JPH03188316A - Azimuth detector - Google Patents

Abstract

PURPOSE:To accurately calculate an estimated azimuth by performing weighting by regarding data more reduced in a noise component as important using a Karman filter constituted on the basis of azimuth data and revolving angular velocity data set as variables. CONSTITUTION:The noise components respectively contained in the output data thetaH of a geomagnetism sensor and the output data DELTAthetaG of a revolving angular velocity sensor are measured by a noise measuring means 12 and the measured noise values are supplied to a filter gain calculation means 13 to calculate a Karman filter gain K. Predetermined weighting processing is applied by a Karman filter means 11 to output an estimated azimuth theta. Since weighting can be performed by more regarding the data more reduced in noise among the data thetaH, DELTAthetaG as important, the azimuth of a moving body can be more accurately estimated.

Description

[Detailed Description of the Invention] <Industrial Application Field> The present invention relates to an azimuth detection device, and more specifically, it uses a geomagnetic sensor to detect the direction of movement of a moving body to determine the turning angular velocity. The present invention relates to an orientation detection device that detects the orientation of a moving body in one direction using a turning angular velocity sensor (for example, an optical fiber gyro, a mechanical gyro, a vibration gyro, or a gas rate gyro).

<Prior Art> Conventionally, the explanation will be based on the assumption that vehicles traveling at any point on a road transportation network, aircraft navigating air routes, ships navigating sea routes, etc. (hereinafter referred to as "vehicles").Vehicles of"
A distance sensor, an azimuth sensor (either a geomagnetic sensor or a turning angular velocity sensor) are used to detect the position of an aircraft or ship. , and a processing device that performs the necessary processing on the output signals from both sensors. Dead Reckoning (Dead Reckoning) has been proposed to obtain current position data of a moving object using sensors. This method calculates, for example, the east-west component ΔX (-Δ) ') for each of the above components ΔX.

By adding Δy, the current position output data (P
This is a method for determining the values (x, Py), but it has the drawback that errors included in the obtained current position data are accumulated due to errors that the orientation sensor inevitably has.

That is, when the direction sensor is a geomagnetic sensor that detects the earth's magnetism and knows the absolute direction of the moving body, the geomagnetic direction sensor detects the strength of the weak earth's magnetic field,
If the main body of the moving body is magnetized, an error will occur in the output data. In order to cancel out this error, the geomagnetic direction sensor is initialized, but when a vehicle is driving, it must pass through railroad crossings, power cable burial sites, railway bridges, expressways with soundproof walls, and valleys between high-rise buildings. As the amount of magnetization of the vehicle body changes due to the influence of strong electromagnetic fields from the outside, errors may occur again. Therefore, unless the geomagnetic sensor output data containing such magnetic field disturbances is accurately detected and eliminated, the correct orientation cannot be determined.

On the other hand, when using a turning angular velocity sensor, for example,
When the direction change exceeds a predetermined value, when the power (ignition) is turned on, when driving at extremely low speeds, or when driving on rough roads such as mountain roads is detected, many errors may appear in the sensor output data. is known, and if these data are used as is, the direction detection accuracy will decrease.

Therefore, two orientation sensors, a turning angular velocity sensor and a geomagnetic sensor, are used together as an azimuth sensor, and if the reliability of either the output data of the turning angular velocity sensor or the output data of the geomagnetic sensor decreases, the other Direction detection devices supplemented with data have been considered, but the problem is how to combine these devices.

For example, the mobile object orientation detection device disclosed in Japanese Patent Application Laid-Open No. 60-122311 usually uses a geomagnetic sensor,
When the variation of the geomagnetic sensor within the designated time is greater than or equal to the set value, and the variation of the turning angular velocity sensor is less than or equal to the set value, it is suggested that the output data of the turning angle sensor be adopted.

<Problems to be Solved by the Invention> However, in the above-mentioned prior art, when the output data of the geomagnetic sensor is excluded, position detection is continued by relying only on the output data of the turning angular velocity sensor, but the output data of the geomagnetic sensor is There is a problem in that while the exclusion of the rotation angle velocity sensor continues for a long time, an accumulated error occurs in the turning angular velocity sensor under certain circumstances, making it impossible to continue accurate position detection.

That is, if only the turning angular velocity sensor is relied upon, errors will accumulate under conditions where errors in the output data of the turning angular velocity sensor are likely to occur, and there is a risk that the accuracy of detecting the position of the vehicle will decrease.

Furthermore, even if the turning angular velocity sensor output data is removed when a malfunction of the turning angular velocity sensor is detected and the vehicle continues to drive relying on the geomagnetic sensor output data, the geomagnetic sensor output data may be removed while the vehicle is running or when passing a railroad crossing, etc., as described above. There is a risk that the data output will be greatly distorted and the accuracy of vehicle position detection will decrease.

Of course, when the reliability of the turning angular velocity sensor output data becomes lower than the standard, it is immediately switched to the geomagnetic sensor output data, and when the reliability of the geomagnetic sensor output data becomes lower than the standard, it is immediately switched to the turning angular velocity sensor output data. If you switch over, you can relatively suppress the decline in position detection accuracy, but until you determine that the reliability has fallen below the standard, you will continue to use data whose reliability is unknown. , it is clear that this will have a negative effect on the subsequent position detection accuracy.

An object of the present invention is to obtain an azimuth detection device that captures the output data of a turning angular velocity sensor and a geomagnetic sensor, calculates the current azimuth of a moving object from those values and estimated past azimuths, and thereby determines the current position of the moving object. To provide an orientation detection device capable of processing output data of a turning angular velocity sensor and a geomagnetic sensor in real time, giving more weight to the more reliable data, and accurately estimating the current orientation of a moving body. There is a particular thing.

Means for Solving the Problems> The orientation detection device of the present invention for achieving the above objects has the following features:
As shown in Figure 1, the output data θH1 of the geomagnetic sensor
and noise measuring means 12 for extracting noise components contained in the output data ΔθG of the turning angular velocity sensor, respectively;
A filter gain calculating means 13 for calculating a Kalman filter gain K using each noise component measured by the noise measuring means 12, and azimuth data θH of the geomagnetic sensor.
and azimuth estimating means 11 for calculating the current estimated azimuth θ of the moving body by weighting the azimuth data θ0 obtained from the output Δθ0 of the turning angular velocity sensor based on the Kalman filter gain K.

Effect> According to the direction detecting device having the above configuration, the noise measuring means 1
2, the noise components included in the output data θH of the geomagnetic sensor and the output data Δθ0 of the turning angular velocity sensor are measured. As a result, each sensor's output data θ1. Δ
The reliability of θ0 can be evaluated individually. The measured noise value is supplied to filter gain calculation means 13, and Kalman filter gain K is calculated. and,
The Kalman filter means 11 performs a predetermined weighting process and outputs the estimated orientation θ.

In this way, it is possible to weight the data with a smaller noise component among θHΔθG, thereby making it possible to estimate the orientation of the moving object more accurately.

In addition, when measuring the above-mentioned noise component, data while the vehicle is running may be used, or data while the vehicle is stopped may be used.

However, it is preferable to use data while the vehicle is running. This is because, since the bearing during driving is estimated using a Kalman filter, it is preferable to evaluate noise using data during driving, which includes noise caused by vibrations during driving, dynamic characteristics of the vehicle, etc.

In particular, it is more preferable to use data during straight running that does not include angular velocity components due to turns. However, if there is a means to extract only noise components even when turning, the data is not limited to data during straight running.

Further, even when the vehicle is stopped, if there is a means to properly determine the noise of the angular velocity sensor, a Kalman filter may be determined from the noise components during the vehicle is stopped.

<Example> Embodiments will be described in detail below with reference to the accompanying drawings showing embodiments.

FIG. 3 is a block diagram showing an embodiment of the direction detection device of the present invention applied to a vehicle. Vehicle speed sensor 41 that detects the rotational speed of both left and right wheels (this sensor is used as a distance sensor). )・Geomagnetic sensor 42,・Gyro 43 (an optical fiber gyro that reads the turning angular velocity as a phase change of interference light, a vibrating gyro that detects the turning angular velocity using cantilever vibration technology of a piezoelectric element, a mechanical gyro, etc.) selected from.

Used as a turning angular velocity sensor. ), ・Road map memory 2 storing road map data, ・Calculates the estimated heading of the vehicle based on the output data detected by the gyro 43 and the geomagnetic sensor 42, and also calculates the vehicle position along with the data of the vehicle speed sensor 41. It consists of a locator 1 that calculates output data and stores it in a buffer memory 3; a navigation controller 5 that displays the read vehicle current position on a display 7 overlaid on a map and interfaces with a keyboard 8;

The locator 1 obtains the number of wheel rotations by, for example, counting the number of output pulse signals from the vehicle speed sensor 41 with a counter, and uses a multiplier to calculate the number of rotations per count for the count output data output from the counter. The mileage output data per unit time is calculated by multiplying by a predetermined constant indicating the distance, and the relative change in vehicle direction is obtained from the gyro 43, and this and the geomagnetic sensor 42
The vehicle's azimuth output data is calculated from the absolute azimuth output data of the vehicle.

The road map memory 2 stores road map data covering a predetermined range in advance, and includes a semiconductor memory,
Cassette tape, CD-ROM.

IC memory, DAT, etc. can be used.

The display 7 uses a CRT, liquid crystal display, or the like to display a road map and the vehicle position while the vehicle is traveling.

The navigation controller 5 is composed of a graphic processing processor, an image processing memory, etc., and performs map searching, scale switching, scrolling, etc. on the display 7.
The current position of the vehicle is displayed.

A procedure for detecting vehicle direction using the device configured as described above will be explained. While the vehicle is running, the position of the vehicle is displayed on the display 7 together with a map based on the output data of each sensor captured by the locator 1, but even during the display, the output data of each sensor is displayed due to interruptions at regular intervals. I am trying to import the data and update the vehicle position. FIG. 2 shows the vehicle direction detection flow at the time of this interruption. Note that this interruption may be performed every fixed distance traveled, which is determined based on the distance output data of the vehicle. The length of the above-mentioned fixed time or fixed travel distance is appropriately set depending on the type of turning angular velocity sensor used, the performance of the geomagnetic sensor, and the like.

First, in step (2), output data Δθ0 of the gyro 43 and output data θ1 of the geomagnetic sensor 42 are taken in.

Next, determine whether the vehicle is traveling in a straight line (step ■
). Whether or not the vehicle is traveling on a straight road can be determined by simple comparative calculations based on output data from the gyro 43 over a relatively short period of time. That is, θ6−θ+ΔθG is calculated using the output data Δθ0 of the gyro 43 and the previous estimated orientation θ. If the difference between this value and, for example, the average value <θ> of several past estimated directions, 1θ6 - θ>1, is less than the reference value e, it can be determined that the vehicle is traveling in a straight line.

In addition to this, the determination may be made using a map matching method.

If the vehicle is not traveling in a straight line, the estimated heading θ0 is registered for use in detecting the heading (step ■), a counter n indicating the number of continuous interruptions is set to 0 (step ■), and the process proceeds to step [phase].

If the vehicle is traveling in a straight line, increment the counter n by 1 (Step ■) and store the sensor output data Δθ6 θH in the nth address of the buffer memory 3 (Step ■); Hereafter, the data stored in the nth address is incremented by ΔθG n1θHn.
), determine whether n has reached the maximum value m determined from the capacity of the buffer memory 3, etc. (step ■)
. If the maximum value m has been reached, it is determined that a sufficient amount of data has been collected for the following calculation, and the process proceeds to step (2). If the maximum value m has not been reached, the process returns to the state before the interrupt and repeats the above process.

In step ■, data Δθ' collected in the past m times is
Average value using n (n=1 to +a), n-■ Δθ'> −(1/11) Σ ΔθG n.

r1 Variance value, . ,.

S' = (17m) Σ (Δθ6 n −
<θ6>) Find 2n=1.

In step ■, data θ'n(
n=1-m), the average value, n-■ θ'>-(17m) Σ θIn −1 variance value, ,.

S' − (1/m) Σ (θHn−kuθ”〉)2
Find rl.

The variance values sG and SR obtained as described above correspond to the magnitude of noise in the output data of the sensor. Therefore, in step [phase], an estimated direction is calculated based on the following equation, taking into account the latest variance values sG and SR.

θi = (1-Ki) (θi-1+ΔθGl)
+Ki θH+ Here, θi is the estimated direction obtained by this interruption, θi
-1 is the direction found last time. Δθ61°θH1 is the output data of the sensor used when calculating the current estimated direction, for example, the latest data Δθ' III +
θHI11 may be used, or the above average value Δθc
><00> may also be used. Kl is 0<Ki<1
This variable is called the Kalman gain. Ki is obtained using the Kalman gain K i-1 obtained last time as follows: K, m 5G + 1-I SH s'+s'' +Ki-t s''.

As described above, the Kalman gain Ki is determined in real time according to the amount of noise in the output data of both sensors, and as a result of weighting, a new vehicle orientation θi can be determined.

The estimated position of the vehicle can be calculated from this direction θl and the distance data from the vehicle speed sensor 41.

Of course, at this time, a map matching method may be adopted in which the estimated position of the vehicle is corrected by comparing it with the road map data, evaluating the degree of correlation with the road map data, and setting the current position of the vehicle on the road. (See Publication No. 63-148115)
.

Although the orientation detection device of the present invention has been described above based on the embodiments, the present invention is not limited to the above embodiments. For example, the present invention can be applied to moving bodies such as aircraft and ships instead of vehicles, and various other design changes can be made without changing the gist of the invention.

<Effects of the Invention> As described above, according to the azimuth detecting device of the present invention, the noise component is reduced by using the Kalman filter configured with the azimuth data θ'' of the geomagnetic sensor and the output data ΔθG of the turning angular velocity sensor as variables. Since weighting can be performed with more emphasis on less data, an accurate estimated orientation of the moving object can be obtained in real time.

Therefore, the position of the moving object can be accurately determined based on the above-mentioned direction.

[Brief explanation of drawings]

FIG. 1 is a functional block diagram of the orientation detection device of the present invention, FIG. 2 is a flowchart showing the orientation detection procedure, and FIG. 3 is a block diagram showing the hardware configuration of the orientation detection device. 1... Locator, 3... Buffer memory, 11...
- Orientation estimation means, 12... Noise measurement means, 13...
- Filter gain calculation means, 42... geomagnetic sensor,
43...Gyro

Claims (1)

[Claims] 1. An azimuth detection device that takes in azimuth data from a geomagnetic sensor and azimuth data obtained from the output of a turning angular velocity sensor, and calculates the current estimated azimuth of a moving body from these values and past estimated azimuths. , a noise measuring means for extracting noise components contained in the output data of both the above-mentioned sensors, a filter gain calculating means for calculating a Kalman filter gain using each noise component measured by the above-mentioned noise measuring means, and a geomagnetic sensor. and azimuth estimating means for calculating the current estimated azimuth of the moving object by weighting the azimuth data obtained from the output and the azimuth data obtained from the output of the turning angular velocity sensor based on the Kalman filter gain. Characteristic direction detection device.