CN108106635A - Inertia defends the anti-interference posture course calibration method of long endurance for leading integrated navigation system - Google Patents
Inertia defends the anti-interference posture course calibration method of long endurance for leading integrated navigation system Download PDFInfo
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C25/00—Manufacturing, calibrating, cleaning, or repairing instruments or devices referred to in the other groups of this subclass
- G01C25/005—Manufacturing, calibrating, cleaning, or repairing instruments or devices referred to in the other groups of this subclass initial alignment, calibration or starting-up of inertial devices
Abstract
The anti-interference posture course calibration method of long endurance for leading integrated navigation system is defended the present invention relates to a kind of inertia, technical characterstic is：In inertial navigation system, carry out inertial reference calculation output posture course, speed and location information and update；It is used as using the location information of satellite positioning and navigation system with reference to information, data fusion is carried out with the location information of inertial navigation system, convergence strategy is that the error propagation principles of foundation inertial navigation system determine mathematical model, and carries out On-line Estimation and calibration to the error state of inertial navigation system navigation information using Kalman filter.Present invention design is reasonable, it is combined filtering to the navigation information of inertial navigation system using Kalman filter with defending the navigation information of guiding systems, obtain optimal carrier aircraft navigation information, and diagnosis isolation is carried out to the failure for defending guiding systems in harsh environment, inertial navigation system is solved in the attitude error calibration problem that works long hours, guarantee inertial navigation system attitude error is estimated accurately and reliably.
Description
Technical field
Integrated navigation technology field of leading is defended the invention belongs to inertia, especially a kind of inertia defends the length for leading integrated navigation system
The anti-interference posture course calibration method of endurance.
Background technology
The precision and stability of stagnant its navigation system of empty characteristic requirements of long-time of long endurance unmanned aircraft is very high, for this
Demand generally defends the navigation system for leading integrated navigation system as long endurance unmanned aircraft using inertia.Inertial navigation system has height
The shortcomings of spending the advantages such as independence, strong antijamming capability, output real-time height, but being accumulated at any time there are error, is expensive.
Satellite navigation system has the advantages such as positioning accuracy is high, error does not dissipate, is cheap at any time, but there is also output real-times
Difference, easily by external interference the shortcomings of.The integrated navigation system being made of the two can integrate their own advantage, with relatively low
Cost realizes that long-time, high-precision navigation information export in real time.
In complicated working environment, satellite navigation system is vulnerable to various environmental disturbances so that defends the navigation of guiding systems
Precision of information declines or generates the phenomena of the failure such as mutation, and be such as not added with differentiating at this time is directly combined filter using fault message
Ripple, by the very big navigation accuracy for reducing integrated navigation system.
The content of the invention
It is overcome the deficiencies in the prior art the mesh of the present invention, proposes that a kind of design is reasonable, navigation accuracy is high and performance
Stable inertia defends the anti-interference posture course calibration method of long endurance for leading integrated navigation system.
The present invention solves its technical problem and following technical scheme is taken to realize：
A kind of inertia defends the anti-interference posture course calibration method of long endurance for leading integrated navigation system, comprises the following steps：
Step 1, in inertial navigation system, carry out inertial reference calculation output posture course, speed and location information and simultaneously update；
Step 2 is used as using the location information of satellite positioning and navigation system with reference to information, the location information with inertial navigation system
Data fusion is carried out, convergence strategy is that the error propagation principles of foundation inertial navigation system determine mathematical model, and is filtered using Kalman
Ripple device carries out On-line Estimation and calibration to the error state of inertial navigation system navigation information.
Include the following steps after step 2：Property defend lead carry out defending during integrated navigation system resists guiding systems fault diagnosis with
Isolation.
The step 1 forms inertial navigation system using three gyroscopes and three acceleration and carries out inertial reference calculation, specifically
Method is：By gathering the Output speed data of gyroscope and deducting rotational-angular velocity of the earth and involve angular speed, calculate
Obtain attitude angle；The acceleration of accelerometer measures by Direct cosine matrix carry out coordinate transform to geographic coordinate system north orientation,
On axis, the acceleration fastened of integration geographical coordinate simultaneously deducts the influence of gravity and harmful acceleration and obtains geographical seat for east orientation, day
Mark north orientation, east orientation and the sky orientation speed of system；Using the north orientation of geographic coordinate system, east orientation speed, and consider the radius of curvature of the earth
Longitude and latitude is calculated.
The concrete methods of realizing of the step 2 includes：
(1) Kalman filtering one-step prediction step：
(2) when filtering time is then filtered update step；
(3) when system timer reach correct the moment, using revised attitude quaternion, speed, position as initial value into
Enter independent navigation step.
The step (1) includes the calculating of state transfer matrix, the calculating of input noise variance matrix and status predication and error
The calculating of variance prediction.
The step (2) includes measuring calculating, filtering gain calculating, state-updating and error variance update.
The step (3) includes attitude quaternion amendment, speed amendment and position correction process.
It is described defend guiding systems fault diagnosis and treatment method be：It is defended with to combine inertia and leads the Kalman of integrated navigation system
Wave filter, using consistency check method of inspection, is derived from the measured value for defending guiding systems failure by isolating, realizes as diagnostic tool
Jamproof inertial navigation system posture course calibration；The measurement of Kalman filter newly cease instruction measurement with state estimation whether one
It causes；Guiding systems failure is defended using the big mutation of method of inspection detection of the new breath monitoring i.e. based on residual error, is monitored using innovation sequence
Detect it is small become slowly defend guiding systems failure.
The advantages and positive effects of the present invention are：
The present invention drifts about and defends at any time the shortcomings that guiding systems are easily by external environmental interference for inertial navigation system error, utilizes
Kalman filter is combined filtering to the navigation information of inertial navigation system with defending the navigation information of guiding systems, obtains optimal load
Machine navigation information, and diagnosis isolation is carried out to the failure for defending guiding systems in harsh environment, even if being disturbed item defending guiding systems
Also the long endurance posture course error calibration of inertial navigation system can be completed under part, solves inertial navigation system in the appearance that works long hours
State angle error calibration problem ensures the estimation of inertial navigation system attitude error accurately and reliably.
Description of the drawings
Fig. 1 is the navigation calculation flow chart of the present invention；
The inertia that Fig. 2 is the present invention is defended and leads integrated navigation flow chart.
Specific embodiment
The embodiment of the present invention is further described below in conjunction with attached drawing.
A kind of inertia defends the anti-interference posture course calibration method of long endurance for leading integrated navigation system, is with three gyroscopes
Strapdown inertial navigation system is formed with three accelerometers, carries out inertial reference calculation output posture course, speed and location information.It adopts
By the use of the location information of satellite positioning and navigation system as with reference to information, data fusion is carried out with the location information of inertial navigation system, is melted
It closes the error propagation principles that strategy is foundation inertial navigation system and determines mathematical model, navigated using Kalman filter to inertial navigation system
The error state of information carries out On-line Estimation and calibration.Specifically comprise the following steps：
Step 1, in strapdown inertial navigation system, carry out inertial reference calculation output posture course, speed and location information simultaneously
Update.
In this step, in three gyroscopes and three acceleration form inertial navigation system, inertial navigation solution is carried out
It calculates.By gathering the Output speed data of gyro and deducting rotational-angular velocity of the earth and involve angular speed, appearance is calculated
State angle.The acceleration of accelerometer measures carries out coordinate transform to the north orientation, east orientation, day of geographic coordinate system by Direct cosine matrix
On axis, the acceleration fastened of integration geographical coordinate simultaneously deducts the influence of gravity and harmful acceleration and obtains the north of geographic coordinate system
To, east orientation and sky orientation speed.Using the north orientation of geographic coordinate system, east orientation speed, and consider that the curvature radius calculation of the earth obtains
Longitude and latitude.Navigation calculation flow is as shown in Figure 1, specific method is：
Remember the corresponding direction cosine matrix of initial attitude angleCorresponding attitude quaternion is denoted asIt willChange into attitude quaternionForm：
K=0 when 1,2 ..., utilizes quaternary number more new algorithm to calculate tk+1The attitude quaternion at moment
Wherein
Δ θ=[Δ θx Δθy Δθz]TFor (tk,tk+1] gyro output angle increment in the sampling period, unit：rad；
For (tk,tk+1] n systems turn over compared with i systems in the update cycle angle.
For e systems compared with i systems rotation angular speed n systems projection,For n systems compared with the angular speed of e systems in n
The projection fastened is calculated by following two formula：
Speed, latitude and radius of curvature in formula were the results of upper navigation calculation update cycle.Finally carry out quaternary
Number normalized
Obtain updated attitude quaternion
The speed increment Δ v of accelerometer output obtains the velocity component that geographical coordinate fastens via coordinate transform
Wherein, Δ v=[Δ vx Δvy Δvz]TFor the speed increment of accelerometer output.
The component of acceleration that geographical coordinate is fastened is
fn=Δ vn/h
Wherein, f is rememberedn=[fE fN fU]T。
Speed updates initial time, vn(0)=[0 0 0]T；
K=0, when 1,2 ..., in a speed update cycle (tk,tk+1] in, speed is updated to
Wherein,
δ A are harmful acceleration, are calculated as follows：
Initial time, L (0), λ (0) and S (0) are latitude, longitude and the elevation of bookbinding；
K=0, when 1,2 ..., in speed update cycle (tk, a tk+1] in, location updating is
Step 2 is used as using the location information of satellite positioning and navigation system with reference to information, the location information with inertial navigation system
Data fusion is carried out, convergence strategy is that the error propagation principles of foundation inertial navigation system determine mathematical model, utilizes Kalman filtering
Device carries out On-line Estimation and calibration to the error state of inertial navigation system navigation information
It is to appearance on the basis of pure-inertial guidance resolving using external information (defend and lead) that inertia, which is defended and leads integrated navigation system,
State misalignment is estimated and is corrected, and the process of resetting position and speed.Under integrated navigation state, equipment can keep optimal
Precision.Integrated navigation uses measurement information of the position as Kalman filter for defending guiding systems, and flow is as shown in Figure 2.
Kalman filtering one-step prediction is divided into state transfer matrix Φk,k-1Calculating, input noise variance matrix
Calculating, status predicationP is predicted with error variancek,k-1Calculating three phases：
(1) state transfer matrix Φk,k-1Calculating
Remember (tk-1,tk] for a predetermined period, h=tk-tk-1.Predetermined period h is generally shorter, and state transfer matrix calculates such as
Under
Wherein,
The variable of every element can be calculated by specific force coordinate transform, speed update, location updating and obtained in matrix,
In,
L is latitude, unit：rad；；
vEFor east orientation speed, unit：m/s；
vNFor north orientation speed, unit：m/s；
vUFor vertical velocity, unit：m/s；
REFor the radius of curvature of the vertical plane normal of meridian plane, unit：m；
RNFor the radius of curvature on meridian plane, unit：m；
fEFor geographic coordinate system east orientation acceleration, unit：m/s2；
fNFor geographic coordinate system north orientation acceleration, unit：m/s2；
fUFor geographic coordinate system vertical acceleration, unit：m/s2；
ωieFor rotational-angular velocity of the earth, ωie=7.292115 × 10-5rad/s.
(2) input noise variance matrixCalculating
The covariance matrix of the system noise of continuous system i.e. three gyro and three accelerometer vector W (t) are Q (t), then
The variance matrix of input noise is
Qq=G (t) Q (t) GT(t)
Wherein, Q (t) is constant, and G (t) is noise inputs matrix, is rewritten as follows：
Obtain the input noise variance Q of continuous systemqThe input noise variance of Kalman filter is calculated afterwardsIt is as follows：
(3) status predicationP is predicted with error variancek,k-1Calculating
Initial time is right as k=0And P0It is initialized；
K=0, when 1,2 ..., recurrence calculation
It is not timed out when the filtering update cycle, it is updated without filtering, continues to predict, made
Pk=Pk,k-1
When filtering the update cycle then,PkIt updates and calculates by the filtering of next section.
When filtering time is then filtered update, the filtering update cycle is generally the External Reference information update cycle, filters
Update cycle is set to 1s, is divided into four-step calculation：
(1) measure and calculate：
Measuring value is calculated as follows：
Subscript s represents that Strapdown Inertial Navigation System calculates and outputs, and subscript r represents reference data output.
vsE、vsN、vsUTo resolve east orientation speed, north orientation speed, vertical velocity, unit：m/s；
Ls、λsTo resolve latitude, longitude, unit：rad；
SsTo solve calculated altitude, unit：m；
vrE、vrN、vrUFor reference velocity, unit：m/s；
Lr、λrFor bookbinding latitude, longitude, unit rad；
SrFor reference altitude, unit：m.
(2) filtering gain calculates
Filtering gain K is calculated as followsk：
Wherein,
Pk,k-1It is calculated for error variance prediction；
Hk=[06×3 I6×6 06×6]；
Rk=diag [(Rve)2 (Rvn)2 (Rvu)2
(Rlat)2 (Rlon)2 (Rh)2]。
(3) state-updating
State estimation is calculated as follows
Wherein,It is calculated for status predication.
(4) error variance updates
Error variance P is calculated as followsk：
The moment is corrected when system timer reaches, is entered certainly as initial value using revised attitude quaternion, speed, position
Leading boat, it is assumed that tkMoment is correction time point：
(1) attitude quaternion amendment
tkMoment is estimated to obtain misalignment φ using Kalman filterE、φN、φU, it is correspondingThe the 1st, 2,3 element,
Correction angle is denoted as φc=[φE φN φU]T, t is corrected using Quaternion MethodkThe attitude quaternion at moment
Wherein,
(2) speed amendment
tkMoment is estimated to obtain velocity error amount δ v using Kalman filterE、δvN、δvU, it is correspondingThe the 4th, 5,6 member
Element corrects tkThe computing speed at moment：
(3) position correction
tkMoment is estimated to obtain site error amount δ L, δ λ, δ S using Kalman filter, correspondingThe the 7th, 8,9 member
Element corrects tkThe resolving position at moment：
Guiding systems fault diagnosis and treatment is defended in step 3, anti-interference integrated navigation system
The fault diagnosis and treatment of integrated navigation system mainly for defending that guiding systems generate when being subject to external interference therefore
Barrier carries out inline diagnosis and is isolated.Using the Kalman filter of integrated navigation system as diagnostic tool.Using consistent
Property examine χ2Method of inspection is derived from the measured value for defending guiding systems failure by isolating, realizes jamproof inertial navigation system posture course
Calibration.Newly breath namely residual error can indicate whether measurement is consistent with state estimation for the measurement of Kalman filter.It is supervised using new breath
It is the χ based on residual error to survey2Guiding systems failure is defended in the big mutation of method of inspection detection, and small slow change is detected using innovation sequence monitoring
Defend guiding systems failure.Specific method is as follows：
(1) new breath monitoring
Newly breath monitoring algorithm flow is：If system failure (is walked) before k-1 steps including k-1, by Kalman filtering
The estimate of obtained -1 step of kthIt should be correct, the one of kth moment system mode is can obtain by the state equation of system
Walk predicted valueI.e.
It can thus be concluded that the predicted value of k moment system measurements
If actual measurement information z outside the k momentkBe it is correct, then it measure predicted value between residual error δ zk -It should take
It is distributed from zero mean Gaussian white noise
Its variance is
When defending guiding systems and breaking down, residual error δ zk -No longer it is just the Gaussian sequence of zero-mean.By detecting δ
zk -Statistical property can differentiate and defend whether guiding systems break down.
Construct statisticWhen measurement information is normal, λz(k) χ that degree of freedom is m is obeyed2Point
Cloth, and when measurement information exception, λz(k) χ that degree of freedom is m is no longer obeyed2Distribution.Using following criterion：
A) λ is worked asz(k)≤χα 2When, it is believed that external measurement information is normal；
B) λ is worked asz(k) ＞ χα 2When, it is believed that external measurement information failure.
Wherein χα 2For detection threshold value, α is false alarm rate.
(2) innovation sequence monitors
Deviation that is smaller between state estimation and slowly establishing is measured, newest N number of measurement can be passed through and form system
Meter is examined to recognize, and the new test statistics that ceases is：
Wherein
As long as covariance Cμ -Correctly, which is exactly to meet the χ with m degree of freedom2It is distributed, here m
It is the dimension for measuring vector, by sδz,kComparison with threshold value is exactly the χ of information sequence2It examines.
Above two inspection result as measured in Fig. 2 whether effective criterion, work as χ2Statistic in inspection exceeds threshold
During value, then it can determine that and defend guiding systems failure, measurement information is unavailable at this time, and Kalman filter is updated without measuring,
Fault message is isolated, the posture course of inertial navigation system is avoided to be polluted by fault message.
It is emphasized that embodiment of the present invention is illustrative rather than limited, therefore present invention bag
The embodiment being not limited to described in specific embodiment is included, it is every by those skilled in the art's technique according to the invention scheme
The other embodiment drawn, also belongs to the scope of protection of the invention.
Claims (8)
1. a kind of inertia defends the anti-interference posture course calibration method of long endurance for leading integrated navigation system, it is characterised in that including with
Lower step：
Step 1, in inertial navigation system, carry out inertial reference calculation output posture course, speed and location information and simultaneously update；
Step 2 is used as using the location information of satellite positioning and navigation system with reference to information, is carried out with the location information of inertial navigation system
Data fusion, convergence strategy is that the error propagation principles of foundation inertial navigation system determine mathematical model, and utilizes Kalman filter
On-line Estimation and calibration are carried out to the error state of inertial navigation system navigation information.
2. inertia according to claim 1 defends the anti-interference posture course calibration method of long endurance for leading integrated navigation system,
It is characterized in that：Include the following steps after step 2：It defends to lead in inertia and carries out defending guiding systems fault diagnosis in integrated navigation system
With isolating.
3. inertia according to claim 1 or 2 defends the long endurance anti-interference posture course calibration side for leading integrated navigation system
Method, it is characterised in that：The step 1 forms inertial navigation system using three gyroscopes and three acceleration and carries out inertial navigation solution
It calculates, specific method is：By gather the Output speed data of gyroscope and deduct rotational-angular velocity of the earth and involve angle speed
Degree, is calculated attitude angle；The acceleration of accelerometer measures carries out coordinate transform to geographic coordinate system by Direct cosine matrix
North orientation, east orientation, day on axis, the acceleration fastened of integration geographical coordinate simultaneously deducts the influence of gravity and harmful acceleration and obtains
North orientation, east orientation and the sky orientation speed of geographic coordinate system；Using the north orientation of geographic coordinate system, east orientation speed, and consider the song of the earth
Longitude and latitude is calculated in rate radius.
4. inertia according to claim 1 or 2 defends the long endurance anti-interference posture course calibration side for leading integrated navigation system
Method, it is characterised in that：The concrete methods of realizing of the step 2 includes：
(1) Kalman filtering one-step prediction step：
(2) when filtering time is then filtered update step；
(3) moment is corrected when system timer reaches, is entered certainly as initial value using revised attitude quaternion, speed, position
Main navigation step.
5. inertia according to claim 4 defends the anti-interference posture course calibration method of long endurance for leading integrated navigation system,
It is characterized in that：The step (1) includes the calculating of state transfer matrix, the calculating of input noise variance matrix and status predication and mistake
The calculating of poor variance prediction.
6. inertia according to claim 4 defends the anti-interference posture course calibration method of long endurance for leading integrated navigation system,
It is characterized in that：The step (2) includes measuring calculating, filtering gain calculating, state-updating and error variance update.
7. inertia according to claim 4 defends the anti-interference posture course calibration method of long endurance for leading integrated navigation system,
It is characterized in that：The step (3) includes attitude quaternion amendment, speed amendment and position correction process.
8. inertia according to claim 2 defends the anti-interference posture course calibration method of long endurance for leading integrated navigation system,
It is characterized in that：It is described defend guiding systems fault diagnosis and treatment method be：The Kalman for leading integrated navigation system is defended with inertia
Wave filter is as diagnostic tool, using consistency check χ2Method of inspection is derived from the measured value for defending guiding systems failure by isolating, real
Existing jamproof inertial navigation system posture course calibration；The measurement of Kalman filter newly cease instruction measurement with state estimation whether one
It causes；Guiding systems failure is defended using the big mutation of method of inspection detection of the new breath monitoring i.e. based on residual error, is monitored using innovation sequence
Detect it is small become slowly defend guiding systems failure.
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