CN114018279A - Multi-sampling-rate data fusion attitude correction method for array sensor - Google Patents

Multi-sampling-rate data fusion attitude correction method for array sensor Download PDF

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CN114018279A
CN114018279A CN202111237885.3A CN202111237885A CN114018279A CN 114018279 A CN114018279 A CN 114018279A CN 202111237885 A CN202111237885 A CN 202111237885A CN 114018279 A CN114018279 A CN 114018279A
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accelerometer
sampling
acceleration
array sensor
attitude
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CN114018279B (en
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张春熹
卢鑫
杨艳强
刘炳琪
田龙杰
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24th Branch Of Pla 96901
Beihang University
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
    • G01C23/00—Combined instruments indicating more than one navigational value, e.g. for aircraft; Combined measuring devices for measuring two or more variables of movement, e.g. distance, speed or acceleration
    • G01C23/005—Flight directors
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
    • G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
    • G01C21/10—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration
    • G01C21/12—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration executed aboard the object being navigated; Dead reckoning
    • G01C21/16—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration executed aboard the object being navigated; Dead reckoning by integrating acceleration or speed, i.e. inertial navigation
    • G01C21/183—Compensation of inertial measurements, e.g. for temperature effects
    • G01C21/188—Compensation of inertial measurements, e.g. for temperature effects for accumulated errors, e.g. by coupling inertial systems with absolute positioning systems

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Abstract

The invention discloses a multi-sampling rate data fusion attitude correction method of an array sensor, which comprises the steps of sampling values of a gyroscope and an accelerometer in an array by multiple sampling rates; performing zero-speed judgment on data obtained at different sampling rates, and comparing the resultant acceleration measured by the three-axis accelerometer with the gravity acceleration to obtain the reliability of the horizontal attitude angle calculated by the acceleration; comparing the accelerometer measurement values with different sampling rates with the previous strapdown matrix to obtain a measurement error estimation value of the horizontal attitude, and performing weighted fusion on the accelerometer measurement values according to the credibility of the accelerometer data under different sampling rates; and fusing the horizontal attitude angle variation obtained by the accelerometer with the angular speed measured by the gyroscope to obtain a final attitude angle.

Description

Multi-sampling-rate data fusion attitude correction method for array sensor
Technical Field
The invention belongs to the technical field of navigation measurement of array sensors, and particularly relates to a multi-sampling-rate data fusion attitude correction method of an array sensor.
Background
With the rapid development of scientific technology, no matter intelligent vehicles, unmanned aerial vehicles or high-precision precise percussion weapons are researched and developed without an inertial navigation system, the inertial navigation system provides precise attitude and position information for the navigation and positioning of intelligent and automatic machinery, and MEMS inertial devices play a key role in various industries due to the characteristics of low cost, small volume, light weight and easiness in batch production.
After an aircraft engine is shut down, the acceleration of the aircraft engine is mainly caused by attitude adjustment and flight resistance, the resistance is basically negligible when the aircraft is in a thin atmosphere or above, the attitude adjustment is the main reason, and at the moment, the attitude is directly updated by a gyroscope, and attitude errors are accumulated due to divergence along with time, so that a correction method must be introduced. The invention provides a correction method adopting multiple sampling rates of an accelerometer array to correct the attitude, and as the acceleration maneuver of an unmanned aerial vehicle generally belongs to high-frequency signals, different sub-sensors in the sensor array are respectively sampled in real time by adopting 20Hz, 10Hz, 2Hz and 1Hz, and compared with a previous strapdown matrix, a measurement error estimation value of the horizontal attitude is obtained, a final estimation value is obtained after weighting and fusing the estimation value, and meanwhile, the angular velocity measured by a gyroscope is corrected, so that fused attitude information is obtained.
The multi-sampling-rate data fusion attitude correction method of the array sensor fully utilizes the parameters of each sensor in the array sensor, and effectively improves the attitude measurement precision. Research on the attitude measurement technology of the array sensor is beneficial to the control domain of the aircraft and benefits in the relevant field of navigation measurement of the array sensor. Therefore, the study of this technology is of great importance.
Disclosure of Invention
In the attitude measurement of the unmanned aerial vehicle, because errors such as zero offset, random walk and the like exist in the gyroscope, accumulated errors are easily introduced in the calculation of the attitude angle; the accelerometer can obtain a horizontal attitude angle with an error which is not accumulated along with time, however, the attitude angle is easily influenced by the acceleration of the carrier, so that an optimal attitude angle can be obtained by fusing the attitude angles measured by the gyroscope and the accelerometer. And carrying out multi-sampling rate acceleration measurement by using different accelerometers in the array, obtaining a measurement error estimation value of the horizontal attitude by comparing with the previous strapdown matrix, carrying out weighting fusion on the variable quantity, and then obtaining the optimal estimation on the attitude angle by combining the measurement value of the gyroscope. The specific technical scheme of the invention is as follows:
a multi-sampling-rate data fusion attitude correction method for an array sensor comprises the following steps:
s1: sampling the measured values of a gyroscope and an accelerometer in the array sensor at a plurality of sampling rates;
s2: performing zero-speed judgment on the data obtained in the step S1, and comparing the resultant acceleration measured by the accelerometer with the gravity acceleration to obtain the reliability of the horizontal attitude angle calculated by the acceleration;
s3: comparing the accelerometer measured value obtained in the step S1 with the gravity acceleration to obtain a measurement error estimated value of the horizontal attitude, and performing weighted fusion on the accelerometer measured value according to the reliability of accelerometer data under the corresponding sampling rate;
s4: and fusing the measurement error estimation value of the horizontal attitude angle obtained by the accelerometer and the angular velocity measured by the gyroscope to obtain a final attitude angle.
Further, the number of sampling rates is determined by the number n of sensors in the array sensor.
Further, the specific process of step S2 is as follows:
judging the carrier maneuvering state of the current array sensor for each sampling rate, comparing the difference between the modulus of the triaxial measurement value of the accelerometer and the gravity acceleration, and taking the difference as the weight of the corresponding sampling rate, wherein the larger the difference is, the lower the weight is:
Figure BDA0003318083550000021
wherein ,
Figure BDA0003318083550000022
the weight of the triaxial measurement value of the accelerometer under the s sampling rate is taken as the weight; axs,ays,azsRespectively measuring values of accelerometers of an x axis, a y axis and a z axis under an s sampling rate, and g is gravity acceleration;
normalizing the weight occupied by the triaxial measurement value of the accelerometer under different sampling rates:
Figure BDA0003318083550000023
wherein ,KsThe weight of the accelerometer measurement value under the normalized s sampling rate is satisfied
Figure BDA0003318083550000024
s1Is a first sampling rate, snIs the nth sample rate.
Further, the specific process of step S3 is as follows:
first, the accelerometer triaxial measurements are converted to the navigation system:
Figure BDA0003318083550000025
wherein ,anFor projection of the triaxial measurements of the accelerometer in the navigation system, abFor the three-axis acceleration values measured by the accelerometer,
Figure BDA0003318083550000031
a transformation matrix from a sensor coordinate system to a navigation system;
normalization treatment:
Figure BDA0003318083550000032
wherein ,
Figure BDA0003318083550000033
for normalized acceleration measurements in the navigation system, anx,any,anzAcceleration measurement values of an x axis, a y axis and a z axis under a navigation system are respectively obtained;
normalized gravitational acceleration of a navigation system
Figure BDA0003318083550000034
Comprises the following steps:
Figure BDA0003318083550000035
calculating measurement error estimation value of accelerometer horizontal attitude angle
Figure BDA0003318083550000036
Figure BDA0003318083550000037
Weighting and fusing accelerometers with different sampling rates to obtain a final measurement error estimated value e:
Figure BDA0003318083550000038
wherein ,
Figure BDA0003318083550000039
is the measurement error estimate of the accelerometer horizontal attitude angle at the normalized s-sample rate.
Further, the residual drift in the angular velocity measured by the gyro is corrected by using the proportional integral of the horizontal attitude angle measurement error estimation obtained by the accelerometer measurement, and the specific process of step S4 is as follows:
δ＝Kpe+Ki∫e
ω＝ωg+δ
wherein, delta is compensation quantity for gyro drift generated after error e passes through a proportional-integral module, Kp and KiProportional and integral coefficients, ω, respectivelygAnd (2) obtaining an angular velocity measured by a gyroscope, wherein omega is the angular velocity corrected by fusing accelerometer data, substituting omega into the following formula, and obtaining an accurate quaternion transmitted along with time by adopting a first-order Rogoku method:
Figure BDA00033180835500000310
Figure BDA00033180835500000311
Figure BDA0003318083550000041
Figure BDA0003318083550000042
wherein ,q0(t+T)q1(t+T)q2(t+T)q3(T + T) are quaternion values at T + T, q0(t)q1(t)q2(t)q3(t) are the quaternion value at time t, ω, respectivelyx、ωy、ωzThe values of the angular velocity in the xyz direction in the update period are respectively, T is the current moment, T is the attitude update period, and the attitude angle at the final T + T moment is obtained as follows:
Figure BDA0003318083550000043
wherein theta is a pitch angle, gamma is a roll angle, and phi is a course angle.
Further, the number of the sampling rates and the number of the sensors in the array sensor are both 4, and the multiple sampling rates in the step S1 are 20Hz, 10Hz, 2Hz, and 1Hz, respectively.
The invention has the beneficial effects that:
1. the invention corrects the gyro error in the sensor array, and after the data of 8 gyros in the array generated by simulation is corrected, the peak-to-peak value of the angular velocity error is reduced to 0.3 degree/s from 1 degree/s;
2. the method of the invention corrects the attitude error in the inertial navigation process.
Drawings
In order to illustrate embodiments of the present invention or technical solutions in the prior art more clearly, the drawings which are needed in the embodiments will be briefly described below, so that the features and advantages of the present invention can be understood more clearly by referring to the drawings, which are schematic and should not be construed as limiting the present invention in any way, and for a person skilled in the art, other drawings can be obtained on the basis of these drawings without any inventive effort. Wherein:
FIG. 1 is a simplified process flow diagram of the present invention;
FIG. 2 is a detailed flow chart of the method of the present invention;
FIG. 3 is a graph of the output of an array 8 of gyroscopes excited at 0 angular velocity;
FIG. 4 is a graph of the fused output of an array gyroscope after multiple sample rate data fusion modification;
FIG. 5 is the effectiveness of the method of the present invention for attitude error suppression;
fig. 6 is a trace generator.
Detailed Description
In order that the above objects, features and advantages of the present invention can be more clearly understood, a more particular description of the invention will be rendered by reference to the appended drawings. It should be noted that the embodiments of the present invention and features of the embodiments may be combined with each other without conflict.
In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present invention, however, the present invention may be practiced in other ways than those specifically described herein, and therefore the scope of the present invention is not limited by the specific embodiments disclosed below.
As shown in fig. 1-2, a method for correcting the multi-sampling rate data fusion attitude of an array sensor includes the following steps:
s1: sampling the measured values of a gyroscope and an accelerometer in the array sensor at a plurality of sampling rates;
s2: performing zero-speed judgment on the data obtained in the step S1, and comparing the resultant acceleration measured by the accelerometer with the gravity acceleration to obtain the reliability of the horizontal attitude angle calculated by the acceleration;
s3: comparing the accelerometer measured value obtained in the step S1 with the gravity acceleration to obtain a measurement error estimated value of the horizontal attitude, and performing weighted fusion on the accelerometer measured value according to the reliability of accelerometer data under the corresponding sampling rate;
s4: and fusing the measurement error estimation value of the horizontal attitude angle obtained by the accelerometer and the angular velocity measured by the gyroscope to obtain a final attitude angle.
Preferably, the number of sampling rates is determined by the number n of sensors in the array sensor.
In some embodiments, the specific process of step S2 is:
judging the carrier maneuvering state of the current array sensor for each sampling rate, comparing the difference between the modulus of the triaxial measurement value of the accelerometer and the gravity acceleration, and taking the difference as the weight of the corresponding sampling rate, wherein the larger the difference is, the lower the weight is:
Figure BDA0003318083550000051
wherein ,
Figure BDA0003318083550000052
the weight of the triaxial measurement value of the accelerometer under the s sampling rate is taken as the weight; axs,ays,azsRespectively measuring values of accelerometers of an x axis, a y axis and a z axis under an s sampling rate, and g is gravity acceleration;
normalizing the weight occupied by the triaxial measurement value of the accelerometer under different sampling rates:
Figure BDA0003318083550000061
wherein ,KsThe weight of the accelerometer measurement value under the normalized s sampling rate is satisfied
Figure BDA0003318083550000062
s1Is a first sampling rate, snIs the nth sample rate.
In some embodiments, the specific process of step S3 is:
first, the accelerometer triaxial measurements are converted to the navigation system:
Figure BDA0003318083550000063
wherein ,anFor projection of the triaxial measurements of the accelerometer in the navigation system, abFor the three-axis acceleration values measured by the accelerometer,
Figure BDA0003318083550000064
a transformation matrix from a sensor coordinate system to a navigation system;
normalization treatment:
Figure BDA0003318083550000065
wherein ,
Figure BDA0003318083550000066
for normalized acceleration measurements in the navigation system, anx,any,anzAcceleration measurement values of an x axis, a y axis and a z axis under a navigation system are respectively obtained;
normalized gravitational acceleration of a navigation system
Figure BDA0003318083550000067
Comprises the following steps:
Figure BDA0003318083550000068
calculating measurement error estimation value of accelerometer horizontal attitude angle
Figure BDA0003318083550000069
Figure BDA00033180835500000610
Weighting and fusing accelerometers with different sampling rates to obtain a final measurement error estimated value e:
Figure BDA00033180835500000611
wherein ,
Figure BDA00033180835500000612
is the measurement error estimate of the accelerometer horizontal attitude angle at the normalized s-sample rate.
In some embodiments, the residual drift in the angular velocity measured by the gyroscope is corrected by proportional integration of the horizontal attitude angle measurement error estimate obtained from the accelerometer measurement, and the specific process of step S4 is:
δ＝Kpe+Ki∫e
ω＝ωg+δ
wherein, delta is compensation quantity for gyro drift generated after error e passes through a proportional-integral module, Kp and KiProportional and integral coefficients, ω, respectivelygAnd (2) obtaining an angular velocity measured by a gyroscope, wherein omega is the angular velocity corrected by fusing accelerometer data, substituting omega into the following formula, and obtaining an accurate quaternion transmitted along with time by adopting a first-order Rogoku method:
Figure BDA0003318083550000071
Figure BDA0003318083550000072
Figure BDA0003318083550000073
Figure BDA0003318083550000074
wherein ,q0(t+T)q1(t+T)q2(t+T)q3(T + T) are quaternion values at T + T, q0(t)q1(t)q2(t)q3(t) are the quaternion value at time t, ω, respectivelyx、ωy、ωzThe values of the angular velocity in the xyz direction in the update period are respectively, T is the current moment, T is the attitude update period, and the attitude angle at the final T + T moment is obtained as follows:
Figure BDA0003318083550000075
wherein theta is a pitch angle, gamma is a roll angle, and phi is a course angle.
In some embodiments, the number of sampling rates and the number of sensors in the array sensor are both 4, and the multiple sampling rates in step S1 are 20Hz, 10Hz, 2Hz, and 1Hz, respectively.
For the convenience of understanding the above technical aspects of the present invention, the following detailed description will be given of the above technical aspects of the present invention by way of specific examples.
Example 1
Through matlab software, the angular random walk ARW parameter of the MEMS gyroscope is set to be 0.0833 degrees/(h ^ (1/2)), and the rate random walk RRW parameter is set to be 600 degrees/(h ^ (3/2)), according to the method shown in FIG. 6The trajectory generator of (1) generates 18000s of raw sensor data, T in the figuresThe sampling interval is set to 10ms for high frequency and the raw data is sampled at 20Hz, 10Hz, 2Hz, 1Hz sampling rates.
FIG. 3 is an output graph of 4 gyros in the x-axis of the array under excitation of 0 angular velocity, FIG. 4 is a fused output graph of the array gyro after multi-sampling rate data fusion correction, and the result shows that the peak-to-peak value of the angular velocity error is reduced from 1/s to 0.3/s after the data of the 4 gyros in the array generated through simulation is corrected;
example 2
In the embodiment, multiple sets of simulation tests are performed, the experimental results are shown in fig. 5, and the 3-axis attitude angle errors, namely the pitch angle, the roll angle and the course angle errors, of the multiple experiments are not dispersed and are limited within 5 degrees, so that the method provided by the invention is proved to have obvious improvement on the navigation attitude errors.
The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims (6)

1. A multi-sampling-rate data fusion attitude correction method for an array sensor is characterized by comprising the following steps:
s1: sampling the measured values of a gyroscope and an accelerometer in the array sensor at a plurality of sampling rates;
s2: performing zero-speed judgment on the data obtained in the step S1, and comparing the resultant acceleration measured by the accelerometer with the gravity acceleration to obtain the reliability of the horizontal attitude angle calculated by the acceleration;
s3: comparing the accelerometer measured value obtained in the step S1 with the gravity acceleration to obtain a measurement error estimated value of the horizontal attitude, and performing weighted fusion on the accelerometer measured value according to the reliability of accelerometer data under the corresponding sampling rate;
s4: and fusing the measurement error estimation value of the horizontal attitude angle obtained by the accelerometer and the angular velocity measured by the gyroscope to obtain a final attitude angle.
2. The method as claimed in claim 1, wherein the number of sampling rates is determined by the number of sensors n in the array sensor.
3. The method for correcting the attitude of the array sensor with the multi-sampling rate data fusion according to claim 1 or 2, wherein the specific process of the step S2 is as follows:
judging the carrier maneuvering state of the current array sensor for each sampling rate, comparing the difference between the modulus of the triaxial measurement value of the accelerometer and the gravity acceleration, and taking the difference as the weight of the corresponding sampling rate, wherein the larger the difference is, the lower the weight is:
Figure FDA0003318083540000011
wherein ,
Figure FDA0003318083540000012
the weight of the triaxial measurement value of the accelerometer under the s sampling rate is taken as the weight; axs,ays,azsRespectively measuring values of accelerometers of an x axis, a y axis and a z axis under an s sampling rate, and g is gravity acceleration;
normalizing the weight occupied by the triaxial measurement value of the accelerometer under different sampling rates:
Figure FDA0003318083540000013
wherein ,KsThe weight of the accelerometer measurement value under the normalized s sampling rate is satisfied
Figure FDA0003318083540000014
s1Is a first sampling rate, snIs the nth sample rate.
4. The method for correcting the multi-sampling rate data fusion attitude of the array sensor according to claim 3, wherein the specific process of the step S3 is as follows:
first, the accelerometer triaxial measurements are converted to the navigation system:
Figure FDA0003318083540000015
wherein ,anFor projection of the triaxial measurements of the accelerometer in the navigation system, abFor the three-axis acceleration values measured by the accelerometer,
Figure FDA0003318083540000021
a transformation matrix from a sensor coordinate system to a navigation system;
normalization treatment:
Figure FDA0003318083540000022
wherein ,
Figure FDA0003318083540000023
for normalized acceleration measurements in the navigation system, anx,any,anzAcceleration measurement values of an x axis, a y axis and a z axis under a navigation system are respectively obtained;
normalized gravitational acceleration of a navigation system
Figure FDA0003318083540000024
Comprises the following steps:
Figure FDA0003318083540000025
calculating measurement error estimation value of accelerometer horizontal attitude angle
Figure FDA0003318083540000026
Figure FDA0003318083540000027
Weighting and fusing accelerometers with different sampling rates to obtain a final measurement error estimated value e:
Figure FDA0003318083540000028
wherein ,
Figure FDA0003318083540000029
is the measurement error estimate of the accelerometer horizontal attitude angle at the normalized s-sample rate.
5. The method for correcting the attitude of the array sensor through data fusion with multiple sampling rates according to claim 4, wherein the residual drift in the angular velocity measured by the gyroscope is corrected by using the proportional integral of the horizontal attitude angle measurement error estimation obtained from the accelerometer measurement, and the specific process of the step S4 is as follows:
δ＝Kpe+Ki∫e
ω＝ωg+δ
wherein, delta is compensation quantity for gyro drift generated after error e passes through a proportional-integral module, Kp and KiProportional and integral coefficients, ω, respectivelygAnd (2) obtaining an angular velocity measured by a gyroscope, wherein omega is the angular velocity corrected by fusing accelerometer data, substituting omega into the following formula, and obtaining an accurate quaternion transmitted along with time by adopting a first-order Rogoku method:
Figure FDA00033180835400000210
Figure FDA00033180835400000211
Figure FDA0003318083540000031
Figure FDA0003318083540000032
wherein ,q0(t+T)q1(t+T)q2(t+T)q3(T + T) are quaternion values at T + T, q0(t)q1(t)q2(t)q3(t) are the quaternion value at time t, ω, respectivelyx、ωy、ωzThe values of the angular velocity in the xyz direction in the update period are respectively, T is the current moment, T is the attitude update period, and the attitude angle at the final T + T moment is obtained as follows:
Figure FDA0003318083540000033
wherein theta is a pitch angle, gamma is a roll angle, and phi is a course angle.
6. The method for correcting the attitude of the array sensor through the data fusion of the multiple sampling rates according to one of the claims 1 to 5, wherein the number of the sampling rates and the number of the sensors in the array sensor are both 4, and the multiple sampling rates in the step S1 are respectively 20Hz, 10Hz, 2Hz and 1 Hz.
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