CN107036595A - Deformation of hull angular estimation method based on interacting multiple model filters - Google Patents
Deformation of hull angular estimation method based on interacting multiple model filters Download PDFInfo
- Publication number
- CN107036595A CN107036595A CN201710185998.0A CN201710185998A CN107036595A CN 107036595 A CN107036595 A CN 107036595A CN 201710185998 A CN201710185998 A CN 201710185998A CN 107036595 A CN107036595 A CN 107036595A
- Authority
- CN
- China
- Prior art keywords
- inertial navigation
- interaction models
- deformation
- interaction
- sub
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Classifications
-
- 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
Abstract
The invention discloses the deformation of hull angular estimation method based on interacting multiple model filters, the basic model of deformation of hull angular estimation is initially set up, interaction models are resettled；By respectively arranging a set of Methods of Strapdown Inertial Navigation System in stem, stern, ship motion information is determined；Using the filter process ship motion information based on interaction models, estimation obtains deformation of hull angle.The inventive method, covers deformation angle dynamic range by setting up multiple interaction models, it is adaptable to the estimation of model parameter condition of uncertainty pontoon deformation angle in dynamic environment.
Description
Technical field
Field is deformed the present invention relates to Ship body, a kind of deformation of hull angle based on interacting multiple model filters is devised
Method of estimation.
Background technology
With the progress of science and technology, modern ships and ship-borne equipment are all fast towards the direction of high accuracy, high automation
Speed development, modern ships can all be provided with various navigation equipments and attacking and defending equipment, including various radars, optics see take aim at equipment, with
Track measuring apparatus, missile launcher etc..To ensure the normal operation of equipment, it is necessary to set up a unified spatial attitude benchmark.
But, ship is not an absolute rigid body, when riding the sea, due to deformation of hull angle, the precision of spatial attitude benchmark by
To serious restriction.Therefore accurate estimation deformation of hull angle suffers from significance for ship and ship-borne equipment, with wide
Application prospect.
When estimating deformation of hull angle, high requirement is proposed for the foundation for deforming angle model, but due in real navigation
In, the uncertain of deformation angle model parameter eventually influences estimated accuracy.Therefore in the case of model is uncertain, accurate estimation
Deformation of hull angle is to be worth the problem of further investigation.Do not know or change for structure and parameter, multiple-model estimator is a kind of
Very effective adaptive estimation method.
The content of the invention
It can remain to accurately estimate ship in the case of deformation angle Parameter uncertainties it is an object of the invention to provide one kind
The inertial measurement method that the deformation of hull is estimated based on interacting multiple model filters of body deformation angle.
The object of the present invention is achieved like this, a kind of deformation of hull angular estimation side based on interacting multiple model filters
Method, comprises the following steps：
Step one：A set of hull guider, i.e., main inertial navigation and sub- inertial navigation are respectively mounted in stem, ship stern, it is used to two sets
Lead the basic Filtering Model set up and consider deflection deformation；
The system mode vector of the basic Filtering Model is
In formula, δ V represent main inertial navigation and sub- inertial navigation system velocity error,Represent that main inertial navigation is missed with sub- inertial navigation system posture
Difference, ▽ and ε represent accelerometer bias and gyroscopic drift respectively, and ξ represents the fix error angle between main inertial navigation and sub- inertial navigation, θ
Deflection deformation angle is represented,Represent deflection deformation angular speed.
Filtering Model is
In formula, w is system noise matrix, and w~N (0, Q), Q is w variance；V is measurement variance matrix, v~N (0, Rv),
RvFor v variance.Wherein, F and G are respectively：
Wherein,
I represents unit matrix.
Wherein, Vx, VyMain inertial navigation east orientation, north orientation speed, ω are represented respectivelyieEarth rotation angular speed is represented,Represent local
Latitude, R represents earth radius,Sub- inertial navigation attitude matrix is represented, subscript n represents navigational coordinate system, and the sub- inertial navigation carriers of subscript s are sat
Mark system, fx, fy, fzThe specific force along northeast day direction, β=[β are represented respectivelyx βy βz], and βx, βy, βzNortheast old name for the Arabian countries in the Middle East is represented respectively
To deflection deformation parameter.
Step 2：, according to the uncertainty of deflection deformation parameter, interaction models are built using basic Filtering Model；
Described interaction models are：Wherein,Respectively by inciting somebody to actionIn
β is replaced by β1,β2,...,βnObtain.
Wherein,
Wherein, β1,β2,...,βnFor deflection deformation parameter vector；c1,c2,...,cnFor interaction models constant parameter；N is
Set interaction models number.
Step 3：Main inertial navigation completes initially to be aligned and carries out inertial reference calculation with sub- inertial navigation system, in real time two sets of inertial navigations of collection
It is inertia device measurement data, the navigation calculation data of output；Interaction models wave filter is initialized；
Step 4：The resolving of model filter is interacted, deformation of hull angular estimation result is obtained.
(1) first, input interaction：
Wherein：For the input of j-th of interaction models wave filter, resolved for the k moment；For i-th of interaction
State estimation of the model filter at the k-1 moment；Inputted for the covariance of j-th of interaction models wave filter, for k
Moment resolves；For i-th of interaction models wave filter the k-1 moment covariance.J=1,2 ..., n；I=1,2 ..., n.
It is defeated to j-th of interaction models wave filter of k moment for i-th of interaction models wave filter estimated result of k-1 moment
The transition probability entered；WhereinFor j-th of interaction models prediction probability,For
The probability of i-th of model of k-1 moment；pijFor probability transfer matrix P element,N is set interaction
Number of Models.
(2) each interaction models wave filter is filtered resolving, then through interaction output, obtains total estimated result；And protect
The filtering calculation result of each interaction models wave filter is deposited, inputs and interacts for subsequent time；
It is described interaction output expression formula be
Total state estimationCalculate:
Total covariance estimation Pk|kCalculate：
Wherein,For the probability of j-th of interaction models of k moment.
A kind of deformation of hull angular estimation method based on interacting multiple model filters, in addition to：Using speed plus angular speed
Match pattern；
Measurement in measurement equation is
Z=[δ Vx δVy δωx δωy δωz]T
In formula, δ Vx, δ VyRepresent main inertial navigation and sub- inertial navigation speed difference, δ ωx,δωy,δωzRepresent main inertial navigation and sub- inertial navigation angle
Speed difference.
Measurement matrix H is：
Wherein
ω1x、ω1y、ω1zAngular speed of the main inertial navigation in the output of northeast day direction direction is represented respectively.
The inventive method has the advantages that：
First, when setting up the mathematical modeling at deformation of hull angle, it is contemplated that influence of the Parameter uncertainties to filter result, more accord with
Close the truth in real navigation；
2nd, state estimation is carried out using interaction models wave filter, is interacted by input interaction and output, make deformation angular estimation
Ratio of precision conventional Kalman filtering estimated accuracy is higher.
Brief description of the drawings
Fig. 1 is the deformation of hull estimation flow chart of the inventive method.
Fig. 2 is resolving structure chart of the inventive method in the case of 3 interaction models.
Fig. 3 is the dynamic deformation angular estimation error schematic diagram of the inventive method.
Fig. 4 is the static deformation angle evaluated error schematic diagram of the inventive method.
Embodiment
The present invention is described in more detail below in conjunction with the accompanying drawings：
Step one：A set of hull guider, i.e., main inertial navigation and sub- inertial navigation are respectively mounted in stem, ship stern, it is used to two sets
Lead and set up basic Filtering Model；
The system mode vector of the basic Filtering Model is
In formula, δ V represent main inertial navigation and sub- inertial navigation system velocity error,Represent that main inertial navigation is missed with sub- inertial navigation system posture
Difference, ▽ and ε represent accelerometer bias and gyroscopic drift respectively, and ξ represents the fix error angle between main inertial navigation and sub- inertial navigation, θ
Deflection deformation angle is represented,Represent deflection deformation angular speed.
Deformation of hull model is set up based on speed plus angular speed matching method, selecting system state vector is
In formula, δ V represent main inertial navigation and sub- inertial navigation system velocity error,Represent that main inertial navigation is missed with sub- inertial navigation system posture
Difference, ▽ and ε represent accelerometer bias and gyroscopic drift respectively, and ξ represents the fix error angle between main inertial navigation and sub- inertial navigation, θ
Deflection deformation angle is represented,Represent deflection deformation angular speed.It is navigational coordinate system to choose northeast day geographic coordinate system, due to be
Measured on hull, ignore sky orientation speed and day to accelerometer component, so state vector 19 is tieed up.
By inertial navigation elementary error equation, it can obtain
Subscript n represents navigational coordinate system in formula, and subscript i represents inertial coodinate system, and subscript e represents terrestrial coordinate system, subscript b
Carrier coordinate system is represented, it is navigational coordinate system to choose northeast day geographic coordinate system.F represents specific force,Represent earth rotation angle speed
Rate navigational coordinate system projection,Projection of the hull with respect to earth movements angular speed under navigation system is represented,With
It is then difference of the main inertial navigation to sub- two corresponding angular speeds of inertial navigation.It is the angle speed of relative inertness system for navigation
Rate,Represent by inertial reference calculationAnd it is real between error.Represent strap-down matrix.
Accelerometer bias ▽ and gyroscopic drift ε are the main source of error of inertial navigation system, according to gyroscopic drift
Characteristic, generally includes the Random Constant Drift ε of gyro0, slow become drift εrBecome drift ε with fastg.Gyroscopic drift is represented by：
Similar with gyro drift error model analysis, accelerometer error model is generally also classified into three kinds of components, but is leading
In design process of navigating, random constant error, i.e. accelerometer biased error are generally only considered
Fix error angle between boss's inertial navigation is considered as constant value, i.e.,：
Because naval vessel is influenceed by different sea situations across the sea, its Dynamic flexural deforms random under being driven with random noise
Process is approximate, and this characteristic and markoff process under white noise acoustic jamming are much like, therefore, using second order markoff process
Carry out the simulation of the deformation of hull.Three axial deflection angle equations can be obtained
Wherein β is deflection deformation parameter, and its size is relevant with correlation time
βi=2.146/ τi(i=x, y, z) (7)
τiIt is the deformation correlation time on corresponding axle.ηiIt is white noise, its variance size is by parameter QηiDetermine
σiIt is then deformation angle θiVariance.
The Filtering Model set up is
In formula, w is system noise matrix, and w~N (0, Q), Q is w variance；V is measurement variance matrix, v~N (0, Rv),
RvFor v variance.Wherein, F and G are respectively：
Wherein,
I represents unit matrix.
Wherein, Vx, VyMain inertial navigation east orientation, north orientation speed, ω are represented respectivelyieEarth rotation angular speed is represented,Represent local
Latitude, R represents earth radius,Sub- inertial navigation attitude matrix is represented, subscript n represents navigational coordinate system, and the sub- inertial navigation carriers of subscript s are sat
Mark system, fx, fy, fzThe specific force along northeast day direction, β=[β are represented respectivelyx βy βz], and βx, βy, βzNortheast old name for the Arabian countries in the Middle East is represented respectively
To deflection deformation parameter.
The present invention adds the measurement in angular speed match pattern, measurement equation to be using speed
Z=[δ Vx δVy δωx δωy δωz]T (10)
In formula, δ Vx, δ VyRepresent main inertial navigation and sub- inertial navigation speed difference, δ ωx,δωy,δωzRepresent main inertial navigation and sub- inertial navigation angle
Speed difference.
Measurement matrix H is：
Wherein
ω1x、ω1y、ω1zAngular speed of the main inertial navigation in the output of northeast day direction direction is represented respectively.
Step 2：, according to the uncertainty of deflection deformation parameter, interaction models are built using basic Filtering Model；
Described interaction models are：Wherein,Respectively by inciting somebody to actionIn
β is replaced by β1,β2,...,βnObtain.
Wherein,
Wherein, β1,β2,...,βnFor deflection deformation parameter vector；c1,c2,...,cnFor interaction models constant parameter；N is
Set interaction models number.
Uncertainty according to deflection deformation parameter is divided into 3 parallel interaction models wave filters, as shown in Figure 2.
In above-mentioned deformation measurement model, deflection deformation parameter is difficult to accurate acquisition in advance, and this results in set up mould
There is error in type, be exactly to be worked using multiple filter parallels using multiple model filtering method, and these wave filters then cover mould
The excursion of type error.By the way that deflection deformation parameter is divided evenly into 3 subintervals, the number of division is of model
Number, i.e. n=3.Obtained after Optimal Parameters：
Step 3：Main inertial navigation completes initially to be aligned and carries out inertial reference calculation with sub- inertial navigation system, in real time two sets of inertial navigations of collection
It is inertia device measurement data, the navigation calculation data of output；Interaction models wave filter is initialized；
Step 4：Interact the resolving of model filter；
(1) first, input interaction：
Wherein：For the input of j-th of interaction models wave filter, resolved for the k moment；For i-th of interaction
State estimation of the model filter at the k-1 moment；Inputted for the covariance of j-th of interaction models wave filter, for k
Moment resolves；For i-th of interaction models wave filter the k-1 moment covariance.J=1,2 ..., n；I=1,2 ..., n.
It is defeated to j-th of interaction models wave filter of k moment for i-th of interaction models wave filter estimated result of k-1 moment
The transition probability entered；WhereinFor j-th of interaction models prediction probability,For
The probability of i-th of model of k-1 moment；pijFor probability transfer matrix P element,N is set interaction
Number of Models.
(2) each interaction models wave filter is filtered resolving, then through interaction output, obtains total estimated result；And protect
The filtering calculation result of each interaction models wave filter is deposited, inputs and interacts for subsequent time；
WithWithCarry out Kalman filtering：
One-step prediction
Predict covariance
Kalman filtering gain
Filtering estimation
Filter covariance estimation
The estimate that each model state and covariance are obtained after Kalman filtering after interactionWithIt will make respectively
It is that the state before the interaction of subsequent time and covariance are estimated.
Model probability updates：
The model probability after interaction is updated using likelihood functionModel j probability likelihood function is after interaction:
In above formula,For measurement residuals
For the covariance of corresponding measurement residuals
Model j probability is after then interacting
In above formula, c is normaliztion constant, and
WhereinFor j-th of model prediction probability after interaction.
The expression formula of the interaction output is total state estimationCalculate:
Total covariance estimation Pk|kCalculate：
Wherein,For the probability of j-th of interaction models of k moment.
In order to further illustrate beneficial effects of the present invention, emulation is carried out according to new filtering algorithm under the following conditions and tested
Card.
Assuming that main inertial navigation is error free, simulation parameter is chosen：Gyroscopic drift：εx=εy=εz=0.01 °/h accelerometers with
Machine zero is inclined:▽x=▽y=100 μ g, naval vessel is navigated by water with east orientation 10m/s speed uniform rectilinear, around axis of roll, pitch axis, course
The rocking tendency of axle is respectively:θpm=3 °, θrm=4 °, θym=5 °, wave initial angle and wave initial phase all assume that to be zero.
ByIt is assumed that rolling period is respectively Tp=10s, Tr=8s, Ty=6s.This emulates every kind of arithmetic result equal
Under the conditions of repeat 50 times, and count 50 Simulation result datas, as a result as shown in table 1, table 2 and Fig. 3, Fig. 4.By table 1, table
2 and Fig. 3, Fig. 4 understand, than traditional kalman filter method, the deformation angle evaluated error of the inventive method is smaller, and precision is more
It is high.
50 emulation average statisticals of the static deformation angle evaluated error of table 1
50 emulation average statisticals of the dynamic deformation angular estimation error of table 2.
Claims (2)
1. the deformation of hull angular estimation method based on interacting multiple model filters, it is characterised in that comprise the following steps：
Step one：A set of SINS is respectively mounted in stem, ship stern, i.e., main inertial navigation and sub- inertial navigation are built to two sets of inertial navigations
The vertical basic Filtering Model for considering deflection deformation；
The system mode vector of the basic Filtering Model is
In formula, δ V represent main inertial navigation and sub- inertial navigation system velocity error,Represent main inertial navigation and sub- inertial navigation system attitude error, ▽
Accelerometer bias and gyroscopic drift are represented respectively with ε, and ξ represents the fix error angle between main inertial navigation and sub- inertial navigation, and θ represents to scratch
Bent deformation angle,Represent deflection deformation angular speed；
The basic Filtering ModelExpression formula be
In formula, w is system noise matrix, and w~N (0, Q), Q is w variance；V is measurement variance matrix, v~N (0, Rv), RvFor v
Variance；Wherein, F and G are respectively：
Wherein,
I represents unit matrix；
Wherein, Vx, VyMain inertial navigation east orientation, north orientation speed, ω are represented respectivelyieEarth rotation angular speed is represented,Ground weft is worked as in expression
Degree, R represents earth radius,Sub- inertial navigation attitude matrix is represented, subscript n represents navigational coordinate system, the sub- inertial navigation carrier coordinates of subscript s
System, fx, fy, fzThe specific force along northeast day direction, β=[β are represented respectivelyx βy βz], and βx, βy, βzNortheast day direction is represented respectively
Deflection deformation parameter；
Step 2：According to the uncertainty of deflection deformation parameter, interaction models are built using basic Filtering Model；
Described interaction models are：Wherein,Respectively by inciting somebody to actionIn β substitute
For β1,β2,...,βnObtain；Wherein,
In formula, β1,β2,...,βnFor deflection deformation parameter vector；c1,c2,...,cnFor interaction models constant parameter；N is set
Put interaction models number；
Step 3：Main inertial navigation completes initially to be aligned and carries out inertial reference calculation with sub- inertial navigation system, and two sets of inertial navigations of collection in real time are defeated
Inertia device measurement data, the navigation calculation data gone out；Interaction models wave filter is initialized；
Step 4：The resolving of model filter is interacted, deformation of hull angular estimation result is obtained；
The resolving of interaction models wave filter includes
(1) input interaction：
Inputting interactive expression formula is：
Wherein：For the input of j-th of interaction models wave filter, resolved for the k moment；For i-th of interaction models
State estimation of the wave filter at the k-1 moment；Inputted for the covariance of j-th of interaction models wave filter, for the k moment
Resolve；For i-th of interaction models wave filter the k-1 moment covariance；J=1,2 ..., n；I=1,2 ..., n；For the transfer of i-th of interaction models wave filter estimated result of k-1 moment to j-th of interaction models wave filter input of k moment
Probability；WhereinFor j-th of interaction models prediction probability,For the k-1 moment
The probability of i-th of model；pijFor probability transfer matrix P element,N is set interaction models
Number；
(2) each interaction models wave filter is filtered resolving, then through interaction output, obtains total estimated result；And preserve each
The filtering calculation result of individual interaction models wave filter, inputs for subsequent time and interacts；
Total state estimation in the interaction outputCalculation expression is:
Total covariance estimation Pk|kCalculation expression is：
Wherein,For the probability of j-th of interaction models of k moment.
2. the deformation of hull angular estimation method as claimed in claim 1 based on interacting multiple model filters, it is characterised in that adopt
With speed plus angular speed match pattern；
Measurement is
Z=[δ Vx δVy δωx δωy δωz]T
In formula, δ Vx, δ VyRepresent main inertial navigation and sub- inertial navigation speed difference, δ ωx,δωy,δωzRepresent main inertial navigation and sub- inertial navigation angular speed
Difference；
Measurement matrix H is：
Wherein
ω1x、ω1y、ω1zAngular speed of the main inertial navigation in the output of northeast day direction direction is represented respectively.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710185998.0A CN107036595A (en) | 2017-03-27 | 2017-03-27 | Deformation of hull angular estimation method based on interacting multiple model filters |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710185998.0A CN107036595A (en) | 2017-03-27 | 2017-03-27 | Deformation of hull angular estimation method based on interacting multiple model filters |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN107036595A true CN107036595A (en) | 2017-08-11 |
Family
ID=59533711
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201710185998.0A Pending CN107036595A (en) | 2017-03-27 | 2017-03-27 | Deformation of hull angular estimation method based on interacting multiple model filters |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN107036595A (en) |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107764261A (en) * | 2017-10-13 | 2018-03-06 | 北京航空航天大学 | A kind of distributed POS Transfer Alignments analogue data generation method and system |
| CN112097728A (en) * | 2020-09-17 | 2020-12-18 | 中国人民解放军国防科技大学 | Inertial dual-vector matching deformation measurement method based on inverse solution inertial navigation system |
| CN114166217A (en) * | 2021-11-25 | 2022-03-11 | 哈尔滨工程大学 | Carrier flexural deformation angle estimation method based on variable structure multi-model |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101650186A (en) * | 2009-09-23 | 2010-02-17 | 哈尔滨工程大学 | Method for measuring ship deck static deformation angle |
| CN101660913A (en) * | 2009-09-23 | 2010-03-03 | 哈尔滨工程大学 | Dynamic deformation measurement method of ship deck of strapdown inertial navigation system |
-
2017
- 2017-03-27 CN CN201710185998.0A patent/CN107036595A/en active Pending
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101650186A (en) * | 2009-09-23 | 2010-02-17 | 哈尔滨工程大学 | Method for measuring ship deck static deformation angle |
| CN101660913A (en) * | 2009-09-23 | 2010-03-03 | 哈尔滨工程大学 | Dynamic deformation measurement method of ship deck of strapdown inertial navigation system |
Non-Patent Citations (1)
| Title |
|---|
| 徐博等: "基于交互式多模型滤波的船体变形惯性测量方法", 《中国惯性技术学报》 * |
Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107764261A (en) * | 2017-10-13 | 2018-03-06 | 北京航空航天大学 | A kind of distributed POS Transfer Alignments analogue data generation method and system |
| CN107764261B (en) * | 2017-10-13 | 2020-03-24 | 北京航空航天大学 | Simulation data generation method and system for distributed POS (point of sale) transfer alignment |
| CN112097728A (en) * | 2020-09-17 | 2020-12-18 | 中国人民解放军国防科技大学 | Inertial dual-vector matching deformation measurement method based on inverse solution inertial navigation system |
| CN112097728B (en) * | 2020-09-17 | 2021-07-30 | 中国人民解放军国防科技大学 | Inertial double-vector matching deformation measurement method based on inverse solution combined inertial navigation system |
| CN114166217A (en) * | 2021-11-25 | 2022-03-11 | 哈尔滨工程大学 | Carrier flexural deformation angle estimation method based on variable structure multi-model |
| CN114166217B (en) * | 2021-11-25 | 2023-07-21 | 哈尔滨工程大学 | Carrier deflection deformation angle estimation method based on variable structure multiple models |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN103575299B (en) | Utilize dual-axis rotation inertial navigation system alignment and the error correcting method of External Observation information | |
| CN104655131B (en) | Inertial navigation Initial Alignment Method based on ISTSSRCKF | |
| CN106885570A (en) | A kind of tight integration air navigation aid based on robust SCKF filtering | |
| CN105737823B (en) | A kind of GPS/SINS/CNS Combinated navigation methods based on five rank CKF | |
| CN106871928B (en) | Strap-down inertial navigation initial alignment method based on lie group filtering | |
| CN108731670A (en) | Inertia/visual odometry combined navigation locating method based on measurement model optimization | |
| CN109443379A (en) | A kind of underwater anti-shake dynamic alignment methods of the SINS/DVL of deep-sea submariner device | |
| CN105806363B (en) | The underwater large misalignment angle alignment methods of SINS/DVL based on SRQKF | |
| CN103759742A (en) | Serial inertial navigation nonlinear alignment method based on fuzzy self-adaptation control technology | |
| CN108226980A (en) | Difference GNSS and the adaptive close coupling air navigation aids of INS based on Inertial Measurement Unit | |
| CN105424036A (en) | Terrain-aided inertial integrated navigational positioning method of low-cost underwater vehicle | |
| CN103776453A (en) | Combination navigation filtering method of multi-model underwater vehicle | |
| CN103913181A (en) | Airborne distribution type POS (position and orientation system) transfer alignment method based on parameter identification | |
| CN103389506A (en) | Adaptive filtering method for strapdown inertia/Beidou satellite integrated navigation system | |
| CN107110650A (en) | The method of estimation of affined navigational state in terms of observability | |
| CN103743395A (en) | Time delay compensation method in inertia gravity matching combined navigation system | |
| CN109059914B (en) | Projectile roll angle estimation method based on GPS and least square filtering | |
| CN106940193A (en) | A kind of ship self adaptation based on Kalman filter waves scaling method | |
| CN103454662B (en) | A kind of SINS/ Big Dipper/DVL based on CKF combines alignment methods | |
| CN103927289A (en) | Method for determining preliminary orbit of low-orbit target satellite according to space-based satellite angle measurement data | |
| CN109739088B (en) | Unmanned ship finite time convergence state observer and design method thereof | |
| CN109211231B (en) | Cannonball attitude estimation method based on Newton iteration method | |
| CN107036595A (en) | Deformation of hull angular estimation method based on interacting multiple model filters | |
| CN111795708A (en) | Self-adaptive initial alignment method of land inertial navigation system under base shaking condition | |
| CN104634348B (en) | Attitude angle computational methods in integrated navigation |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20170811 |
|
| RJ01 | Rejection of invention patent application after publication |