CN106595705A - GPS-based flight inertial initial reference error estimation method - Google Patents
GPS-based flight inertial initial reference error estimation method Download PDFInfo
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- CN106595705A CN106595705A CN201611048571.8A CN201611048571A CN106595705A CN 106595705 A CN106595705 A CN 106595705A CN 201611048571 A CN201611048571 A CN 201611048571A CN 106595705 A CN106595705 A CN 106595705A
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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
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- 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
- G01C21/165—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 combined with non-inertial navigation instruments
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Abstract
The invention provides a GPS-based flight inertial initial reference error estimation method. According to an inertial navigation error transmission mechanism, an inertial initial reference error model is built, and an inertial initial reference error is estimated through a standard Kalman filter method based on GPS information as observed quantity. Mathematical modelling technique and carrying flight test results show that the method provided by the invention can effectively estimate the inertial reference error so that the accuracy and reliability of the navigation system are improved.
Description
Technical field
The present invention relates to Guidance & Navigation technical field, more particularly to a kind of in-flight inertia initial baseline based on GPS
Bias estimation method.
Background technology
Some guided missiles adopt direct laying of fire or Transfer Alignment, can produce larger initial baseline deviation, can so cause used
Property navigation error accelerated accumulation, it is therefore necessary to take measures estimate initial baseline precision with suppress inertial navigation error diverging speed
Degree.
The content of the invention
It is an object of the invention to overcome the deficiencies in the prior art, there is provided a kind of in-flight inertia based on GPS is initial
Datum drift method of estimation, the method set up inertia initial baseline buggy model according to inertial navigation error propagation mechanism, utilize
GPS information estimates inertia initial baseline deviation using standard Kalman filtering method as observed quantity.
The above-mentioned purpose of the present invention is realized by below scheme:
A kind of in-flight inertia initial baseline bias estimation method based on GPS, comprises the following steps:
(1), in moment k, calculate state vector predictive value State vector for moment k-1 is estimated
Value, the initial value of the state vector estimated valueIt is set as null vector;Wherein, in Kalman filtering, definition status vector
X=[φx0 φy0 φz0 δX0 δY0 δZ0 δVx0 δVy0 δVz0]T;φx0、φy0、φz0Respectively guided missile is in inertial coodinate system
Under X to initial attitude misalignment, Y-direction initial attitude misalignment, Z-direction initial attitude misalignment;δX0、δY0、δZ0Respectively lead
X of the bullet under inertial coodinate system is to initial position error, Y-direction initial position error, Z-direction initial position error;δVx0、δVy0、δ
Vz0Respectively X of the guided missile under inertial coodinate system is to initial velocity error, Y-direction initial velocity error, Z-direction initial velocity error;
(2), in moment k, predict covariance matrix Pk|k-1=Pk-1;Pk-1It is for the estimate covariance matrix of moment k-1, described
The initial value of estimate covariance matrix is P0, P0For 9 × 9 dimension matrixes of setting;
(3), in moment k, calculate gain matrix Kk=Pk|k-1HT(H Pk|k-1HT+R)-1;Wherein, H is the observation square of setting
Battle array, R are the noise variance matrix of setting:
(4), calculate the state vector estimated value of moment kWherein, ZkFor outside
The observation vector of the moment k of offer;In Kalman filtering, observation vector Z=[δ X δ Y δ Z δ V are definedx δVy δVz]T;δ
X, δ Y, δ Z be respectively X that inertial navigation system and GPS system measure to the difference of position, the difference of Y-direction position, Z-direction position difference;δVx、δ
Vy、δVzThe respectively X of inertial navigation system and GPS system measurement to the difference of speed, the difference of Y-direction speed, Z-direction speed difference;
(5), calculate moment k estimate covariance matrix Pk=(I-KkH)Pk|k-1, I is unit matrix;
(6), in the initial value datum drift cycle estimator of setting, repeat step (1)~(5), by Kalman filtering meter
Calculation obtains initial position error, initial velocity error and initial attitude misalignment.
The above-mentioned in-flight inertia initial baseline bias estimation method based on GPS, in step (3), observing matrix H and
Noise variance matrix R is respectively set as:
Wherein:Sx、Sy、SzRespectively inertial navigation system provide inertial system X to, Y-direction, Z-direction apparent place;Wx、Wy、WzRespectively
Inertial navigation system provide inertial system X to, Y-direction, Z-direction apparent velocity; Respectively set inertial system under X to, Y-direction, Z
To position detection noise variance;Under the inertial system for respectively setting, X is to, Y-direction, Z-direction speed observation noise side
Difference.
The present invention compared with prior art, with advantages below:
Jing mathematical simulations technology and carrying flight test checking, the in-flight inertia initial baseline estimation of deviation based on GPS
Method can effectively estimate inertial reference deviation, reach the purpose of the precision and reliability that improve navigation system.
Description of the drawings
Fig. 1 is the flow chart of the in-flight inertia initial baseline bias estimation method based on GPS of the present invention.
Specific embodiment
The present invention is described in further detail with instantiation below in conjunction with the accompanying drawings:
The present invention sets up inertia initial baseline buggy model according to inertial navigation error propagation mechanism, is made using GPS information
For observed quantity, inertia initial baseline deviation is estimated using standard Kalman filtering method, flow process is implemented as shown in Figure 1.
First, set up initial baseline estimation of deviation state equation:
Wherein:State vector X=[φx0 φy0 φz0 δX0 δY0 δZ0 δVx0 δVy0 δVz0]T;φx0、φy0、φz0
Respectively X of the guided missile under inertial coodinate system is to initial attitude misalignment, Y-direction initial attitude misalignment, Z-direction initial attitude misalignment
Angle;δX0、δY0、δZ0At the beginning of respectively X of the guided missile under inertial coodinate system to initial position error, Y-direction initial position error, Z-direction
Beginning site error;δVx0、δVy0、δVz0Respectively X of the guided missile under inertial coodinate system is to initial velocity error, Y-direction initial velocity
Error, Z-direction initial velocity error;Sytem matrix F is 9 × 9 dimension null matrix.
Then, set up the observational equation of inertia initial baseline estimation of deviation:
Z=HX+V;
Wherein:Observation vector Z=[δ X δ Y δ Z δ Vx δVy δVz]T;δ X, δ Y, δ Z are respectively inertial navigation system and GPS systems
The X of unified test amount to the difference of position, the difference of Y-direction position, Z-direction position difference;δVx、δVy、δVzRespectively inertial navigation system and GPS system
The X of measurement to the difference of speed, the difference of Y-direction speed, Z-direction speed difference;V is observation noise vector;H is observing matrix, at this
Specifically it is set as in bright:
Wherein:Sx、Sy、SzRespectively inertial navigation system provide inertial system X to, Y-direction, Z-direction apparent place;Wx、Wy、WzRespectively
Inertial navigation system provide inertial system X to, Y-direction, Z-direction apparent velocity.
Kalman filter equation based on more than, the in-flight inertia initial baseline estimation of deviation based on GPS of the present invention
Method realizes that step is as follows:
(1), in moment k, calculate state vector predictive value State vector for moment k-1 is estimated
Value, the initial value of the state vector estimated valueIt is set as null vector;Wherein, in Kalman filtering, definition status vector
X=[φx0 φy0 φz0 δX0 δY0 δZ0 δVx0 δVy0 δVz0]T;φx0、φy0、φz0Respectively guided missile is in inertial coodinate system
Under X to initial attitude misalignment, Y-direction initial attitude misalignment, Z-direction initial attitude misalignment;δX0、δY0、δZ0Respectively lead
X of the bullet under inertial coodinate system is to initial position error, Y-direction initial position error, Z-direction initial position error;δVx0、δVy0、δ
Vz0Respectively X of the guided missile under inertial coodinate system is to initial velocity error, Y-direction initial velocity error, Z-direction initial velocity error;
(2), in moment k, predict covariance matrix Pk|k-1=Pk-1;Pk-1It is for the estimate covariance matrix of moment k-1, described
The initial value of estimate covariance matrix is P0, P0For 9 × 9 dimension matrixes of setting;
(3), in moment k, calculate gain matrix Kk=Pk|k-1HT(HPk|k-1HT+R)-1;Wherein, H is the observation square of setting
Battle array, R are the noise variance matrix of setting:
Wherein:Sx、Sy、SzRespectively inertial navigation system provide inertial system X to, Y-direction, Z-direction apparent place;Wx、Wy、WzRespectively
Inertial navigation system provide inertial system X to, Y-direction, Z-direction apparent velocity; Respectively set inertial system under X to, Y-direction, Z
To position detection noise variance;Under the inertial system for respectively setting, X is to, Y-direction, Z-direction speed observation noise side
Difference;
(4), calculate the state vector estimated value of moment kWherein, ZkFor outside
The observation vector of the moment k of offer;In Kalman filtering, observation vector Z=[δ X δ Y δ Z δ V are definedx δVy δVz]T;δ
X, δ Y, δ Z be respectively X that inertial navigation system and GPS system measure to the difference of position, the difference of Y-direction position, Z-direction position difference;δVx、δ
Vy、δVzThe respectively X of inertial navigation system and GPS system measurement to the difference of speed, the difference of Y-direction speed, Z-direction speed difference;
(5), calculate moment k estimate covariance matrix Pk=(I-KkH)Pk|k-1, I is unit matrix;
(6), in the initial value datum drift cycle estimator of setting, repeat step (1)~(5), by Kalman filtering meter
Calculation obtains initial position error, initial velocity error and initial attitude misalignment.
When concrete engineering is realized, the in-flight inertia initial baseline bias estimation method based on GPS of the present invention is by solid
The software changed in missile-borne computer realizes that during missile flight, Flight Control Software calls the method, initial to guided missile
Inertial reference deviation estimated, improves the navigation accuracy and accuracy at target of guided missile.
The above, only one specific embodiment of the present invention, but protection scope of the present invention is not limited thereto, and appoints
What those familiar with the art the invention discloses technical scope in, the change or replacement that can be readily occurred in, all
Should be included within the scope of the present invention.
The content not being described in detail in description of the invention belongs to the known technology of professional and technical personnel in the field.
Claims (2)
1. a kind of in-flight inertia initial baseline bias estimation method based on GPS, it is characterised in that comprise the following steps:
(1), in moment k, calculate state vector predictive value For the state vector estimated value of moment k-1, institute
State the initial value of state vector estimated valueIt is set as null vector;Wherein, in Kalman filtering, definition status vector X=
[φx0 φy0 φz0 δX0 δY0 δZ0 δVx0 δVy0 δVz0]T;φx0、φy0、φz0Respectively guided missile is under inertial coodinate system
X to initial attitude misalignment, Y-direction initial attitude misalignment, Z-direction initial attitude misalignment;δX0、δY0、δZ0Respectively guided missile
X under inertial coodinate system is to initial position error, Y-direction initial position error, Z-direction initial position error;δVx0、δVy0、δVz0
Respectively X of the guided missile under inertial coodinate system is to initial velocity error, Y-direction initial velocity error, Z-direction initial velocity error;
(2), in moment k, predict covariance matrix Pk|k-1=Pk-1;Pk-1For the estimate covariance matrix of moment k-1, the estimation
The initial value of covariance matrix is P0, P0For 9 × 9 dimension matrixes of setting;
(3), in moment k, calculate gain matrix Kk=Pk|k-1HT(H Pk|k-1HT+R)-1;Wherein, H be setting observing matrix, R
For the noise variance matrix of setting:
(4), calculate the state vector estimated value of moment kWherein, ZkThere is provided for outside
Moment k observation vector;In Kalman filtering, observation vector Z=[δ X δ Y δ Z δ V are definedx δVy δVz]T;δX、δY、
δ Z are respectively the difference of the X of inertial navigation system and GPS system measurement to position, the difference of Y-direction position, the difference of Z-direction position;δVx、δVy、δVz
The respectively X of inertial navigation system and GPS system measurement to the difference of speed, the difference of Y-direction speed, Z-direction speed difference;
(5), calculate moment k estimate covariance matrix Pk=(I-KkH)Pk|k-1, I is unit matrix;
(6), in the initial value datum drift cycle estimator of setting, repeat step (1)~(5) are calculated by Kalman filtering
To initial position error, initial velocity error and initial attitude misalignment.
2. a kind of in-flight inertia initial baseline bias estimation method based on GPS according to claim 1, its feature exist
In:In step (3), observing matrix H and noise variance matrix R are respectively set as:
Wherein:Sx、Sy、SzRespectively inertial navigation system provide inertial system X to, Y-direction, Z-direction apparent place;Wx、Wy、WzRespectively inertial navigation
System provide inertial system X to, Y-direction, Z-direction apparent velocity; X is set under inertial system respectively to, Y-direction, Z-direction position
Put observation noise variance;Under the inertial system for respectively setting X to, Y-direction, Z-direction speed observation noise variance.
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CN109357674A (en) * | 2018-12-07 | 2019-02-19 | 上海机电工程研究所 | A kind of GNSS and INS integrated navigation observed quantity introducing method |
CN110082115A (en) * | 2019-04-23 | 2019-08-02 | 哈尔滨工业大学 | A kind of online single-shot failure diagnostic method for carrier rocket |
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