CN102128625B - Initial matching method for use in gravimetric map matching in gravity-aided inertial navigation system - Google Patents
Initial matching method for use in gravimetric map matching in gravity-aided inertial navigation system Download PDFInfo
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Abstract
The invention discloses an initial matching method for use in gravimetric map matching in a gravity-aided inertial navigation system, which comprises: according to the characteristic of high short-term measurement precision of the inertial navigation system, building a geometric constraint model by using three parameters, namely running distance information L1 and L2, which are acquired by the inertial navigation system at adjacent moments t1 and t2 and t2 and t2, of a carrier body and relative steering angle theta at the moment t2 of the carrier body; and obtaining the initial value of the gravimetric map matching by according to isolines C1, C2 and C3 corresponding to the gravity values measured by a gravity sensor at the moments t1, t2 and t3 and according to a geometric constraint isoline matching algorithm. The method is an automatic initial matching method and has the characteristics of high precision and high robustness. The method can be used for initial matching in a passive navigation system such as landform/ geomagnetism/gravity-aided inertial navigation systems.
Description
Technical field
The present invention relates to the initial matching method of gravimetric map coupling in the gravity aided inertial navigation system, be primarily aimed at the initial matching method of gravimetric map matching algorithm in the gravity aided inertial navigation.
Background technology
With regard to the passive airmanship of earth physical field aided inertial navigation, be not a fresh problem, early start be the landform aided inertial navigation research of land, and obtain tangible achievement beginning of the eighties late 1970s.In recent years, by the geodetic surveying technological achievement, the theory and the method for inertia/gravity, the passive integrated navigation of inertia/earth magnetism have caused domestic and international research institution and scholar's attention equally, have carried out Study on Technology such as the navigation of gravity coupling, the navigation of earth magnetism coupling in succession.The normal method that adopts of the technology of gravity aided inertial navigation is to continue to use the correlation technique of terrain match mostly at present, mainly contains SITAN algorithm, TERCOM algorithm etc.No matter be the SITAN algorithm, or the TERCOM algorithm, its basic procedure all is to measure the geophysics field data on the carrier movement locus through the sensor in real time of carrying on the carrier; Simultaneously, the carrier positional information that provides according to inertial navigation system, from navigation with obtaining the geophysics field data the reference to gravitational figure; Give coupling with this two group data set then and resolve computing machine, utilize matching algorithm to confirm the best match position of carrier.
The data set matching problem can be traced back to the remote Sensing Image Analysis of later 1950s the earliest, and Hobrough has carried out similarity analysis to the remote sensing analog image first at that time, has proposed the notion of images match; To six the seventies, the research method of data set coupling is mostly based on the feature extraction to image, as; The quick Fourier transformation of Anuta (FFT) method; But,, make that the information of data set can not obtain reflection fully when feature extraction owing to extract the restriction of characterization method.Up to early eighties, Lucas has provided a kind of iterative algorithm to video image coupling, because this method directly searches for to image data set, so the method for Lucas kept the character of image fully, thereby guaranteed the accuracy of coupling.To the early 1990s; Chen and Medioni; People such as Besl and McKay and Zhang rises to the matching problem between the data set with various concrete matching problems respectively on the working foundation of Lucas; And independently proposed to find the solution the data set matching problem ICP (Iterated Closest Point, be called for short: the work of ICP) algorithm, especially Besl and McKey has become a basis of data set matching problem; The ICP method has also become the general approach of finding the solution the data set matching problem and has extensively been adopted, and has been widely used in gravimetric map (topomap/magnetic map) coupling of geophysical field aided inertial navigation.
The ICP algorithm is the research about global convergence; Can both work in any initial position error condition in theory; And in practical application because the influence of the factors such as selection of objective function, corresponding relation selection, alternative types and initial position; Nearly all existing method based on ICP all can only obtain the local optimum coupling, whether can obtain the optimum key of global registration and be the initial matching parameters of choice.Selection problem to initial matching; People such as Hugli have proposed the SIC-range method based on the initial parameter division; People such as Chetverikov are through carrying out " cutting " to the range of choice of corresponding point in each step iteration; And along with the carrying out of iteration progressively dwindles and revise the range of choice of corresponding point, above method mainly comes from the similarity coupling to static remote sensing images, does not require real-time.In gravity aided inertial navigation system; Owing to will guarantee long-time, the high-precision work of inertial navigation system; Must revise the systematic error of inertial navigation system itself in real time, so gravity aided inertial navigation system has real-time and reliability requirement to matching algorithm.
Summary of the invention
Technology of the present invention is dealt with problems: the deficiency that overcomes prior art; The initial matching method of gravimetric map coupling in a kind of gravity aided inertial navigation system is provided; Can improve the reliability and the real-time of gravity aided inertial navigation system effectively, thereby there is the defective that the gravimetric map matching algorithm lost efficacy under the mistake condition in the positional information that can eliminate and overcome in inertial navigation system output.
The technical scheme steps that the present invention adopts is following: the initial matching method of gravimetric map coupling in a kind of gravity aided inertial navigation system, and performing step is following:
The first step judges that carrier has got into gravity field adaptive area Ψ, chooses three continuous sampled points of gravity field sensor that carrier carries, and three pairing times of sampled point are respectively t
1, t
2And t
3Constantly.
Second goes on foot, and confirms the region of search Ω of carrier gravity match reference figure; Error profile characteristic function according to inertial navigation system that carrier carries; Confirm the distance error threshold value δ of current time inertia system; With the carrier current location information that inertial navigation system was provided is the center, and distance error threshold value δ is a radius, delimits the region of search Ω of gravity match reference figure.
The 3rd step made up high precision triangle geometry restricted model, and made up triangular space Γ.
In the 4th step, utilize gravity field sensor that carrier carries at t
1, t
2And t
3The gravity value of constantly being taked is obtained carrier at t
1, t
2And t
3The moment corresponding reference to gravitational field isoline C
1, C
2And C
3The point set P that is comprised
1, P
2And P
3
In the 5th step, based on triangle geometry restricted model isoline matching algorithm, it is right in all initial matching of current time to obtain carrier
These initial matching are the initial matching collection to the sets definition of forming
J is a natural number, and 1＜j＜N, N are a pairing set
The coupling logarithm that is comprised, p
j, q
j, m
jRepresent that respectively j initial matching is at isoline C
1, isoline C
2, isoline C
3Last pairing point.
The 6th step, adopt probability-weighted estimation model algorithm, the value function is these characteristics of quadratic function of the angular error factor and the distance error factor, and calculates initial matching and concentrate the cost value of respectively organizing data, finally obtains accurate initial matching value.
Delimit region of search Ω in said second step; Its process is: at first according to the error profile characteristic function and the error model of inertial navigation system, confirm the error of position information threshold value δ that inertial navigation system provides, the carrier current location that provides with inertial navigation system then is the center; The error threshold δ of inertial navigation system is a radius; Delimit region of search Ω, thereby reduce to guarantee that carrier actual position information falls within the regional Ω under the region of search raising search speed precondition.
Said the 3rd step makes up high precision triangle geometry restricted model, and the triangular space Γ of definite triangle geometry model.Its process is: at first, utilize the inertial navigation system high characteristics of measuring accuracy in short-term, obtain inertial navigation system at adjacent moment t
1t
2Between and t
2t
3Between record the range information L that carrier goes
1, L
2, and carrier is at t
2Relative steering angle θ constantly makes up high-precision triangular form geometrical constraint model; Then, choose arbitrary triangle, suppose that the leg-of-mutton length of side is respectively a, b and c, and a＞b＞c; Represent this triangle with two parameter b/a and c/a, thereby by (x, y) triangle that constitutes of three points in the space converts that (b/a c/a) representes that with a point this space is triangle space Γ in the space to.
Said the 5th step is obtained the initial matching collection of all possible positions of carrier based on triangle geometry restricted model isoline coupling
(j is a natural number, and 1＜j＜N, N are a pairing set
The coupling logarithm that is comprised, p
j, q
j, m
jRepresent that respectively j initial matching is at isoline C
1, isoline C
2, isoline C
3Last pairing point).Its process is: at first from point set P
1, P
2And P
3In get respectively that a bit to form triangle coupling right
Calculate coupling then respectively to each the limit length of side a of corresponding triangle of institute
i, b
iAnd c
i(i is a natural number, corresponding i of expression mate to); At last i coupling to projecting to triangle space, and judge whether subpoint falls in the triangular space Γ; Traversal point set P
1, P
2And P
3Middle having a few chosen subpoint and fallen into all interior couplings of triangular space Γ to forming the initial matching collection.
Said the 6th step is adopted probability-weighted estimation model algorithm; The value function is these characteristics of quadratic function of the angular error factor and the distance error factor; Calculate initial matching and concentrate the cost value of respectively organizing data, the detailed process that those group data that replace the value minimum are the final initial matching of carrier position is following:
The cost function that makes up is:
cost＝f(l，α) (1)
L representes the distance parameter between the correspondence position point that match point and inertial navigation system provide in the formula, and α representes the angle between the deflection of the corresponding point that deflection and inertial navigation system provided of match point.
From a pairing set
In optional one group of coupling right
It is right to calculate coupling respectively by formula (1)
Pairing three match point p
j, q
jAnd m
jCoupling cost value costp
j, costq
jAnd costm
j, it is right to mate
The coupling cost value
Choose
Middle pairing one group of minimum value is paired into the final initial matching value of carrier.
The present invention compares useful effect with existing technical method:
(1) to the real-time requirement; People such as present existing initial matching method such as Hugli have proposed the SIC-range method based on the initial parameter division; " cutting " method that people such as Chetverikov propose all is the similarity coupling to static remote sensing images, does not require real-time.Utilize the present invention; The high precision parameter that can directly utilize inertial navigation system to measure in short-term makes up the geometrical constraint model and combines the isoline matching algorithm directly to obtain high precision real-time and reliable initial matching parameter, thereby there is the defective that the gravimetric map matching algorithm lost efficacy under the mistake condition in the positional information that can eliminate and overcome in inertial navigation system output.
(2) to the requirement of system to the matching algorithm real-time; Domestic people such as Sun Feng utilize inertial navigation system short-time high-accuracy characteristics; Employing is based on the optimum isoline matching algorithm of error sum of squares cost function, and people such as Wu Taiqi have proposed a kind of gravimetric map matching process based on the straight-line segment mode, and these two kinds of methods all are in order to obtain high-precision initial position message; But they all do rectilinear motion with the hypothesis carrier is precondition, therefore in practical application, has certain limitation.The geometrical constraint model that the present invention proposes, it does the motion of any track applicable to carrier, has wide range of applications.
Description of drawings
Fig. 1 is a gravity aided inertial navigation ultimate principle block diagram;
Fig. 2 is a process flow diagram of the present invention;
Fig. 3 is the dead reckoning positioning principle block diagram of inertial navigation system;
The geometrical constraint model synoptic diagram that Fig. 4 makes up for the present invention;
The triangle space Γ synoptic diagram that Fig. 5 makes up for the present invention;
Fig. 6 is the isoline matching algorithm synoptic diagram that the present invention is based on the geometrical constraint model.
Embodiment
As shown in Figure 1, general main A, B, C and four modules of D of being divided into of traditional gravity aided inertial navigation system.The fundamental purpose of A module is that the gravity field sensor in real time of utilizing on the carrier to be carried is measured the A/W field data on the carrier running orbit; The fundamental purpose of B module is the carrier positional information that provides in real time of the inertial navigation system that utilizes on the carrier to be carried and combines gravity reference figure finally to obtain the reference to gravitational field data; The purpose of C module is to utilize matching algorithm finally to obtain the optimal location information of carrier; The purpose of D module is to utilize the Optimum Matching positional information to adopt information fusion technology to revise the inner systematic error of inertial navigation system in real time.
The present invention mainly is the initial alignment method to matching algorithm in the C module, to improve the reliability and the real-time of gravity aided inertial navigation system.
As shown in Figure 2, the present invention will realize according to following steps:
The first step judges that carrier has got into gravity field adaptive area Ψ, chooses three continuous sampled points of gravity field sensor that carrier carries, and three pairing times of sampled point are respectively t
1, t
2And t
3Constantly.
Can use when the big site error in order to ensure matching algorithm; And the characteristics of the triangle restriction model of the present invention's structure; When judging that carrier has got into gravity field adaptive area Ψ; After choosing the geophysical field observed reading of three continuous sampled points of geophysics field sensor that carrier carries, write down three sampled point time corresponding and be respectively t
1, t
2And t
3Constantly.
Second goes on foot, and confirms the region of search Ω of carrier gravity match reference figure; Error profile characteristic function according to inertial navigation system that carrier carries; Confirm the distance error threshold value δ of current time inertia system; With the carrier current location information that inertial navigation system was provided is the center, and distance error threshold value δ is a radius, delimits the region of search Ω of gravity match reference figure.
Inertial technology is very ripe at present; So at first according to the error profile characteristic function and the error model of inertial navigation system; Confirm the error of position information threshold value δ that the current time inertial navigation system provides; The carrier current location that provides with inertial navigation system then is the center, and the error threshold δ of inertial navigation system is a radius, delimits the region of search Ω of gravity match reference figure; Thereby reducing to guarantee that carrier actual position information falls within the region of search Ω of gravity match reference figure under the region of search raising search speed precondition.
The 3rd step made up high precision triangle geometry restricted model, and the triangular space Γ of definite triangle geometry model.
Utilize the inertial navigation system high characteristics of measuring accuracy in short-term, obtain inertial navigation system at adjacent moment t
1t
2Between and t
2t
3Between record the range information L that carrier goes
1, L
2, and carrier is at t
2Relative steering angle θ constantly makes up high-precision triangular form geometrical constraint model.
As shown in Figure 3, the localization method of inertial navigation system is to adopt the dead reckoning principle, can know that according to the dead reckoning principle inertial navigation system has high-precision measured value in short-term, thus as shown in Figure 4, utilize adjacent t
1The time be carved into t
2The distance L of inertial navigation output in this time period constantly
1, t
2The time be carved into t
3The distance L of inertial navigation output in this time period constantly
2, and at t
2Inertial navigation system records the relative steering angle θ structure geometrical constraint model ABC of carrier constantly; Then, choose arbitrary triangle, suppose that the leg-of-mutton length of side is respectively a, b and c, and a＞b＞c; Represent this triangle with two parameter b/a and c/a; Thereby by (x; Y) triangle that constitutes of three points in the space converts that (b/a c/a) representes with a point in the space, and is as shown in Figure 5 to; This space is triangle space Γ, and obtains the subpoint Q of high precision triangle geometry restricted model on triangle space Γ of structure
0
In the 4th step, utilize gravity field sensor that carrier carries at t
1, t
2And t
3The gravity value of constantly being taked is obtained carrier at t
1, t
2And t
3The moment corresponding reference to gravitational field isoline C
1, C
2And C
3The point set P that is comprised
1, P
2And P
3Its process is following:
As shown in Figure 6, isoline C
1Point set P in the Ω zone
1 (i is a natural number, 0＜i＜L
1, L
1Expression point set P
1What comprise counts) be positioned at interval [P
10, P
1n] in; Isoline C
2Point set P in the Ω zone
2 
(i is a natural number, 0＜i＜L
2, L
2Expression point set P
2What comprise counts) be positioned at interval [P
20, P
2n] in; And isoline C
3Point set P in the Ω zone
3 
(i is a natural number, 0＜i＜L
3, L
3Expression point set P
3What comprise counts) be positioned at interval [P
30, P
3n] in.
In the 5th step,, obtain the initial matching collection of carrier at current time based on triangle geometry restricted model isoline matching algorithm
(j is a natural number, and 1＜j＜N, N are a pairing set
The coupling logarithm that is comprised, p
j, q
j, m
jRepresent that respectively j initial matching is at isoline C
1, isoline C
2, isoline C
3Last pairing point).Its process is following:
At first from point set P
1, P
2And P
3In get respectively that a bit to form triangle coupling right
Calculate coupling then respectively to each the limit length of side a of corresponding triangle of institute
i, b
iAnd c
i(i is a natural number, corresponding i of expression mate to); Obtain i coupling at last to the subpoint Q on triangle space Γ
iTraversal point set P
1, P
2And P
3Middle having a few obtained all triangles couplings to the projection point set Q (Q on triangle space Γ
1, Q
2..., Q
k..., Q
M) (k is a natural number, and 1＜k＜M, M count for what point set Q comprised), calculate subpoint Q
iWith subpoint Q
0Between distance
Choose
The pairing coupling of all subpoints to forming the initial matching collection
(j is a natural number, and 1＜j＜N, N are a pairing set
The coupling logarithm that is comprised, p
j, q
j, m
jRepresent that respectively j initial matching is at isoline C
1, isoline C
2, isoline C
3Last pairing point).。
The 6th step, adopt probability-weighted estimation model algorithm, the value function is these characteristics of quadratic function of the angular error factor and the distance error factor, and calculates initial matching and concentrate the cost value of respectively organizing data, finally obtains accurate initial matching value.
The cost function that makes up is:
cost＝f(l，α)＝M
1l
2+M
2α
2 (1)
L representes the distance parameter between the correspondence position point that match point and inertial navigation system provide in the formula, and α representes the angle between the deflection of the corresponding point that deflection and inertial navigation system provided of match point, M
1Represent the distance weighted factor, M
2Expression angle weighting factor.
From a pairing set
In optional one group of coupling right
It is right to calculate coupling respectively by formula (1)
Pairing three match point p
j, q
jAnd m
jCoupling cost value costp
j, costq
jAnd costm
j, it is right to mate
The coupling cost value
Choose
Middle pairing one group of minimum value is paired into the final initial matching value of carrier.
The above only is a gravimetric map matching initial alignment methods in the gravity aided inertial navigation system, should be pointed out that in the building process of geometrical constraint model to have proposed t
1, t
2And t
3Be three adjacent moment constantly, if carrier is done strict rectilinear motion in certain time period, the user can be according to actual needs and is combined the cumulative errors characteristic of inertial navigation system, desirable t
1, t
iAnd t
I+n(i, n are natural number, i>=2) must guarantee that wherein carrier is at t
1To t
iInterior and t of the moment
iTo t
I+nIn do strict rectilinear motion, these uses also should be regarded as protection scope of the present invention.
The content of not doing in the instructions of the present invention to describe in detail belongs to this area professional and technical personnel's known prior art.
Claims (4)
1. the initial matching method that gravimetric map matees in the gravity aided inertial navigation system is characterized in that step is following:
The first step judges that carrier has got into gravity field adaptive area Ψ, chooses three continuous sampled points of gravity field sensor that carrier carries, and three pairing times of sampled point are respectively t
1, t
2And t
3Constantly;
Second goes on foot, and confirms the region of search Ω of carrier gravity match reference figure
At first according to the error profile characteristic function of inertial navigation system that carrier carries; Confirm the distance error threshold value δ of current time inertia system; Be the center with the carrier current location information that inertial navigation system was provided then, distance error threshold value δ is a radius, delimits the region of search Ω of gravity match reference figure; Thereby reducing to guarantee that carrier actual position information falls within the region of search Ω of gravity match reference figure under the region of search raising search speed precondition;
The 3rd step made up the triangle geometry restricted model, and made up triangular space Γ;
In the 4th step, utilize gravity field sensor that carrier carries at t
1, t
2And t
3The gravity value of constantly being taked is obtained carrier at t
1, t
2And t
3The moment corresponding reference to gravitational field isoline C
1, C
2And C
3The point set P that is comprised
1, P
2And P
3
In the 5th step, based on triangle geometry restricted model isoline matching algorithm, it is right in all initial matching of current time to obtain carrier
These initial matching are the initial matching collection to the sets definition of forming
J is a natural number, and 1＜j＜N, N are a pairing set
The coupling logarithm that is comprised, p
j, q
j, m
jRepresent that respectively j initial matching is at isoline C
1, isoline C
2, isoline C
3Last pairing point;
The 6th step, adopt probability-weighted estimation model algorithm, the value function is the quadratic function of the angular error factor and the distance error factor, calculates initial matching and concentrates the cost value of respectively organizing data, finally obtains accurate initial matching value.
2. the initial matching method of gravimetric map coupling in the gravity aided inertial navigation according to claim 1 system; It is characterized in that: said the 3rd step makes up the triangle geometry restricted model, and its process of structure triangular space Γ is: at first obtain inertial navigation system at adjacent moment t
1t
2Between and t
2t
3Between record the range information L that carrier goes
1, L
2, and carrier is at t
2Relative steering angle θ constantly makes up high-precision triangular form geometrical constraint model; Then, choose arbitrary triangle, suppose that the leg-of-mutton length of side is respectively a, b and c, and a＞b＞c; Represent this triangle with two parameter b/a and c/a, thereby by (x, y) triangle that constitutes of three points in the space converts that (b/a c/a) representes that with a point this space is triangle space Γ in the space to.
3. the initial matching method of gravimetric map coupling in the gravity aided inertial navigation according to claim 1 system; It is characterized in that: said the 5th step is obtained the initial matching collection of all possible positions of carrier based on triangle geometry restricted model isoline matching algorithm
Process be: at first from point set P
1, P
2And P
3In get respectively that a bit to form triangle coupling right
Calculate coupling then respectively to each the limit length of side a of corresponding triangle of institute
i, b
iAnd c
i, i is a natural number, i coupling of expression correspondence is right; At last i coupling to projecting to triangle space, and judge that this coupling is to subpoint and the distance lambda of triangle geometry restricted model between the subpoint of triangular space
iTraversal point set P
1, P
2And P
3Middle having a few chosen λ
iAll couplings of＜ξ are to forming the initial matching collection, the permissible error threshold value that ξ sets for the user.
4. the initial matching method of gravimetric map coupling in the gravity aided inertial navigation according to claim 1 system; It is characterized in that: said the 6th step is adopted probability-weighted estimation model algorithm; The value function is these characteristics of quadratic function of the angular error factor and the distance error factor; Calculate initial matching and concentrate the cost value of respectively organizing data, the detailed process that those group data that replace the value minimum are the final initial matching of carrier position is following:
A. the cost function that makes up is:
cost＝f(l，α)＝M
1l
2+M
2α
2 (1)
L representes the distance parameter between the correspondence position point that match point and inertial navigation system provide in the formula, and α representes the angle between the deflection of the corresponding point that deflection and inertial navigation system provided of match point, M
1Represent the distance weighted factor, M
2Expression angle weighting factor;
B. from a pairing set
In optional one group of coupling right
It is right to calculate coupling respectively by formula (1)
Pairing three match point p
j, q
jAnd m
iCoupling cost value costp
j, costq
jAnd costm
j, it is right to mate
The coupling cost value
Choose
Middle pairing one group of minimum value is paired into the final initial matching value of carrier.
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| CN102706348B (en) * | 2012-05-16 | 2015-05-20 | 北京航空航天大学 | Gravimetric map fast matching method based on triangle |
| CN102809376B (en) * | 2012-08-06 | 2015-02-25 | 哈尔滨工程大学 | Isoline-based assistant navigation positioning method |
| CN105021182B (en) * | 2015-06-03 | 2018-04-24 | 北京理工大学 | A kind of system of selection in Method in Gravity Aided INS adaptation area |
| CN105157703A (en) * | 2015-06-03 | 2015-12-16 | 北京理工大学 | Evaluation method of navigability of gravity-assisted inertial navigation adaptation zone |
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| CN109141426B (en) * | 2018-08-10 | 2020-11-10 | 中国空间技术研究院 | Method for matching navigation adaptation area by underwater gravity |
| CN109059964B (en) * | 2018-09-19 | 2021-07-23 | 中国船舶重工集团公司第七0七研究所 | Inertial navigation and gravity measurement double-calibration method based on gravity peak |
| CN110081884B (en) * | 2019-05-21 | 2021-02-12 | 北京理工大学 | Virtual course based gravity-assisted inertial navigation area suitability evaluation method |
| CN110031001B (en) * | 2019-05-21 | 2020-12-11 | 北京理工大学 | Adaptive area selection method for gravity-assisted inertial navigation |
| CN111397599A (en) * | 2020-02-25 | 2020-07-10 | 河海大学 | Improved ICCP (Integrated Circuit chip) underwater geomagnetic matching method based on triangular matching algorithm |
| CN113503871B (en) * | 2021-05-19 | 2024-04-16 | 北京理工大学 | Gravity matching method based on correlation filtering |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US5339684A (en) * | 1991-12-10 | 1994-08-23 | Textron Inc. | Gravity aided inertial navigation system |
| CN101424534A (en) * | 2008-12-09 | 2009-05-06 | 东南大学 | Inertia/gravity combined navigation semi-physical object simulating device |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US7142983B2 (en) * | 2003-07-03 | 2006-11-28 | Northrop Grumman Corporation | Method for the processing of non-continuous atom interferometer intertial instrument measurements and continuous wide bandwidth instrument measurements with a gravity database |
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Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US5339684A (en) * | 1991-12-10 | 1994-08-23 | Textron Inc. | Gravity aided inertial navigation system |
| CN101424534A (en) * | 2008-12-09 | 2009-05-06 | 东南大学 | Inertia/gravity combined navigation semi-physical object simulating device |
Non-Patent Citations (3)
| Title |
|---|
| 夏冰等.基于SPSS的重力匹配区域选择算法.《中国惯性技术学报》.2010,第18卷(第1期),第81-84页. * |
| 夏冰等.重力辅助导航联邦滤波算法仿真研究.《计算机仿真》.2010,第27卷(第11期),第1-4,13页. * |
| 孙岚.重力辅助惯性导航的匹配算法初探.《海洋测绘》.2006,第26卷(第1期),第44-46页. * |
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