage portion of the road link data included in the map data stored in the storage device has a configuration capable of storing the gradient information considered here.

According to the present embodiment, not only can the information amount of the map data be insufficient or inaccurate, but also if the road thus added or corrected is run again, collation using the gradient data can be performed. Higher-accuracy position detection becomes possible.

Further, according to the present embodiment, it is possible to learn gradient information of map data as the moving body moves. Further, it is possible to increase the frequency at which the following three-dimensional display with a reality of the fourth embodiment can be performed, which leads to an improvement in the overall performance of the entire system.

In addition to the map matching processing of the present embodiment, if the degree of matching according to the position and orientation is extremely high and there are no other road link candidates, step 95
If only the comparison based on the gradient data in step (1) does not match, the gradient data of the road link may be regarded as incorrect, and the gradient data of the road link may be corrected with the gradient data calculated in the present embodiment.

Further, instead of using the above-mentioned gradient data,
Data on road altitude is derived based on the gradient data, and this altitude data is used as one of the conditions for matching judgment, and is further stored as one of the road link data or modified as necessary You may.

Next, a fourth embodiment to which the present invention is applied will be described.

This embodiment is the same as the first embodiment except for the details of the display processing unit 22 (steps 46 and 54 in FIG. 5) for displaying a navigation screen on the display device 308.
It has the same configuration, operation and effect as the first embodiment.
Hereinafter, a specific example of the gradient information transmission method for notifying the user of the gradient information will be described with reference to FIG.

FIG. 14 shows a bird's-eye view of the traveling state of the moving object, centering on the own vehicle mark 410, together with the sky 412 as a background on the display device 308.

The gradient information newly acquired in the present invention is obtained by first displaying the grid lines 4 on the map screen 400 by the amount of the gradient or by the amount of emphasis correspondingly.
01, the gradient is displayed intuitively to the user.

Further, in this embodiment, a window 402 is opened at the lower right of the screen, and a schematic diagram 404 in which the gradient is viewed from the side is drawn therein. In addition, the gradient amount calculated with high accuracy according to the present invention is displayed by a numeral like 406,
Inform the user of the grade. At this time, the driving state such as the vehicle speed and the grade information is evaluated.
08 is displayed.

[0153] Instead of displaying an image, a configuration may be adopted in which the information is transmitted to the user by sound or light emission.

According to this embodiment, the gradient information newly acquired by the present invention is transmitted to the user intuitively, and detailed information such as the gradient amount can be quantitatively grasped. Further, a safety warning or the like can be generated together with other traveling information, and a multi-functional GPS navigation device excellent in human interface can be provided.

[0155]

According to the GPS navigation apparatus of the present invention, the vertical measurement, which is considered to be less accurate due to the principle of GPS surveying, in particular, the gradient measurement, is combined with a self-contained navigation system sensor, etc. It can be realized inexpensively and with high accuracy without adding a dedicated sensor.

Further, according to the present invention, an elevated road and an under-elevated road can be automatically identified, and not only the positioning accuracy is improved, but also, in particular, the route guidance performance, which is one of the navigation functions, is significantly improved. be able to.

Further, if the gradient information newly obtained in the present invention is used, a three-dimensional display having a reality closer to the actual driving state can be provided, and a navigation device excellent in terms of a human interface can be provided.

[Brief description of the drawings]

FIG. 1 is a block diagram showing a configuration of an embodiment of a GPS navigation device of the present invention.

FIG. 2 is a block diagram showing a hardware configuration example of the present invention.

FIG. 3 is an explanatory diagram for explaining the principle of gradient calculation according to the present invention.

FIG. 4 is an explanatory view showing details of a main part of FIG. 3;

FIG. 5 is a flowchart showing a general flow of the GPS navigation device of the present invention.

FIG. 6 is a flowchart of a moving body direction calculation interrupt process of FIG. 5;

FIG. 7 is a flowchart of a moving object speed calculation interruption process of FIG. 5;

FIG. 8 is a flowchart of a moving object gradient calculation interruption process of FIG. 5;

FIG. 9 is a flowchart of a moving object position estimation interrupt process of FIG. 5;

FIG. 10 is a flowchart of a map matching process in FIG. 9;

FIG. 11 is a flowchart showing one embodiment of the satellite selection process of FIG. 8;

FIG. 12 is a flowchart showing another embodiment of the satellite selection processing of FIG. 8;

FIG. 13 is a flowchart illustrating a map matching process according to an embodiment of the present invention in which gradient information is written to a map memory.

FIG. 14 is an explanatory diagram showing one embodiment of a screen displayed on the display device of FIG. 1;

[Explanation of symbols]

2 ... GPS satellite, 8 ... pseudo distance change rate measuring unit, 9 ... satellite information and pseudo distance measuring unit, 10 ... satellite selecting unit, 12 ... moving object velocity vector gradient calculating unit, 14 ... moving object direction estimating unit, 16 ... Moving body speed estimating unit, 18: moving body position estimating unit, 98: gradient data addition processing, 140: satellite selection processing, 304: GPS receiver, 306: map memory, 30
8: display device, 310: gyro sensor, 312: vehicle speed sensor.

 ──────────────────────────────────────────────────続 き Continued on the front page (72) Koji Kuroda, Inventor 7-1-1, Omikacho, Hitachi City, Ibaraki Prefecture Inside Hitachi Research Laboratory, Hitachi, Ltd. (72) Koji Nakamura 7-1, Omikamachi, Hitachi City, Ibaraki Prefecture No. 1 Inside the Hitachi Research Laboratory, Hitachi, Ltd.

Claims (15)

[Claims] 1. A G which receives a GPS signal from a GPS satellite.
A PS receiver, satellite information acquiring means for acquiring satellite information and a pseudorange from the received GPS signal, and when there are a predetermined number or more of receivable GPS satellites, the received GP
A GPS positioning device for determining a position of a moving object from the satellite information and the pseudorange acquired for each of the S satellites; a pseudorange for measuring a pseudorange change rate for each GPS satellite from the GPS signal. A rate-of-change measuring means;
A moving body speed / azimuth measuring means for measuring without using the S signal; a moving body position determined by the GPS positioning means; and at least one receivable GPS satellite obtained by the satellite information obtaining means. Satellite information, the pseudo-range change rate obtained by the pseudo-range change rate measuring means for the at least one receivable GPS satellite, the speed of the moving object measured by the moving object speed / azimuth measuring means, and A GPS navigation device comprising: a moving body speed vector gradient calculating means for calculating an angle (hereinafter, referred to as a gradient) of a speed vector of a moving body from a horizontal plane from at least one of the azimuths. 2. The GPS navigation device according to claim 1, further comprising a gradient information transmitting unit that notifies the user of the GPS navigation device of the gradient information obtained from the moving object velocity vector gradient calculating unit. . 3. The apparatus according to claim 2, further comprising a display unit for displaying the current position of the determined moving body, wherein the gradient information transmitting unit corresponds to the schematically displayed moving body corresponding to the gradient amount. A GPS navigation device which informs a user by displaying a state of being tilted by an amount on the display means. 4. A storage unit for storing map data including gradient information on each road on which a moving body moves, gradient information obtained from the moving body velocity vector gradient calculating means, A GPS navigation device, further comprising: a moving object position estimating means for estimating a position of the moving object based on a degree of collation with information of the map data corresponding to the gradient information. 5. The moving object velocity vector gradient calculating means according to claim 4, wherein said map data is stored in said storage means so that gradient information contained therein can be rewritten. A GPS navigation device, further comprising a gradient information correcting means for collating the obtained gradient information with the corresponding information of the map data and performing correction according to the degree of the collation. 6. The gradient information obtained from the moving body velocity vector gradient calculating means according to claim 4, wherein the map data is stored in the storage means so that gradient information can be added. A GPS navigation device, further comprising a gradient information adding unit that determines whether corresponding information exists in the map data, and if not, adds the gradient information to the map data. 7. The image data according to claim 4, wherein a predetermined display mark indicating the estimated position of the moving object is superimposed on a map image based on map data of a predetermined range area including the position. And display means for displaying the generated image data. The map image in the image data includes a gradient corresponding to the gradient information included in the map data. A GPS navigation device comprising an image to be displayed. 8. A vehicle according to claim 1, wherein when there are a plurality of receivable GPS satellites, said plurality of GPS satellites are used for processing by said moving object velocity vector gradient calculating means according to a predetermined selection criterion. A GPS navigation device, further comprising satellite selection means for selecting the at least one GPS satellite. 9. The GPS according to claim 8, wherein said satellite selecting means preferentially selects a satellite having a large elevation angle of a satellite position obtained from satellite information obtained by said satellite information obtaining means. Navigation device. 10. The satellite selection means according to claim 8, wherein the azimuth angle of the satellite position obtained from the satellite information obtained by said satellite information acquisition means is closer to the traveling direction of the moving object or a direction opposite to the direction by 180 degrees. A GPS navigation device for preferentially selecting a satellite. 11. The satellite selecting means according to claim 8, wherein said satellite selecting means selects two or more GPS satellites, and said moving object velocity vector gradient calculating means selects said selected two or more GPS satellites.
A GPS navigation device comprising: calculating a gradient value for each of a plurality of GPS satellites; and calculating an average of the gradient values to obtain a final gradient of a velocity vector of the moving object. 12. The moving object velocity vector gradient calculating means according to claim 1, wherein
When there are a plurality of PS satellites, at least two of the plurality of GPS satellites are selected, a gradient value is calculated for each of the plurality of GPS satellites, and a weight is assigned according to the position of each of the selected GPS satellites. A GPS navigation device, wherein an average of the calculated gradient values is obtained using the calculated average, and the average is used as a final gradient of the velocity vector of the moving body. 13. The vehicle according to claim 1, wherein the moving body is an automobile, and the moving body speed / azimuth measuring means includes at least a vehicle speed sensor for measuring a rotation state of wheels of the automobile. GPS navigation device. 14. The moving body speed / azimuth measuring means according to claim 1, wherein the moving body speed / azimuth measuring means detects at least one of a gyro sensor for detecting a rotational angular velocity caused by a change in the moving azimuth of the moving body, and a road link azimuth in the map data. A GPS navigation device comprising at least means for determining a moving direction by using a GPS navigation device. 15. The vehicle according to claim 1, wherein the moving body is an automobile, and the moving body speed / azimuth measuring means has a vehicle speed sensor for measuring a rotation state of wheels of the automobile and a gyro sensor for detecting a rotational angular velocity. These sensors measure the speed and direction of the moving object.The moving object speed vector gradient calculating means calculates, for each GPS satellite, the origin of the moving object position based on the moving object position and the satellite information. Calculating the elevation angle and azimuth angle of the satellite to be measured in the coordinate system, calculating the line-of-sight component from the moving object to the satellite in the velocity vector of the satellite, and calculating the elevation angle and azimuth angle of the satellite, From the calculated line-of-sight component of the satellite speed vector, the measured speed and direction of the moving object, and the measured pseudorange change rate, calculate the gradient of the moving object speed vector. GPS navigation device, characterized in that the output.