JP2011102784A - Apparatus, method, and program for detection of inclination angle - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide a technology for highly accurately detecting an inclination angle by highly accurately computing an offset of an acceleration sensor. <P>SOLUTION: An acceleration sensor 12 acquires an acceleration signal, and a speed sensor 10 acquires a speed signal. An error setting part 14 sets an measurement error of the acceleration sensor 12. A gain computation part 24 and a state variable update part 26 updates the inclination angle of a vehicle and the offset of the acceleration sensor 12 by performing Kalman filter processing on the basis of the measurement error of the acceleration sensor 12, the acceleration signal, and the speed signal. The error setting part 14 sets the measurement error of the acceleration sensor 12 on the basis of the speed signal and the updated inclination angle of the vehicle. <P>COPYRIGHT: (C)2011,JPO&INPIT

Description

  The present invention relates to an inclination angle detection technique, and more particularly to an inclination angle detection device, an inclination angle detection method, and an inclination angle detection program for detecting an inclination angle of a vehicle.

  Conventionally, a car navigation apparatus combines a GPS (Global Positioning System) capable of obtaining an absolute position and a self-contained navigation that obtains a relative position calculated from a sensor such as a gyroscope or a speed pulse to obtain a vehicle position and traveling direction. Is calculated. In the self-contained navigation, it is possible to calculate a more accurate position by taking into account the attitude angle of the vehicle including the road inclination. In order to calculate the attitude angle of the vehicle, Kalman filter processing has been conventionally performed based on an acceleration signal corresponding to the longitudinal acceleration of the vehicle and a distance signal corresponding to the moving distance of the vehicle (for example, Patent Document 1).

  Here, the acceleration signal is output from the acceleration sensor, and the acceleration sensor outputs a voltage called offset or bias even when the acceleration is zero. In order to improve the accuracy of the acceleration detected by the acceleration sensor, it is required to improve the accuracy of deriving the offset of the acceleration sensor. The offset of the acceleration sensor is calculated, for example, by performing Kalman filter processing using the offset of the acceleration sensor as one of the elements of the state variable (see, for example, Patent Document 2).

JP 2003-75172 A JP 2000-346661 A

  When the offset of the acceleration sensor is not directly calculated by the Kalman filter process but is indirectly calculated using a parameter including a plurality of errors, it is difficult to improve the accuracy of calculating the offset of the acceleration sensor. In addition, even if the acceleration sensor offset is directly calculated by Kalman filter processing, if the Kalman filter processing is executed using only the speed that is not directly related to the acceleration sensor offset as the observed value, the accuracy of the acceleration sensor offset calculation is improved. It becomes difficult to make.

  Also, assuming that the occurrence probability of acceleration and deceleration of the vehicle is the same, and the occurrence probability of up and down is the same, if the output of the acceleration sensor is averaged over a sufficiently long period, the average value will be It is considered close to the offset. As described above, since the output of the acceleration sensor is related to the offset of the acceleration sensor, it is possible to execute the Kalman filter process using the output of the acceleration sensor as one of the observed values. However, when the vehicle stops, or when the vehicle travels on an inclined road where the vehicle goes up or down at a low speed, the gravity component is continuously superimposed on the output of the acceleration sensor. As a result, local deviation occurs with respect to the offset of the true acceleration sensor. For this reason, it is difficult to calculate the offset of the acceleration sensor with high accuracy, or the offset of the acceleration sensor is locally biased depending on the driving conditions.

  The present invention has been made in view of such circumstances, and an object thereof is to provide a technique for detecting an inclination angle with high accuracy by calculating an offset of an acceleration sensor with high accuracy.

  In order to solve the above problems, an inclination angle detection device according to an aspect of the present invention includes a first acquisition unit that acquires an acceleration signal corresponding to acceleration in the front-rear direction of a vehicle from an acceleration sensor mounted on the vehicle, A second acquisition unit that acquires a speed signal corresponding to the moving speed of the vehicle, a setting unit that sets an observation error of the acceleration sensor, an observation error of the acceleration sensor set in the setting unit, An update unit that updates the vehicle tilt angle and the offset of the acceleration sensor by executing Kalman filter processing based on the acceleration signal acquired in the first acquisition unit and the speed signal acquired in the second acquisition unit. Prepare. The setting unit sets the observation error of the acceleration sensor based on the speed signal acquired by the second acquisition unit and the vehicle inclination angle already updated by the updating unit.

  According to this aspect, since the observation error is set based on the speed signal and the tilt angle, and the tilt angle and the offset are updated based on the observation error, the tilt angle reflecting the speed signal and the tilt angle Offset can be detected.

  The setting unit may set the observation error of the acceleration sensor so that the speed signal acquired by the second acquisition unit decreases when the speed signal increases, and increases when the vehicle inclination angle already updated by the update unit increases. In this case, when the vehicle travels on an inclined road where the ascending or descending is continued at a low speed, the gravitational component is continuously superimposed on the acceleration sensor, and the inclination angle is detected accurately due to the deviation from the true offset. Deterioration can be suppressed.

  The setting unit sets the observation error of the acceleration sensor so as to be proportional to the reciprocal of the addition value of the speed signal acquired by the second acquisition unit and a predetermined constant, and to be proportional to the vehicle inclination angle already updated by the updating unit. May be. In this case, since a predetermined constant is added to the speed signal, division by zero can be prevented even if the speed signal becomes zero.

  You may further provide the comparison part which compares the speed signal acquired in the 2nd acquisition part with a threshold value. When the speed signal acquired in the second acquisition unit is smaller than the threshold value as a result of the comparison in the comparison unit, the update unit performs the calculation on the acceleration signal acquired in the first acquisition unit instead of deriving the Kalman gain for the acceleration sensor. The Kalman gain may be set to a predetermined value. In this case, if the speed signal is small, the Kalman gain for the acceleration signal is set to a predetermined value, so that the processing amount can be reduced while suppressing deterioration in accuracy.

  Another aspect of the present invention is also a tilt angle detection device. The apparatus includes a first acquisition unit that acquires an acceleration signal corresponding to the longitudinal acceleration of the vehicle from an acceleration sensor mounted on the vehicle, and a speed corresponding to the moving speed of the vehicle from the speed sensor mounted on the vehicle. A second acquisition unit that acquires a signal, a setting unit that sets an observation error of the acceleration sensor so as to decrease when the velocity signal acquired by the second acquisition unit increases, and an observation error of the acceleration sensor that is set by the setting unit An update unit that updates the vehicle tilt angle and the acceleration sensor offset by executing Kalman filter processing based on the acceleration signal acquired in the first acquisition unit and the speed signal acquired in the second acquisition unit; .

  According to this aspect, since the observation error is set according to the speed signal, the tilt angle and the offset reflecting the speed signal can be detected.

  Yet another embodiment of the present invention is a tilt angle detection method. In this method, an acceleration signal corresponding to the longitudinal acceleration of the vehicle is acquired from an acceleration sensor mounted on the vehicle, and a speed signal corresponding to the moving speed of the vehicle is acquired from a speed sensor mounted on the vehicle. The step of setting the observation error of the acceleration sensor, the observation error of the acceleration sensor, the acceleration signal, and the velocity signal, and executing the Kalman filter processing to thereby offset the vehicle tilt angle and the acceleration sensor offset. And updating. In the setting step, the observation error of the acceleration sensor is set based on the speed signal and the already updated vehicle inclination angle.

  Yet another embodiment of the present invention is also a tilt angle detection method. In this method, an acceleration signal corresponding to the longitudinal acceleration of the vehicle is acquired from an acceleration sensor mounted on the vehicle, and a speed signal corresponding to the moving speed of the vehicle is acquired from a speed sensor mounted on the vehicle. The step of setting the observation error of the acceleration sensor so as to decrease when the velocity signal increases, and by performing the Kalman filter processing based on the observation error of the acceleration sensor, the acceleration signal, and the velocity signal Updating the vehicle tilt angle and the offset of the acceleration sensor.

  It should be noted that any combination of the above-described constituent elements and a conversion of the expression of the present invention between a method, an apparatus, a system, a recording medium, a computer program, etc. are also effective as an aspect of the present invention.

  According to the present invention, the inclination angle can be detected with high accuracy by calculating the offset of the acceleration sensor with high accuracy.

It is a figure which shows the structure of the inclination-angle detection apparatus which concerns on Example 1 of this invention. It is a figure which shows the operation state of the vehicle carrying the inclination-angle detection apparatus of FIG. It is a flowchart which shows the estimation procedure in the inclination-angle detection apparatus of FIG. It is a flowchart which shows the Kalman filter process sequence in the inclination-angle detection apparatus of FIG. It is a figure which shows the structure of the inclination-angle detection apparatus which concerns on Example 2 of this invention.

Example 1
Before describing the present invention specifically, an outline will be given first. Embodiment 1 of the present invention relates to a tilt angle detection device that detects a tilt angle of a vehicle in a self-contained navigation with a car navigation device. The tilt angle detection apparatus according to the first embodiment executes the following processing in order to detect the offset of the acceleration sensor with high accuracy and also detect the tilt angle with high accuracy. The tilt angle detection device acquires an acceleration signal from the acceleration sensor and also acquires a speed signal from the speed sensor. The tilt angle detection device calculates the tilt angle of the vehicle and the offset of the acceleration sensor by executing Kalman filter processing based on the speed signal, the acceleration signal, and the observation error.

  Here, the tilt angle detection device sets an observation error so that it decreases as the velocity signal increases and increases as the tilt angle calculated in the past increases, and is used for the Kalman filter processing. Also, the observation error is updated with the newly calculated tilt angle. By setting the observation error in this way, when the vehicle travels on an inclined road where the ascending or descending is continued at a low speed, the gravitational component is continuously superimposed on the acceleration sensor to cause a deviation from the true offset. The deterioration of the accuracy of the inclination angle due to is suppressed.

  FIG. 1 shows a configuration of an inclination angle detection apparatus 100 according to Embodiment 1 of the present invention. The tilt angle detection device 100 includes a speed sensor 10, an acceleration sensor 12, an error setting unit 14, and a state estimation unit 16. The state estimation unit 16 includes an estimated value calculation unit 20, an observation residual calculation unit 22, a gain calculation unit 24, a state variable update unit 26, and a state variable storage unit 28. The tilt angle detection device 100 is mounted on a vehicle (not shown).

  The speed sensor 10 acquires a speed signal corresponding to the moving speed of the vehicle. The speed sensor 10 is installed in the middle of the speedometer cable that rotates in response to the rotation of the drive shaft. After detecting the speed pulse signal accompanying the rotation of the drive shaft, the speed sensor 10 measures the number of vehicle speed pulses per unit time. To obtain a speed signal. Here, the vehicle speed pulse signal corresponds to a pulse generated every predetermined distance. The speed sensor 10 may directly acquire a speed signal from the GPS. The speed sensor 100 outputs a vehicle speed signal.

  The acceleration sensor 12 acquires an acceleration signal corresponding to the acceleration in the longitudinal direction of the vehicle. Here, FIG. 2 is used to explain the acceleration signal. FIG. 2 shows an operation state of the vehicle on which the tilt angle detection device 100 is mounted. The vehicle 50 is equipped with an inclination angle detection device 100 (not shown). In addition, the vehicle 50 moves on the road surface 54. Here, it is assumed that the sensitive axis 56 of the acceleration sensor 12 (not shown) mounted on the vehicle 50 is parallel to the road surface 54 and coincides with the longitudinal direction of the vehicle 50. Further, the sensitive shaft 56 and the road surface 54 are inclined with respect to the horizontal plane 52 by an inclination angle θ. In the acceleration signal, the moving acceleration of the vehicle 50 and the gravity component corresponding to the inclination angle θ formed by the sensitive axis 56 and the horizontal plane 52 are superimposed. Returning to FIG. The acceleration sensor 12 outputs an acceleration signal.

ここで、上付きの添え字Ｔは、ベクトルまたは行列の転置を示す。前述のごとく、下付きの添え字ｎはタイミングｎを示す。 The estimated value calculator 20 receives the acceleration signal a _OUT from the acceleration sensor 12. The acceleration signal at timing n is assumed to be a _OUTn . Here, a state variable xn at timing _n is defined. The state variable x _n includes three elements: a speed v _n , a tilt angle θ _n , and an acceleration offset a _OFSn as in the equation (1).

Here, the superscript T indicates a transposition of a vector or a matrix. As described above, the subscript n indicates the timing n.

ここで、入力ｕ_ｎは、加速度信号ａ_ＯＵＴｎである。

また、式（２）におけるシステム行列Ａと入力行列Ｂとは、式（４）および式（５）のように示される。

ここで、ｇは重力加速度、ｋは加速度信号から加速度単位（例えばｍ／ｓ^２）への変換係数、ΔＴはサンプリング間隔を示す。 Estimated value calculating section 20 includes an input u _n, 1 single previous state variables, i.e. on the basis of the state variable x _n-1 at the timing n-1, calculates the equation of state shown in equation (2) Thus, an estimated value x _n ′ at timing n is calculated. The state variable x _n−1 is input from the state variable storage unit 28.

Here, the input _{u n} is the acceleration signal _{a OUTn.}

Further, the system matrix A and the input matrix B in Expression (2) are expressed as Expression (4) and Expression (5).

Here, g is a gravitational acceleration, k is a conversion coefficient from an acceleration signal to an acceleration unit (for example, m / s ² ), and ΔT is a sampling interval.

ここで、出力行列Ｃは式（７）のように示される。

The observation residual calculation unit 22 inputs a speed signal from the speed sensor 10, inputs an acceleration signal from the acceleration sensor 12, and inputs an estimated value x _n ′ from the estimated value calculation unit 20. The observation residual calculator 22 defines the observation value z _n using the velocity signal v _n and the acceleration signal a _OUTn as components. Observation difference computation unit 22, as the equation (6), the velocity and acceleration of the state variables extracted from the estimated value x _{n 'with} respect to the offset, the observation residuals y _n of the observed value z _n To derive.

Here, the output matrix C is expressed as shown in Equation (7).

The error setting unit 14 inputs a speed signal from the speed sensor 10 and inputs an estimated value (hereinafter referred to as “tilt angle”) of the tilt angle of the vehicle 50 from the state variable update unit 26. Although details will be described later, the inclination angle is sequentially updated in the state variable update unit 26, and the previous inclination angle, that is, the inclination angle θ _n-1 at the timing _n−1 is input to the error setting unit 14. The Error setting unit 14, based on the speed signal and the previous inclination angle to set the observation error .delta.a _n of the acceleration sensor 12 at the timing n. Here, the error setting unit 14 sets the observation error of the acceleration sensor 12 so as to decrease as the speed signal increases and to increase as the previous tilt angle increases.

ここで、αは定数である。所定の定数βは、速度信号ｖ_ｎがゼロの場合に、加速度センサ１２の観測誤差δａ_ｎが無限大になることを防ぐために設けられている。また、誤差設定部１４は、速度センサ１０の観測誤差δｖ_ｎを一定の値として設定する。誤差設定部１４は、加速度センサ１２の観測誤差δａ_ｎと速度センサ１０の観測誤差δｖ_ｎとを出力する。 More specifically, the error setting unit 14, as the equation (8), proportional to the reciprocal of the sum of the velocity signals v _n and a predetermined constant beta, and is proportional to the previous inclination angle theta _n-1 setting the observation error .delta.a _n of the acceleration sensor 12 as.

Here, α is a constant. The predetermined constant beta, velocity signal v _n is in the case of zero is provided to prevent the observation error .delta.a _n of the acceleration sensor 12 becomes infinite. The error setting unit 14 sets the observation error .delta.v _n speed sensor 10 as a constant value. Error setting unit 14 outputs the observation error .delta.v _n of the observation error .delta.a _n and the speed sensor 10 of the acceleration sensor 12.

ゲイン演算部２４は、共分散行列Ｒ_ｎとシステム誤差とをもとに、カルマンフィルタのゲインＫ_ｎを演算する。ここで、共分散行列Ｒ等からカルマンフィルタのゲインの導出には、公知の技術が使用されればよい。 Gain calculator 24 inputs the observation error .delta.v _n of the observation error .delta.a _n and the speed sensor 10 of the acceleration sensor 12, as these observation error represents the standard deviation, a covariance matrix R _n Formula (9) Derived as follows.

The gain calculation unit 24 calculates a Kalman filter gain K _n based on the covariance matrix R _n and the system error. Here, a known technique may be used to derive the gain of the Kalman filter from the covariance matrix R or the like.

Known techniques are described, for example, in MOHINDER S.M. GREWAL, ANGUS P. It is shown on pages 116 to 120 of ANDREWS, “Kalman Filtering: Theory and Practice Using MATLAB”, A Wiley-Interscience Publication. The gain calculation unit 24 derives a gain formed by six components as shown in Expression (10).

State variable updating unit 26 receives the observation residuals y _n observations difference computation unit 22 receives the estimated value x _{n 'from} the estimated value computation unit 20, and inputs the gain K _n from the gain calculation unit 24. State variable updating unit 26, the estimated value _{x n} ', based on the observation residuals _{y n} and the gain _{K n,} by calculating the equation (11) updates the state variable _{x n.}

Smaller gain K _n is greater the weight of the estimated value x _{n ',} the larger the gain K _n is a large observation weights residuals y _n. Expression (11) represents that x _n '+ K _n y _n is newly substituted for x _n . The above processing can be said to update the inclination angle of the vehicle 50 and the offset of the acceleration sensor 12 by executing the Kalman filter processing based on the observation error of the acceleration sensor 12, the acceleration signal, and the velocity signal. . The state variable update unit 26 outputs the updated state variable x _n , particularly the inclination angle θ _n, and feeds back the updated state variable x _n to the error setting unit 14 and the state variable storage unit 28.

The state variable storage unit 28 receives the state variable _xn from the state variable update unit 26 and stores the state variable _xn . The state variable storage unit 28 outputs the state variable _xn to the estimated value calculation unit 20. Further, the inclination angle updated by the state variable update unit 26 is used, for example, for correcting the gyro sensitivity (voltage-angular velocity conversion coefficient), and thereby, the turning angle on the inclined road is derived with high accuracy. It becomes possible.

  This configuration can be realized in terms of hardware by a CPU, memory, or other LSI of any computer, and in terms of software, it can be realized by a program loaded in the memory, but here it is realized by their cooperation. Draw functional blocks. Accordingly, those skilled in the art will understand that these functional blocks can be realized in various forms by hardware only, software only, or a combination thereof.

  The operation of the tilt angle detection apparatus 100 having the above configuration will be described. FIG. 3 is a flowchart showing an estimation procedure in the tilt angle detection apparatus 100. The tilt angle detection apparatus 100 acquires a speed signal from the speed sensor 10 (S10), and acquires an acceleration signal from the acceleration sensor 12 (S12). The tilt angle detection apparatus 100 executes the Kalman filter process (S14) and outputs the tilt angle (S16). If the process is continued (Y in S18), the process returns to step 10. If the process is not continued (N in S18), the process is terminated.

  FIG. 4 is a flowchart showing a Kalman filter processing procedure in the tilt angle detection apparatus 100. This corresponds to step 14 in FIG. The estimated value calculation unit 20 acquires the previous state variable (S30), and derives an estimated value (S32). The observation residual calculation unit 22 derives an observation residual (S34). The error setting unit 14 sets an observation error (S36), and the gain calculation unit 24 calculates a gain (S38). The state variable update unit 26 updates the state variable (S40). The state variable storage unit 28 stores the updated state variable (S42).

  According to the embodiment of the present invention, the observation error is set based on the velocity signal and the inclination angle, and the inclination angle and the offset are updated based on the observation error, so that the velocity signal and the inclination angle are reflected. The tilt angle and offset can be detected. In addition, since the observation error is set to be proportional to the tilt angle and inversely proportional to the speed signal, the vehicle travels on a sloping road that continues up or down at low speed, and gravity components are continuously superimposed on the acceleration sensor. Even if deviation occurs with respect to the true offset, it is possible to suppress the deterioration of the inclination angle detection accuracy. Moreover, since the deterioration of the accuracy of the inclination angle under a predetermined condition is suppressed, the detection accuracy of the inclination angle can be improved. Further, since a predetermined constant is added to the speed signal, division by zero can be prevented even if the speed signal becomes zero.

(Example 2)
A second embodiment of the present invention relates to a tilt angle detecting device for detecting a tilt angle, similarly to the first embodiment. The tilt angle detection apparatus according to the first embodiment derives the gain of the Kalman filter regardless of the value of the velocity signal, and executes the Kalman filter process. When the value of the speed signal is small, some gains are small to some extent. If such a gain value is small, the gain multiplication result is also small, so that the gain accuracy becomes less important. The purpose of the second embodiment is to reduce the amount of processing under such circumstances.

  FIG. 5 shows a configuration of the tilt angle detection apparatus 100 according to the second embodiment of the present invention. In the tilt angle detection apparatus 100 shown in FIG. 5, a determination unit 30 is added to the tilt angle detection apparatus 100 shown in FIG. Here, it demonstrates centering on the difference with FIG. The determination unit 30 receives a speed signal from the speed sensor 10. The determination unit 30 stores a threshold value in advance, and compares the speed signal with the threshold value. The threshold value is defined to correspond to a somewhat low speed, for example, 5 km / h. The determination unit 30 outputs the comparison result to the gain calculation unit 24.

  The gain calculation unit 24 inputs the comparison result from the determination unit 30. In the comparison result, if the speed signal is equal to or greater than the threshold value, the gain calculation unit 24 derives the gain as in the first embodiment. On the other hand, when the speed signal is smaller than the threshold value in the comparison result, the gain calculator 24 sets the gain for the acceleration signal to a predetermined fixed value instead of deriving the gain for the acceleration signal. The gain for the acceleration signal corresponds to the gain K32 in Expression (10). The gain calculation unit 24 sets the gain K32 to zero or a small value.

  According to the embodiment of the present invention, if the speed signal is small, the gain for the acceleration signal is set to a predetermined value, so that the processing amount can be reduced. Further, if the speed signal is small, the gain for the acceleration signal should be close to zero. Therefore, even if the gain is set to a predetermined value, deterioration of the inclination angle detection accuracy can be suppressed.

  In the above, this invention was demonstrated based on the Example. This embodiment is an exemplification, and it will be understood by those skilled in the art that various modifications can be made to the combination of each component and each processing process, and such modifications are also within the scope of the present invention. .

In the first and second embodiments of the present invention, the error setting unit 14 sets the observation error of the acceleration sensor 12 based on the speed signal and the tilt angle. However, the present invention is not limited to this. For example, the error setting unit 14 may set the observation error of the acceleration sensor 12 so as to decrease as the speed signal increases. Specifically, the observation error is set to be proportional to the reciprocal of the sum of the velocity signals v _n and a predetermined constant beta. According to this modification, since an observation error is set according to the speed signal, it is possible to detect an inclination angle and an offset reflecting the speed signal.

  DESCRIPTION OF SYMBOLS 10 Speed sensor, 12 Acceleration sensor, 14 Error setting part, 16 State estimation part, 20 Estimated value calculation part, 22 Observation residual calculation part, 24 Gain calculation part, 26 State variable update part, 28 State variable memory part, 30 Determination 100, an inclination angle detection device.

Claims (9)

A first acquisition unit that acquires an acceleration signal corresponding to the longitudinal acceleration of the vehicle from an acceleration sensor mounted on the vehicle;
A second acquisition unit that acquires a speed signal corresponding to a moving speed of the vehicle from a speed sensor mounted on the vehicle;
A setting unit for setting an observation error of the acceleration sensor;
By performing Kalman filter processing based on the observation error of the acceleration sensor set in the setting unit, the acceleration signal acquired in the first acquisition unit, and the velocity signal acquired in the second acquisition unit, An update unit that updates an inclination angle of the vehicle and an offset of the acceleration sensor;
The setting unit sets an observation error of the acceleration sensor based on the speed signal acquired by the second acquisition unit and the inclination angle of the vehicle already updated by the updating unit. Angle detection device.   The setting unit sets an observation error of the acceleration sensor so that the speed signal acquired by the second acquisition unit decreases when the speed signal increases, and increases when the inclination angle of the vehicle already updated by the update unit increases. The tilt angle detection apparatus according to claim 1, wherein   The acceleration sensor is proportional to the reciprocal of the added value of the speed signal acquired by the second acquisition unit and a predetermined constant, and is proportional to the inclination angle of the vehicle that has already been updated by the update unit. The tilt angle detection apparatus according to claim 2, wherein an observation error is set. A comparison unit for comparing the speed signal acquired in the second acquisition unit with a threshold value;
When the speed signal acquired in the second acquisition unit is smaller than a threshold value as a result of the comparison in the comparison unit, the update unit performs the first acquisition unit instead of deriving the Kalman gain for the acceleration sensor. 4. The tilt angle detection device according to claim 1, wherein a Kalman gain for the acquired acceleration signal is set to a predetermined value. A first acquisition unit that acquires an acceleration signal corresponding to the longitudinal acceleration of the vehicle from an acceleration sensor mounted on the vehicle;
A second acquisition unit that acquires a speed signal corresponding to a moving speed of the vehicle from a speed sensor mounted on the vehicle;
A setting unit that sets an observation error of the acceleration sensor so as to decrease when the velocity signal acquired in the second acquisition unit increases;
By performing Kalman filter processing based on the observation error of the acceleration sensor set in the setting unit, the acceleration signal acquired in the first acquisition unit, and the velocity signal acquired in the second acquisition unit, An updating unit for updating a vehicle inclination angle and an offset of the acceleration sensor;
An inclination angle detection device comprising: Obtaining an acceleration signal corresponding to the longitudinal acceleration of the vehicle from an acceleration sensor mounted on the vehicle;
Obtaining a speed signal corresponding to the moving speed of the vehicle from a speed sensor mounted on the vehicle;
Setting an observation error of the acceleration sensor;
Updating an inclination angle of the vehicle and an offset of the acceleration sensor by performing a Kalman filter process based on the observation error of the acceleration sensor, the acceleration signal, and the velocity signal;
The setting step includes setting an observation error of the acceleration sensor based on the speed signal and the already updated tilt angle of the vehicle. Obtaining an acceleration signal corresponding to the longitudinal acceleration of the vehicle from an acceleration sensor mounted on the vehicle;
Obtaining a speed signal corresponding to the moving speed of the vehicle from a speed sensor mounted on the vehicle;
Setting the observation error of the acceleration sensor to be small when the speed signal is large;
Updating an inclination angle of the vehicle and an offset of the acceleration sensor by executing a Kalman filter process based on the observation error of the acceleration sensor, the acceleration signal, and the velocity signal;
An inclination angle detection method comprising: Obtaining an acceleration signal corresponding to the longitudinal acceleration of the vehicle from an acceleration sensor mounted on the vehicle;
Obtaining a speed signal corresponding to the moving speed of the vehicle from a speed sensor mounted on the vehicle;
Setting an observation error of the acceleration sensor;
The computer executes a step of updating the vehicle inclination angle and the acceleration sensor offset by executing a Kalman filter process based on the observation error of the acceleration sensor, the acceleration signal, and the velocity signal. Let
The setting step includes setting an observation error of the acceleration sensor based on the speed signal and the already updated tilt angle of the vehicle. Obtaining an acceleration signal corresponding to the longitudinal acceleration of the vehicle from an acceleration sensor mounted on the vehicle;
Obtaining a speed signal corresponding to the moving speed of the vehicle from a speed sensor mounted on the vehicle;
Setting the observation error of the acceleration sensor to be small when the speed signal is large;
Updating an inclination angle of the vehicle and an offset of the acceleration sensor by executing a Kalman filter process based on the observation error of the acceleration sensor, the acceleration signal, and the velocity signal;
Tilt angle detection program for causing a computer to execute.

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