JP5074950B2 - Navigation equipment - Google Patents

Description

  The present invention relates to a navigation apparatus that performs navigation calculation that performs positioning and the like by integrating external support data including at least a detection value of an angular velocity sensor and an observation amount obtained by receiving a positioning signal from a navigation satellite. .

  An inertial navigation device that performs an inertial navigation calculation based on a detection signal of an inertial sensor uses an angular velocity sensor that detects an angular velocity of a moving body in a predetermined direction as one of the sensors. In addition, the satellite navigation / inertial navigation integrated positioning device that integrates the observation amount obtained from the GPS positioning device and the observation amount obtained from the inertial navigation system (INS), which is an independent system, is also a sensor other than GPS. An angular velocity sensor, a temperature sensor, an acceleration sensor, and / or a velocity sensor are used (see Patent Documents 1 to 4).

  In the navigation apparatus that performs the navigation calculation using the angular velocity sensor as described above, conventionally, the angular velocity bias of the angular velocity sensor is estimated by any one of the following methods.

(1) Method of Estimating as a Function of Temperature The angular velocity bias is estimated as a function of temperature by batch processing using the least square method or the like.

(2) Method for estimating in time series The angular velocity bias is estimated in time series in real time by sequentially performing operations such as a Kalman filter on the detection signal of the angular velocity sensor.

  The device of Patent Document 1 calculates a drift value with respect to the temperature of the vibrating gyroscope while the vehicle is stopped, stores it as a temperature characteristic map, obtains a drift value corresponding to the current temperature during traveling, and outputs an output voltage from the vibrating gyroscope. Is to correct.

  The device of Patent Document 2 is a device that determines the azimuth and position of a vehicle by dead reckoning navigation, and corrects the temperature-dependent drift of the bias of the azimuth sensor using a Kalman filter. For each stationary point, calculate the orientation sensor bias drift rate vs. temperature model coefficients and use the bias drift rate calibration curve during vehicle movement to periodically adjust the orientation sensor bias. To be estimated.

  In the device of Patent Document 3, when the angular velocity sensor such as the vehicle traveling speed determination means and the GPS system outputs a zero point voltage, the ambient temperature of the angular velocity sensor is determined by the temperature sensor together with the output voltage of the angular velocity sensor at that time. By detecting and changing the zero-point voltage of the correction characteristic storage memory at the detected temperature to the detected output voltage, the zero-point voltage-temperature characteristic of the angular velocity sensor is dealt with individual differences and aging of the angular velocity sensor. Is.

  When detecting the stop of the vehicle, the device of Patent Document 4 stores the output value of the angular velocity sensor as a reference value at the sensor temperature at that time, and when obtaining the angular velocity, it is stored corresponding to the sensor temperature at that time. The reference voltage is used to correct the output voltage of the angular velocity sensor.

  Here, as an example of the “method of estimating as a function of temperature” in the above (1), the configuration of the apparatus disclosed in Patent Document 1 will be described with reference to FIG. In FIG. 1, a vehicle position detection apparatus 1 includes a vibration gyro 2 arranged at an appropriate position of a vehicle, a temperature sensor 3 for detecting the temperature of the vibration gyro 2, and an A / D for converting these detection signals into digital signals. Converter 4, computer 5 for inputting various digital signals from A / D converter 4, wheel speed sensor 6 for inputting detection signals relating to wheel speed to computer 5, and navigation for displaying the vehicle position A device 70 is provided.

Each time the vehicle stops, the computer 5 obtains the temperature at the time of stopping and the drift value of the vibration gyro, and estimates the drift characteristic of the vibration gyro with respect to the temperature (function of temperature). The detection signal of the vibration gyro is corrected with the function.
Japanese Patent Laid-Open No. 04-364422 JP 2002-303533 A JP 2000-111348 A JP 2007-024601 A

  However, the conventional navigation devices including Patent Documents 1 to 4 have the following problems to be solved.

(1) Method of estimating as a function of temperature Since the method of estimating as a function of temperature is a batch process, the angular velocity bias cannot be estimated in real time. In addition, it can be obtained directly if the moving body is stopped, but it is unknown whether the value output from the angular velocity sensor is due to the movement of the moving body or the angular velocity bias during movement. It is difficult to estimate the angular velocity bias by comparison with GPS data. Therefore, for example, when the vehicle travels without stopping on a highway, the angular velocity bias is not updated, so that an estimation error of the angular velocity bias increases due to a temperature change.

  Further, when passing through a tunnel on the highway, positioning by satellite navigation cannot be performed, and only inertial navigation using angular velocity information with a large error is performed, so that positioning accuracy is deteriorated.

(2) Method of estimating in time series When trying to estimate the angular velocity bias that depends on temperature fluctuations by the method of estimating in time series, the angular velocity bias (or the detected value of the angular velocity sensor and the angular velocity bias under the condition where the temperature fluctuation width is small). (Actual angular velocity obtained from the above) cannot be estimated correctly.

  Moreover, it cannot respond when the temperature is different between when the navigation calculation is stopped and when it is started. For example, when the navigation calculation is stopped, such as when the engine is stopped, the values used in the navigation calculation are backed up to prepare for the subsequent start of the navigation calculation. If the temperature is significantly different, the value of the backed up value is low.

  For example, if you park in an indoor parking lot in the daytime when the temperature is high and leave the indoor parking lot at night when the temperature is low, the component of the angular velocity bias due to temperature change directly becomes the estimation error of the angular velocity bias, and satellite navigation Until it becomes possible, the accuracy of navigation data (position, speed, etc.) will deteriorate. Thus, even if the estimated value of the angular velocity bias immediately before the stop of the navigation calculation is backed up, its utility value is low.

  Therefore, the object of the present invention is to combine the advantages of the method of estimating as a function of temperature and the advantages of the method of estimating in time series, estimating the angular velocity bias in real time during movement, and calculating the position, velocity, direction, etc. It is an object of the present invention to provide a navigation apparatus that can maintain high accuracy of navigation data.

  The navigation device of the present invention takes advantage of both the method of estimating as a function of temperature and the method of estimating in time series. Therefore, the navigation device of the present invention is configured as follows.

Positioning signal transmitted from ocean-going method satellites, and the navigation system with an integrated navigation calculation means for performing an integrated navigation calculation based on external support data including the detection value of the angular velocity sensor provided in the moving body, the temperature of the angular velocity sensor Alternatively, the temperature characteristic of the angular velocity bias is determined based on the temperature sensor that detects the temperature of the environment in which the angular velocity sensor exists, and at least the detected value of the angular velocity sensor and the detected value of the temperature sensor when the moving body is stopped. Angular velocity bias temperature characteristic detection means, and the integrated navigation calculation means is based on the detection value of the angular velocity sensor, the detection value of the temperature sensor, and the temperature characteristic of the angular velocity bias during a period in which the positioning signal cannot be received. calculating the angular speed Te, the period capable of receiving a positioning signal, based on the detected value and the temperature characteristics of the angular velocity bias of said temperature sensor Te set angular velocity bias calculated most recently to the initial value of the angular velocity bias of the integrated navigation calculation, it is assumed that estimates the angular bias and angular velocity based on the integrated navigation operation results.

  Thus, by using a calculated value as a function of temperature as an initial value in time-series real-time processing, it is possible to cope with a temperature difference between day and night, which was difficult only by the time-series estimation method. Also, the angular velocity bias that changes from moment to moment is expressed as “angular velocity bias that does not depend on temperature estimated by real-time processing in time series” + “temperature characteristics (coefficient) of angular velocity bias calculated by batch processing as a function of temperature” × “temperature By calculating as “change”, it is possible to estimate the angular velocity bias in real time during movement, which is difficult only by the method of estimating it as a function of temperature.

  Note that the detected value of the angular velocity sensor when the moving body is stopped is a value corresponding to an angular velocity of 0 if there is no bias, but this state is not limited to when the moving body is stopped, but is the same even during constant velocity linear motion. It is. Therefore, the temperature characteristic detection means of the angular velocity bias may obtain the temperature characteristic of the angular velocity bias based on the detection value of the angular velocity sensor and the detection value of the temperature sensor when the moving body is moving at a constant linear velocity.

  According to this configuration, the angular velocity bias and the angular velocity are accurately estimated immediately after the integrated navigation calculation is started.

Also, navigation system of the present invention, the integrated navigation calculation means,
An angular velocity bias temperature variation update that detects an angular velocity bias temperature fluctuation amount based on a detected value of the temperature sensor and a temperature characteristic of the angular velocity bias at a predetermined timing, and updates an estimated angular velocity bias value using the temperature fluctuation amount. And Kalman filter calculation means for estimating an angular velocity bias error in real time processing in time series, and updating the estimated value of the angular velocity bias using the angular velocity bias error,
The integrated navigation calculation means estimates the angular velocity after correcting the angular velocity bias by removing the estimated value of the angular velocity bias updated by the angular velocity bias temperature fluctuation updating means and the calculation means from the detection value of the angular velocity sensor. And

  With this configuration, the estimated value of the angular velocity bias can be updated during a period in which the positioning signal can be received even when the moving body is moving.

Temperature characteristic detecting means before Symbol angular velocity bias, and when the stop time of the moving object exceeds a predetermined time, and when the value detected by the temperature sensor during the stop of the movable body exceeds a predetermined temperature variation width When both or any one of them is satisfied, the temperature characteristic of the angular velocity bias is obtained or regarded as an effective value.

  As a result, the temperature characteristic of the angular velocity bias that can be applied under a somewhat wide temperature fluctuation range is obtained. Therefore, the angular velocity bias can be corrected using the temperature characteristic of the angular velocity bias with higher accuracy. In addition, when the temperature characteristics of the angular velocity bias is obtained as a function of temperature, the detection result of the temperature characteristics of the angular velocity bias is not updated under a condition where the temperature fluctuation range is small, so that the accuracy of detecting the temperature characteristics of the angular velocity bias can be improved. .

Also, the temperature characteristic detection means of the angular velocity bias, obtains an approximate expression of the angular velocity bias to temperature changes within the variation range of the detected value by the temperature sensor, and the angular velocity bias the best value above the temperature of the variation range The angular velocity bias value at the maximum temperature in the variation range is determined, and the angular velocity bias is determined as the angular velocity bias value at the minimum temperature in the variation range at a temperature equal to or lower than the minimum value in the variation range.

  For example, the temperature characteristic detecting means of the angular velocity bias obtains the 0th order coefficient, the first order coefficient, etc. of the function when the change of the angular velocity bias with respect to the temperature change is obtained as a function of the temperature. Alternatively, a relationship table of angular velocity bias with respect to temperature is created.

  As a result, an angular velocity bias temperature characteristic close to the true value can be applied at a temperature that has not yet been experienced, and an angular velocity bias that uses the temperature characteristic of the angular velocity bias with a predetermined accuracy can be obtained even at a temperature outside the above temperature fluctuation range.

  According to the present invention, since the angular velocity bias can be estimated in consideration of the temperature fluctuation, the angular velocity detection accuracy and the navigation data using the angular velocity can be obtained with high accuracy. In addition, a highly accurate angular velocity can be estimated immediately after the start of the integrated navigation calculation, and the responsiveness can be improved.

  The configuration of the navigation apparatus of the present invention is shown in FIG. As shown in FIG. 2, the navigation device 100 includes a GPS receiver 11, an angular velocity sensor 13 including a vibrating gyroscope, a temperature sensor 14, an acceleration sensor 12, and an integrated calculation unit 30 including a CPU and the like. It is mounted on a moving body.

  The GPS receiver 11 receives a positioning signal transmitted from a GPS satellite, which is a navigation satellite, and outputs a GPS positioning signal.

  The acceleration sensor 12 detects the acceleration in the three orthogonal directions of the moving body. The angular velocity sensor 13 detects the angular velocity in the three orthogonal directions of the moving body. The temperature sensor 14 detects the temperature of the angular velocity sensor 13 or the temperature of the environment where the angular velocity sensor 13 exists.

  If the calculation processing content is made into a block, the integrated calculation unit 30 is represented by a tracking processing unit 20, a GPS / INS calculation unit 21, an angular velocity bias temperature variation parameter estimation unit 22, and an angular velocity bias temperature variation parameter backup unit 23. be able to.

  The tracking processing unit 20 receives a GPS positioning signal from the GPS receiving circuit 11 and tracks the phase of a baseband GPS positioning signal obtained by receiving a signal from each GPS satellite, and also includes a pseudorange (PR) and Doppler. Obtain frequency observations, position / velocity of each satellite, etc.

  The GPS / INS calculation unit 21 obtains the position / velocity of the reception point based on the pseudorange and Doppler frequency information, the position / velocity of each satellite, and the like. Further, GPS / INS integration calculation is performed based on the pseudo distance, Doppler frequency information, and detection signals of the angular velocity sensor and the acceleration sensor.

  Based on the speed information output from the GPS / INS calculation unit 21, the angular velocity bias temperature characteristic detection unit 22 uses a method described later to detect the angular velocity bias temperature characteristic (temperature, as will be described later). When the change of the angular velocity bias with respect to the change is obtained as a function of temperature, a 0th order coefficient, a first order coefficient, etc. of the function are obtained and written to the backup unit 23 together with information on the valid / invalid state.

  The GPS / INS calculation unit 21 performs GPS / INS integrated positioning calculation, and detects the temperature characteristics of the angular velocity bias based on the angular velocity obtained by the integrated positioning calculation, the detection value of the temperature sensor 14, and the detection value of the angular velocity sensor 13. To do. This means corresponds to “angular velocity bias temperature characteristic detecting means”.

  The GPS / INS calculation unit 21 detects the temperature fluctuation amount of the angular velocity bias based on the detection value of the temperature sensor and the temperature characteristic of the angular velocity bias at a predetermined timing, and uses the temperature fluctuation amount to estimate the angular velocity bias. Update. This means corresponds to “angular velocity bias temperature fluctuation updating means”.

  The GPS / INS calculation unit 21 estimates the angular velocity bias error in real time in a time series by the Kalman filter calculation means, and updates the estimated value of the angular velocity bias using the angular velocity bias error. This means corresponds to “Kalman filter calculation means”.

  Then, the GPS / INS calculation unit 21 estimates the angular velocity after the angular velocity bias correction by removing the updated estimated value of the angular velocity bias from the detected value of the angular velocity sensor 13.

  A speed sensor may be provided instead of the acceleration sensor 12. A speed sensor may be provided together with the acceleration sensor.

The contents of the processing of the integrated arithmetic unit 30 shown in FIG. 2 are shown as a flowchart in FIG.
When the temperature characteristics data of angular velocity bias has not been backed up at the time of shipment from the factory, etc. (invalid state), the initial value for estimation of angular velocity bias in the Kalman filter, etc. is the nominal value determined by the specifications of the angular velocity sensor Is set as an initial value (S1->S2-> S3). Then, GPS / INS integration calculation is performed (S4). The process of step S3 is only once, and once the angular velocity bias is obtained by GPS / INS calculation, the value is used as an initial value when starting a new GPS / INS calculation (integrated navigation calculation) ( S2 → S4).

  When the vehicle is stopped, the temperature characteristic data of the angular velocity bias accompanying the temperature change is detected using the detection value of the temperature sensor 14 and the detection value of the angular velocity sensor 13, and is backed up as effective temperature characteristic data when a predetermined condition is satisfied. A flag indicating that the temperature characteristic data stored or obtained in the unit 23 is valid is set. (S5 → S6). This predetermined condition will be described later.

  For example, when the temperature characteristic data of the angular velocity bias stored in the backup unit 23 is valid at the time of power-on other than the factory shipment, the calculation is performed based on the detected value of the temperature sensor and the temperature characteristic of the angular velocity bias. The temperature-dependent angular velocity bias is removed from the detected value of the angular velocity sensor, an angular velocity including only the temperature-independent angular velocity bias is calculated, and this is set as the initial value of the angular velocity bias estimation in the Kalman filter or the like (S1). → S7 → S8). This process corresponds to “angular velocity bias initial value setting means” of the present invention.

  Thereafter, GPS / INS calculation (integrated navigation calculation) is performed (S9). The processing in step S9 corresponds to “integrated navigation calculation means” of the present invention. Specifically, during the period when the GPS positioning signal cannot be received, the angular velocity is calculated based on the angular velocity bias obtained by removing the temperature-dependent angular velocity bias from the detection value of the angular velocity sensor 13, and the period during which the GPS positioning signal can be received is a predetermined timing. (For example, when the temperature changes by a certain value or every certain time), the temperature fluctuation amount of the angular velocity bias is detected based on the detected value of the temperature sensor 14 and the temperature characteristic of the angular velocity bias, and only this temperature fluctuation amount is detected. Update the estimated angular velocity bias. Further, the integrated navigation calculation is performed using the GPS positioning signal, and the angular velocity bias estimated by the Kalman filter calculation is updated by the temperature fluctuation. The Kalman filter estimates an angular velocity bias error in real time processing in time series, and estimates a temperature-independent angular velocity bias using the angular velocity bias error.

  In this way, the processing shown in FIG. 3 is repeated, and the angular velocity bias is sequentially estimated in time series by the GPS / INS calculation in step S9.

  The angular velocity bias estimated in the above time series is backed up and used as an initial value when the temperature characteristic data of the angular velocity bias is invalid.

  Next, an example of the processing contents of steps S8 and S9 in FIG. 3 will be shown for the case where the GPS positioning signal can be received and the case where the GPS positioning signal cannot be received.

  For example, assuming an automobile as a moving body, after traveling outdoors where GPS positioning signals can be received, parked in an indoor parking lot, and exited after a long time has elapsed, the following operation is performed.

  (1) Before entering the parking lot, in step S9, GPS / INS integrated navigation calculation is performed based on the detected values of the acceleration sensor 12, the angular velocity sensor 13, the temperature sensor 14, and the GPS positioning signal. That is, the position and speed of the moving body are obtained by integrating the inertial navigation calculation using the acceleration detection value of the acceleration sensor 12 and the GPS navigation calculation.

  Also, the angular velocity bias is estimated in real time. That is, at a predetermined timing, the temperature fluctuation amount of the angular velocity bias is detected based on the detected value of the temperature sensor and the temperature characteristic of the angular velocity bias, and the estimated value of the angular velocity bias is updated. Then, the angular velocity bias estimated by the Kalman filter calculation is updated based on the angular velocity bias corrected for the temperature fluctuation.

  The detected value of the angular velocity sensor is corrected with the angular velocity bias obtained in this way, and the azimuth of the moving body is obtained by accurate angular velocity integration, and the moving azimuth of the moving body and the moving azimuth of the moving body obtained by the GPS navigation calculation are calculated. The exact orientation of the moving object is obtained by integration of.

  (2) Since the GPS positioning signal cannot be received when entering the indoor parking lot, the position and speed of the moving body are obtained by inertial navigation calculation using the acceleration detection value of the acceleration sensor 12 in step S9. Further, the azimuth of the moving body is obtained by integration of the angular velocity (temperature corrected) obtained by removing the temperature dependent component from the detected value of the angular velocity sensor 13.

  (3) When parking after a long time has elapsed after parking, for example, when parking at noon and leaving at night, based on the detected value of the angular velocity sensor, the detected value of the temperature sensor, and the temperature characteristics of the angular velocity bias The calculated angular velocity bias is given as the initial value of the angular velocity bias at the time of inertial navigation calculation. Thereafter, until the GPS positioning signal is received, the position / velocity / orientation of the moving body is estimated by inertial navigation calculation as in (2) above.

  Thus, when the temperature difference between parking and leaving is large, the angular velocity bias becomes larger than when parking, but the angular velocity calculated based on the detected value of the angular velocity sensor, the detected value of the temperature sensor, and the temperature characteristics of the angular velocity bias. By giving the bias as an initial value of the angular velocity bias at the time of the integrated navigation calculation and performing the inertial navigation calculation, a more accurate moving body orientation can be obtained.

  (4) After that, when the GPS positioning signal can be received, the integrated navigation calculation is started. In step S8, the value of the most recent angular velocity bias that has already been obtained is given as the initial value of the angular velocity bias of the Kalman filter.

Next, a specific example of temperature characteristic data estimation of the angular velocity bias will be shown with reference to FIG.
Whether the speed obtained as the integrated estimated value or the speed obtained from the GPS data is less than a threshold value (for example, less than 0.1 m / s) is determined whether the vehicle is stopped / moved. The sensor detection values are sequentially stored in pairs, and the parameters of the approximate expression (function) are calculated by the least square method for the relationship between the two. A parameter representing this approximate expression is temperature characteristic data of the angular velocity bias.

  In FIG. 4, the horizontal axis represents the detection value of the temperature sensor, the vertical axis represents the detection value of the angular velocity sensor, and these detection values are plotted. Here, the slope of the approximated straight line is the primary coefficient of the parameter of the coefficient of variation of the angular velocity bias. Further, the angular velocity at an approximate straight line reference temperature (for example, 25 ° C.) is the zeroth-order coefficient of the parameter of the variation coefficient of the angular velocity bias. In this way, temperature characteristic data of the angular velocity bias is obtained.

  The following [Equation 1] shows how to determine the temperature fluctuation of the angular velocity bias in the temperature range of the approximate straight line shown in FIG.

  Note that the linear coefficient approximated by a straight line is not always used for calculating the temperature fluctuation of the angular velocity bias in the temperature range that has been experienced. You may use the partial differential coefficient in the vicinity of the observed temperature calculated | required as [Equation 2] from the approximated curve more than quadratic.

  FIG. 5 shows how the angular velocity bias is determined at a temperature lower than the lowest temperature shown in FIG. 4 and higher than the highest temperature.

  In this example, the temperature fluctuation of the angular velocity bias takes a certain value in the temperature range that has been experienced, but is zero at an inexperienced temperature. That is, zero is set at a temperature lower than the lowest temperature, or zero is set at a temperature higher than the highest temperature. This is because there is no guarantee that the accuracy is improved by temperature compensation by applying the calculated value using the first-order coefficient as it is at an inexperienced temperature.

  The data to be backed up in the backup unit 23 shown in FIG. 2 includes the 0th order coefficient and the 1st order coefficient of the temperature characteristic data of the angular velocity bias, the maximum temperature / minimum temperature experienced when estimating the temperature characteristic data of the angular velocity bias, and the temperature. This is a flag for valid / invalid state of characteristic data (0th order coefficient / first order coefficient).

  The above-described validity / invalidity determination of the temperature characteristic data of the angular velocity bias is performed based on whether or not the range of the experienced temperature fluctuation is somewhat wide. For example, it is determined that the temperature characteristic data of the angular velocity bias is valid when both of the following two conditions are satisfied.

<Condition A> When the time experienced when obtaining the temperature characteristic data of the angular velocity bias exceeds a set condition (for example, 10 minutes).
<Condition B> When the temperature fluctuation range experienced when obtaining the temperature characteristic data of the angular velocity bias exceeds the set condition (for example, 10 ° C.).

  In addition, depending on the setting conditions of time and temperature, you may determine by satisfy | filling either the said conditions A or the conditions B. FIG.

It is a block diagram which shows the structure of the vehicle position detection apparatus which concerns on patent document 1. FIG. It is a block diagram which shows the structure of the navigation apparatus which concerns on embodiment of this invention. It is a flowchart which shows the content of the process of the integrated calculating part 30 shown in FIG. It is a figure which shows the example of the estimation method of the temperature characteristic data of an angular velocity bias. FIG. 5 is a diagram showing how the angular velocity bias is determined at a temperature lower than the lowest temperature and higher than the highest temperature shown in FIG. 4.

Explanation of symbols

DESCRIPTION OF SYMBOLS 11 ... GPS receiver 12 ... Acceleration sensor 13 ... Angular velocity sensor 14 ... Temperature sensor 20 ... Tracking processing unit 21 ... GPS / INS calculation unit 22 ... Angular velocity bias temperature characteristic detection unit 23 ... Backup unit 30 ... Integrated calculation unit 100 ... Navigation device

Claims (4)

In a navigation apparatus provided with integrated navigation calculation means for performing integrated navigation calculation based on positioning signals transmitted from navigation satellites and external support data including detection values of angular velocity sensors provided in a moving body,
A temperature sensor for detecting the temperature of the angular velocity sensor or the temperature of the environment in which the angular velocity sensor exists;
An angular velocity bias temperature characteristic detection means for obtaining a temperature characteristic of the angular velocity bias based on a detection value of the angular velocity sensor and a detection value of the temperature sensor at least when the moving body is stopped;
The integrated navigation calculation means includes:
During a period when the positioning signal cannot be received ,
Detection value before Symbol angular rate sensor, a detection value of the temperature sensor, and calculates the angular velocity based on the temperature characteristics of the angular velocity bias,
In a period that can receive before Symbol positioning signal,
The most recent angular velocity bias calculated based on the detected value of the temperature sensor and the temperature characteristics of the angular velocity bias is set as the initial value of the angular velocity bias of the integrated navigation calculation, and the angular velocity bias and the angular velocity are determined based on the result of the integrated navigation calculation. Estimate the navigation device. The integrated navigation calculation means includes:
An angular velocity bias temperature variation update that detects an angular velocity bias temperature fluctuation amount based on a detected value of the temperature sensor and a temperature characteristic of the angular velocity bias at a predetermined timing, and updates an estimated angular velocity bias value using the temperature fluctuation amount. Means,
When estimating the angular velocity bias error in real-time processing in sequence, and a computation means to update the estimated value of the angular velocity bias with angular velocity bias error,
The integrated navigation calculation means estimates the angular velocity after the angular velocity bias correction by removing the estimated value of the angular velocity bias updated by the angular velocity bias temperature fluctuation updating means and the calculation means from the detected value of the angular velocity sensor. The navigation device according to claim 1. The angular velocity bias temperature characteristic detecting means is both when the stop time of the moving body exceeds a predetermined time and when the detection value by the temperature sensor during the stop of the moving body exceeds a predetermined temperature fluctuation range or The navigation apparatus according to claim 1 or 2 , wherein when either of the conditions is satisfied, a temperature characteristic of the angular velocity bias is obtained or regarded as an effective value. The angular velocity bias temperature characteristic detecting means obtains an approximate expression of an angular velocity bias with respect to a temperature change within a variation range of a detection value by the temperature sensor, and at a temperature equal to or higher than a maximum value of the variation range, the angular velocity bias is determined within the variation range. defined angular bias value at the highest temperature, said lowest value below the temperature of the variation range defining said angular bias to the value of the angular velocity bias at the lowest temperature of the variation range, according to claim 1 Navigation equipment.

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