CN108759845A - A kind of optimization method based on inexpensive multi-sensor combined navigation - Google Patents
A kind of optimization method based on inexpensive multi-sensor combined navigation Download PDFInfo
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- G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
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- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
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Abstract
The invention discloses a kind of optimization methods based on inexpensive multi-sensor combined navigation, include the following steps：Design Butterworth low-pass filters are filtered three axis angular rates and 3-axis acceleration of IMU, while the installation site deviation according to each sensor relative to IMU compensates.It then sets up 7 rank quaternary numbers, the state equation that angular speed biases, show that quaternary number and angular speed bias using closed loop extended Kalman filter.Data buffer zone is established according to the delay character of different sensors, time synchronization is carried out on the basis of the time that IMU acquires information, establishes that 9 component levels are set, speed, acceleration are biased to the closed loop extended Kalman filter of quantity of state.The output of 9 rank extended Kalman filters is subjected to time synchronization with the result of strapdown inertia prediction equation using complementary filter and merges compensation, obtains the more accurate navigation information of current time.
Description
Technical field
The present invention relates to aircraft integrated navigation technology fields, and in particular to one kind is led based on inexpensive multi sensor combination
The optimization method of boat.
Background technology
With the progress of microelectric technique, embedded technology, unmanned vehicle technology (abbreviation aircraft) obtains
Development at full speed, and navigator fix is a very important part in vehicle technology.Traditional strapdown inertial navigation method
Need by based on high-precision, expensive IMU to be not suitable in civil aircraft applications.Consumer level IMU cost phases
For relatively low, but precision is relatively low, and noise is big, strapdown inertial navigation side larger by external influences, traditional
Method is easy to fail.Therefore inexpensive sensor combinations navigation is come into being, it is by consumer level IMU with other inexpensive sensors
(such as GPS, magnetometer) carries out data fusion, eliminates the error that IMU integrals generate by introducing new breath, provides more reliable, precision
Relatively high navigator fix.
However since embedded chip computing capability improves, flight control system allows to reach better control performance
Aircraft has preferably maneuverability, often constantly improves control frequency (100Hz-400Hz).Low cost sensing
There are different degrees of delay characters for device, if not considering time synchronization data fusion, it will add one in the feedback loop
Different degrees of delay component.The introducing of delay component will cause control performance to decline, in some instances it may even be possible to cause the shakiness of controlled system
It is fixed.In addition sensor mounting location can not be overlapped with body barycenter in actual application, also will produce different degrees of effect
Control effect should be caused to deteriorate to reduce measurement accuracy.
Invention content
The purpose of the present invention is to solve drawbacks described above in the prior art, provide a kind of based on inexpensive multisensor
The optimization method of integrated navigation, the position and speed of the GPS for acquiring onboard flight control system, the magnetic field of magnetometer are strong
Degree, three axis angular rates and 3-axis acceleration of barometer height, the height of laser radar and IMU carry out data fusion, simultaneously
Consider that each sensor delay character and installation site compensate.
The purpose of the present invention can be reached by adopting the following technical scheme that：
A kind of optimization method based on inexpensive multi-sensor combined navigation, the optimization method include the following steps：
S1, according to the Butterworth low-pass filters of body vibration level design corresponding index to three shaft angles of IMU
Speed and 3-axis acceleration are filtered, and reduce dithering noise interference, simultaneously because each sensor is existing in body
Differ for the installation site of IMU, it need to accordingly be compensated.
S2,7 rank quaternary number [q are established0 q1 q2 q3]T, angular speed biased w _ bias=[bp bq br]TState equation
(as follows), with 3-axis acceleration acc after filteringb=[ax ay az]TThe course angle ψ calculated with magnetometer is as observation
Amount show that quaternary number and angular speed bias using closed loop extended Kalman filter, will obtain quaternary number and add with what IMU was acquired
Speed accbIt is stored in data buffer area, synchronizes and prepares for follow-up progress data time；
Wherein g is acceleration of gravity.
S3, data buffer zone is established according to the delay character of different sensors, acceleration acc is collected with IMUbTime
On the basis of carry out time synchronization, establish 9 component levels and set P=[λ Ф h]T, speed V=[VN VE VD]T, acceleration biasingFor the closed loop extended Kalman filter of quantity of state, as follows：
Wherein：
For radius of meridional section.
For chordwise curvature radius.
weFor rotational-angular velocity of the earth.
S4, strapdown is passed through into the output of 9 rank extended Kalman filters and pure IMU acceleration informations using complementary filter
The result of formula inertial navigation prediction equation carries out time synchronization fusion compensation, obtains the more accurate navigation information of current time.
Further, the step S1 includes：S11, sensing data filtering；S12, sensor measurement compensated
Journey.
Further, the step S11, sensing data filtering are as follows：
S111, spectrogram is obtained by carrying out discrete Fast Fourier Transform iterative inversion (FFT) to acquisition IMU acceleration informations；
S112, the frequency size and amplitude size for analyzing aircraft body vibration source.According to sample frequency (Hz), bandwidth
Frequency (Hz), vibration source attenuation amplitude (dB) index and delay degree (°) design Butterworth low-pass filters.
Butterworth low pass filter equations are as follows：
Y (k)=b0x(k)+…+bn-1x(k-n)-a0y(k)-…-an-1y(k-n)
In above formula, x (k-n) is the data that n moment front sensors are read, and y (k-n) is low for Butterworth before the n moment
The output of bandpass filter, b0..., bn-1, a0..., an-1For the coefficient of filter.
Further, the step S12, sensor measurement compensation process：
S121, lidar measurement height are relative altitudes, and can be changed with attitudes vibration.Because according to laser thunder
Altimetric compensation is carried out up to the difference in height of IMU installation sites, and must take into consideration current time posture information.
Assuming that laser radar mounting height deviation is Δ hb, then the relative altitude after overcompensation be：
Wherein:
The measurement height for being laser radar under body coordinate system,
EulerrollTo indicate the roll angle of attitude of flight vehicle information,
EulerpitchTo indicate the pitch angle of attitude of flight vehicle information；
S122, GPS actual installation position are often misaligned with IMU installation sites, are produced when body carries out high maneuver flight
Raw lever arm effect causes measurement error to reduce GPS measurement accuracy, as follows to its compensation way：
Assuming that the installation site deviation of GPS and IMU is Δ rb, then through overcompensation after GPS measurements obtain IMU position,
Speed is respectively：
Wherein：
For location informations of the GPS under NED coordinate systems,
For velocity informations of the GPS under NED coordinate systems,
For radius of meridional section,
For chordwise curvature radius,
H is height above sea level,
Ф is current latitude,
For the antisymmetric matrix that earth's spin vector is projected in navigational coordinate system,
The antisymmetric matrix of the angular velocity vector of the opposite earth is generated for body speed,
For the antisymmetric matrix of body angular speed,
For the spin matrix under body coordinate system to navigational coordinate system.
Further, quaternary number and angular speed are obtained using 7 rank closed loop extended Kalman filters in the step S2
The input as 9 rank closed loop extended Kalman filters is biased, concatenated form is formed, the time for reducing entire algorithm is complicated
Degree and space complexity.
Further, data time synchronous method is used in the step S3.
Delay character and the algorithm cycle of operation of the data time synchronous method according to each sensor, respectively to all biographies
Sensor establishes corresponding length data fifo memory block, then the sensor (such as IMU, laser radar etc.) that can quickly measure
Output is stored in respective data storage area, and records system time when sensor exports.It is simultaneously that time of measuring is longer
Sensor (such as GPS) receives new output information and also is stored in respective data storage area, when considering each sensor
Record measures the output system time under delay characteristics.When then being looked for from the memory block of the sensor quickly measured with same system
Between IMU information, formed 9 rank Kalman filtering simultaneous observation values input.
Further, the fusion compensation method of the step S4 uses the thinking of complementary filter.Detailed process is as follows：
It is searched and the obtained positions step S3 from the data buffer zone that IMU is integrated by strapdown inertia equation
Set PEKF, velocity information VEKFTime synchronization information, error between the two by complementary filter formed compensation rate, by compensation rate
It feeds back in data buffer area, the result integrated to strapdown inertia equation is modified, and it is more accurate to obtain current time
Location information PInsWith velocity information VIns；Complementary filter uses 2 rank complementary filters, the following institute of expression of transmission function
Show：
Method is as follows using 2 rank complementary filter transmission function expressions：
For the K of locations complementary filterP,
For the K of locations complementary filteri,
For the K of speed complementary filterP,
For the K of speed complementary filteri,
Acc is acceleration information.
Further, the vibration frequency source of the aircraft includes motor or oily piston engine work, rotation
The wing waves the body vibration of generation.
The present invention has the following advantages and effects with respect to the prior art：
1) the method for the present invention is suitable for aircraft integrated navigation field, and Extended Kalman filter is reduced using concatenated mode
Device exponent number reduces the time complexity and space complexity of algorithm.
2) the method for the present invention considers the installation site difference of sensor, is accordingly compensated, and sensor accuracy class is improved.
3) the method for the present invention fully considers that the delay character of sensor, deadline synchronous fusion have precision height, data
Small advantage is lagged, good performance index can be kept the case where aircraft carries out high maneuver flight.
Description of the drawings
Fig. 1 is the flow chart of the optimization method disclosed by the invention based on inexpensive multi-sensor combined navigation；
Fig. 2 is time synchronization fusion compensation complementary filter flow chart in the present invention.
Specific implementation mode
In order to make the object, technical scheme and advantages of the embodiment of the invention clearer, below in conjunction with the embodiment of the present invention
In attached drawing, technical scheme in the embodiment of the invention is clearly and completely described, it is clear that described embodiment is
A part of the embodiment of the present invention, instead of all the embodiments.Based on the embodiments of the present invention, those of ordinary skill in the art
The every other embodiment obtained without making creative work, shall fall within the protection scope of the present invention.
Embodiment
As shown in Fig. 1, the present embodiment discloses a kind of stream of the optimization method based on inexpensive multi-sensor combined navigation
Cheng Tu, the method includes the following steps：
S1, the Butterworth low-pass filters of corresponding index are designed to the three of IMU according to aircraft body level of vibration
Axis angular rate and 3-axis acceleration are filtered, and high-frequency noise interference are reduced, simultaneously because each sensor is in aircraft
Body differs relative to the installation site of IMU, need to accordingly be compensated it.
The step S1 includes：S11, sensing data filtering；S12, sensor measurement compensation process.
S11, sensing data filtering are as follows：
The body that S111, FLIGHT VEHICLE VIBRATION frequency source are mainly waved generation by motor or the dynamic engine work of oil, rotor shakes
Dynamic composition.Discrete Fast Fourier Transform iterative inversion (FFT) acquisition acceleration spectrogram, analysis are carried out by acquiring IMU acceleration informations
The frequency size in body vibration source and amplitude size.
S112, according to IMU sample frequencys (Hz), aerocraft system bandwidth frequency (be usually 20Hz to 30Hz), vibration source
Attenuation amplitude (dB) index and delay degree (°) design different rank Butterworth low-pass filters.Butterworth is low
Pass filter equation is as follows：
Y (k)=b0x(k)+…+bn-1x(k-n)-a0y(k)-…-an-1y(k-n)
In above formula, x (k-n) is the data that n moment front sensors are read, and y (k-n) is low for Butterworth before the n moment
The output of bandpass filter, b0..., bn-1, a0..., an-1For the coefficient of filter.
S12, sensor measurement compensation process：
S121, lidar measurement height are relative altitudes, and can be changed with attitudes vibration.Because according to laser thunder
Altimetric compensation is carried out up to the difference in height of IMU installation sites, and must take into consideration current time posture information.
Assuming that laser radar mounting height deviation is Δ hb, then the relative altitude after overcompensation be：
Wherein:
The measurement height for being laser radar under body coordinate system,
EulerrollTo indicate the roll angle of attitude of flight vehicle information,
EulerpitchTo indicate the pitch angle of attitude of flight vehicle information；
S122, GPS actual installation position are often misaligned with IMU installation sites, when aircraft carries out high maneuver flight
Lever arm effect is generated, measurement error is caused to reduce GPS measurement accuracy, it is as follows to its compensation way：
Assuming that the installation site deviation of GPS and IMU is Δ rb∈R3×1, then through overcompensation after GPS measurements obtain IMU's
Position, speed are respectively：
Wherein：
For location informations of the GPS under NED coordinate systems,
For velocity informations of the GPS under NED coordinate systems,
For radius of meridional section,
For chordwise curvature radius,
H is height above sea level,
Ф is current latitude,
For the antisymmetric matrix that earth's spin vector is projected in navigational coordinate system,
The antisymmetric matrix of the angular velocity vector of the opposite earth is generated for body speed,
For the antisymmetric matrix of body angular speed,
For the spin matrix under body coordinate system to navigational coordinate system.
S2,7 rank quaternary number [q are established0 q1 q2 q3]T, angular speed biased w _ bias=[bp bq br]TState equation,
With 3-axis acceleration acc after filteringb=[ax ay az]TThe course angle ψ calculated with magnetometer utilizes closed loop as observed quantity
Extended Kalman filter obtains quaternary number and angular speed biasing, will obtain the acceleration acc of quaternary number and IMU acquisitionsbDeposit
Data buffer area synchronizes for follow-up progress data time and prepares；
Quaternary number is obtained using 7 rank closed loop extended Kalman filters and angular speed biases conduct in the step S2
The input of 9 rank closed loop extended Kalman filters, forms concatenated form, reduces time complexity and the space of entire algorithm
Complexity.
S3, data buffer zone is established according to the delay character of different sensors, acceleration acc is collected with IMUbTime
On the basis of carry out time synchronization, establish 9 component levels and set P=[λ Ф h]T, speed V=[VN VE VD]T, acceleration biasingFor the closed loop extended Kalman filter of quantity of state；
Wherein：
For radius of meridional section,
For chordwise curvature radius,
weFor rotational-angular velocity of the earth.
Delay character and the algorithm cycle of operation of the data time synchronous method according to each sensor, respectively to all biographies
Sensor establishes corresponding length data fifo memory block.Then the sensor (such as IMU, laser radar etc.) that can quickly measure
Output is stored in respective data storage area, and records system time when sensor exports.It is simultaneously that time of measuring is longer
Sensor (such as GPS) receives new output information and also is stored in respective data storage area, when considering each sensor
Record measures the output system time under delay characteristics.When then being looked for from the memory block of the sensor quickly measured with same system
Between IMU information, formed 9 rank Kalman filtering simultaneous observation values input.
S4, strapdown is passed through into the output of 9 rank extended Kalman filters and pure IMU acceleration informations using complementary filter
The result of formula inertial navigation prediction equation carries out time synchronization fusion compensation, obtains the more accurate navigation information of current time.
Time synchronization fusion compensation method uses the thinking of complementary filter in the step S4.Detailed process is as follows：
It is searched and the obtained positions step S3 from the data buffer zone that IMU is integrated by strapdown inertia equation
Set PEKF, velocity information VEKFTime synchronization information, error between the two by complementary filter formed compensation rate, by compensation rate
It feeds back in data buffer area, the result integrated to strapdown inertia equation is modified, and it is more accurate to obtain current time
Location information PInsWith velocity information VIns；Complementary filter uses 2 rank complementary filters, the following institute of expression of transmission function
Show：
Method is as follows using 2 rank complementary filter transmission function expressions：
Wherein：
For the K of locations complementary filterP,
For the K of locations complementary filteri,
For the K of speed complementary filterP,
For the K of speed complementary filteri,
Acc is acceleration information.
By taking speed complementary filter as an example (similarly locations complementary filter), above formula transmission function can convert following shape
Formula：
From above formula it can be found that 2 rank complementary filters act on VEKFIncluding second-order low-pass filter and the filtering of second order bandwidth
Device, bivalent high-pass filter act on acceleration.The frequency response of second order complementary filter depends on resonant frequencyDamping ratioDamping ratio is determined in resonant frequency overshoot.In order to keep complementary filter output gentle
(step response is without concussion), should be arranged dampingratioζ>1, therefore exist with downstream condition：
Certainly, in order to reach better effect, ζ ≈ 2 can obtain better convergence rate.
The above embodiment is a preferred embodiment of the present invention, but embodiments of the present invention are not by above-described embodiment
Limitation, it is other it is any without departing from the spirit and principles of the present invention made by changes, modifications, substitutions, combinations, simplifications,
Equivalent substitute mode is should be, is included within the scope of the present invention.
Claims (8)
1. a kind of optimization method based on inexpensive multi-sensor combined navigation, which is characterized in that the optimization method includes
The following steps：
S1, three shaft angles of the Butterworth low-pass filters to IMU that corresponding index is designed according to aircraft body level of vibration
Speed wb=[p q r]bWith 3-axis acceleration accb=[ax ay az]bIt is filtered, reduces dithering noise interference,
It is accordingly compensated relative to the installation site of IMU in aircraft body according to each sensor simultaneously；
S2,7 rank quaternary number [q are established0 q1 q2 q3]T, angular speed biased w _ bias=[bp bq br]TState equation, with filter
3-axis acceleration acc after waveb=[ax ay az]TThe course angle ψ calculated with magnetometer is extended as observed quantity using closed loop
Kalman filter obtains quaternary number and angular speed biasing, will obtain the acceleration acc of quaternary number and IMU acquisitionsbIt is stored in data
Buffer area is synchronized for follow-up progress data time and is prepared；
S3, data buffer zone is established according to the delay character of different sensors, acceleration acc is collected with IMUbTime be base
Standard carries out time synchronization, establishes 9 component levels and sets P=[λ Ф h]T, speed V=[VN VE VD]T, acceleration biasingFor the closed loop extended Kalman filter of quantity of state；
S4, the output of 9 rank extended Kalman filters and pure IMU acceleration informations are used to by strapdown using complementary filter
The result for leading prediction equation carries out time synchronization fusion compensation, obtains the accurate navigation information of current time.
2. a kind of optimization method based on inexpensive multi-sensor combined navigation according to claim 1, which is characterized in that
The step S1 includes：
S11, sensing data filtering；
S12, sensor measurement compensation process.
3. a kind of optimization method based on inexpensive multi-sensor combined navigation according to claim 2, which is characterized in that
The step S11, sensing data filtering are as follows：
S111, spectrogram is obtained by carrying out discrete Fast Fourier Transform iterative inversion to acquisition IMU acceleration informations, analyzes aircraft machine
The frequency size of body vibration source and amplitude size；
S112, according to sample frequency, bandwidth frequency, vibration source attenuation amplitude index and delay degree design Butterworth it is low
Bandpass filter, wherein Butterworth low pass filter equations are as follows：
Y (k)=b0x(k)+…+bn-1x(k-n)-a0y(k-1)-…-an-1y(k-n)
In above formula, x (k-n) is the data that n moment front sensors are read, and y (k-n) is Butterworth low-pass filtering before the n moment
The output of device, b0..., bn-1, a0..., an-1For the coefficient of filter.
4. a kind of optimization method based on inexpensive multi-sensor combined navigation according to claim 2, which is characterized in that
The step S12, sensing data filtering are as follows：
S121, consider aircraft current time posture information, height is carried out according to the difference in height of laser radar and IMU installation sites
Compensation, it is assumed that laser radar mounting height deviation is Δ hb, then after overcompensation laser radar relative altitudeFor：
The measurement height for being laser radar under body coordinate system,
EulerrollTo indicate the roll angle of attitude of flight vehicle information,
EulerpitchTo indicate the pitch angle of attitude of flight vehicle information；
S122, consider that GPS actual installations position and IMU installation sites are misaligned, when aircraft body carries out high maneuver flight
Lever arm effect is generated, causes measurement error to reduce GPS measurement accuracy, it is as follows that mode is compensated to GPS：Assuming that GPS and IMU
Installation site deviation is Δ rb, then through overcompensation after GPS measurements obtain the position of IMUSpeedRespectively：
Wherein：
For location informations of the GPS under NED coordinate systems,
For velocity informations of the GPS under NED coordinate systems,
For radius of meridional section,
For chordwise curvature radius,
H is height above sea level,
Ф is current latitude,
For the antisymmetric matrix that earth's spin vector is projected in navigational coordinate system,
The antisymmetric matrix of the angular velocity vector of the opposite earth is generated for body speed,
For the antisymmetric matrix of body angular speed,
For the spin matrix under body coordinate system to navigational coordinate system.
5. a kind of optimization method based on inexpensive multi-sensor combined navigation according to claim 1, which is characterized in that
Quaternary number is obtained using 7 rank closed loop extended Kalman filters and angular speed biasing is used as 9 ranks in the step S2
The input of closed loop extended Kalman filter forms concatenated form.
6. a kind of optimization method based on inexpensive multi-sensor combined navigation according to claim 1, which is characterized in that
It is as follows using data time synchronous method in the step S3：
According to the delay character of each sensor and the algorithm cycle of operation, corresponding length FIFO is established to all the sensors respectively
Data storage area；
Then the output for the sensor that can quickly measure is stored in respective data storage area, and records sensor output
When system time, wherein the sensor that can quickly measure includes IMU and laser radar, at the same time of measuring compared with
Long sensor receives new output information and also is stored in respective data storage area, wherein the time of measuring compared with
Long sensor includes GPS, and in the case where considering each sensor delay character, record measures the output system time；
Then it is looked for from the memory block of the sensor quickly measured with same system time IMU information, forms 9 rank Kalmans filter
The input of wave simultaneous observation value.
7. a kind of optimization method based on inexpensive multi-sensor combined navigation according to claim 1, which is characterized in that
The thinking that compensation method uses complementary filter is merged in the step S4, flow is as follows：
It is searched and the obtained position P of step S3 from the data buffer zone that IMU is integrated by strapdown inertia equationEKF、
Velocity information VEKFTime synchronization information, error between the two by complementary filter formed compensation rate, compensation rate is fed back to
In data buffer area, the result integrated to strapdown inertia equation is modified, and obtains the more accurate position of current time
Information PInsWith velocity information VIns；Complementary filter uses 2 rank complementary filters, the expression of transmission function as follows：
Wherein：
For the K of locations complementary filterP,
For the K of locations complementary filteri,
For the K of speed complementary filterP,
For the K of speed complementary filteri,
Acc is acceleration information.
8. a kind of optimization method based on inexpensive multi-sensor combined navigation according to claim 1, which is characterized in that
The vibration frequency source of the aircraft includes motor or oily piston engine work, rotor wave the body of generation and shakes
It is dynamic.
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