CN112902957A - Missile-borne platform navigation method and system - Google Patents

Missile-borne platform navigation method and system Download PDF

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CN112902957A
CN112902957A CN202110081249.XA CN202110081249A CN112902957A CN 112902957 A CN112902957 A CN 112902957A CN 202110081249 A CN202110081249 A CN 202110081249A CN 112902957 A CN112902957 A CN 112902957A
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landmark
current moment
opportunity
missile
map
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CN112902957B (en
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王炯琦
吕东辉
周萱影
陈彧赟
何章鸣
侯博文
魏居辉
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National University of Defense Technology
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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
    • G01C21/18—Stabilised platforms, e.g. by gyroscope

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Abstract

The invention provides a missile-borne platform navigation method and a missile-borne platform navigation system, which comprise the following steps: acquiring an output state value at the current moment through an inertial navigation device; inquiring the map landmark at the current moment, and calculating the output deviation estimation value based on the map landmark at the current moment according to the inquired map landmark at the current moment; inquiring the opportunity landmark at the current moment, and calculating an output deviation estimation value based on the opportunity landmark at the current moment according to the inquired opportunity landmark at the current moment; performing fusion calculation on the output deviation estimated value based on the map landmark and the output deviation estimated value based on the opportunity landmark to obtain an output deviation compensation item at the current moment; and substituting the output deviation compensation item into the output state value at the current moment for compensation to obtain the corrected posture and position of the missile-borne platform. By the technical scheme, the state estimation precision of the missile-borne platform during the navigation of the missile can be effectively improved.

Description

Missile-borne platform navigation method and system
Technical Field
The invention relates to the technical field of missile measurement and control, in particular to a missile-borne platform navigation method and a missile-borne platform navigation system.
Background
The missile is an important weapon, and the navigation system provides navigation information such as the position, the speed, the attitude and the like of a missile-borne platform relative to a certain reference coordinate system, and is one of core equipment for the operation of the missile.
As a most common Navigation method, a Global Navigation Satellite System (GNSS) can provide information such as a position, a velocity, and an attitude of a carrier in real time. However, GNSS signals are susceptible to interference or spoofing, difficult to penetrate solid matter, and are easily lost in the case of high maneuvering of the support. For this reason, missile-borne platform autonomous navigation methods for replacing or assisting GNSS have been developed, and the most important of them is the inertial navigation system, but they still have various problems, which restrict the inertial long-term navigation accuracy.
With the continuous improvement of the autonomous navigation performance of the missile-borne navigation system, the requirement of high precision, high reliability, all-time and all-autonomous navigation is often difficult to be simultaneously met by a single autonomous navigation mode. Based on the information fusion theory, different navigation modes are combined to form a combined navigation system, and the advantage complementation is realized, so that the precision and the reliability of the whole system are improved, and the combined navigation system becomes an important development direction for the research of the autonomous navigation technology. With the rapid development of image recognition, matching, processing and other technologies, landmark observation information becomes a new important information source in autonomous accurate navigation. Landmarks at exact geographic positions are obtained through landmark recognition and matching with a landmark database, and are called Map Landmarks (MLs), a navigation method based on a MLs auxiliary Inertial Navigation System (INS) establishes an observation equation of a motion carrier through the visual direction of a sensitive landmark and combining with possible inertial equipment output, and meanwhile obtains high-precision estimation of the attitude and the position of the carrier, and the method is widely applied.
In the process of implementing the invention, the inventor finds that at least the following problems exist in the prior art:
a navigation method based on the MLs auxiliary inertial system needs to store high-precision landmark information in advance, and the observability of landmarks puts high requirements on illumination, weather, map storage and the like. In regions where the missile does not have significant MLs through deserts, oceans and the like, and under the conditions of insufficient visible light and cloud shielding, MLs may not be successfully matched, and the number of observable MLs may be drastically reduced, thereby affecting the navigation accuracy based on MLs-assisted inertial system.
Disclosure of Invention
The embodiment of the invention provides a missile-borne platform navigation method, which is used for solving the problem that navigation accuracy is influenced because part of map signposts in an existing MLs-based auxiliary inertial system can not be identified.
To achieve the above object, in one aspect, an embodiment of the present invention provides a missile-borne platform navigation method, including:
acquiring an output state value at the current moment through an inertial navigation device, wherein the output state value comprises the attitude and the position of the missile-borne platform;
inquiring the map landmark at the current moment, and calculating the output deviation estimation value based on the map landmark at the current moment according to the inquired map landmark at the current moment;
inquiring the opportunity landmark at the current moment, and calculating an output deviation estimation value based on the opportunity landmark at the current moment according to the inquired opportunity landmark at the current moment; (ii) a
Performing fusion calculation on the output deviation estimated value based on the map landmark at the current moment and the output deviation estimated value based on the opportunity landmark at the current moment to obtain an output deviation compensation item at the current moment;
and substituting the output deviation compensation item into the output state value at the current moment to perform compensation, so as to obtain the corrected posture and position of the missile-borne platform.
In another aspect, an embodiment of the present invention provides a missile-borne platform navigation system, including:
the inertial navigation device is used for outputting an output state value at the current moment, and the output state value comprises the posture and the position of the missile-borne platform;
the output deviation estimation value determining unit is used for inquiring the map landmark at the current moment and calculating the output deviation estimation value based on the map landmark at the current moment according to the inquired map landmark at the current moment; inquiring the opportunity landmark at the current moment, and calculating an output deviation estimation value based on the opportunity landmark at the current moment according to the inquired opportunity landmark at the current moment;
the fusion calculation unit is used for performing fusion calculation on the output deviation estimation value based on the map landmark and the output deviation estimation value based on the opportunity landmark to obtain an output deviation compensation item at the current moment;
and the adjusting unit is used for substituting the output deviation compensation item into the output state value at the current moment to perform compensation, so as to obtain the corrected posture and position of the missile-borne platform.
The technical scheme has the following beneficial effects:
according to the technical scheme, the navigation method based on the landmark auxiliary inertia of the Opportunity Landmarks (OLs) is introduced into the autonomous navigation system, the missile-borne platform autonomous navigation method using the two landmark fusion auxiliary inertia systems is constructed in consideration of the advantages and the limitations of MLs and OLs in navigation, high-precision estimation of all states of the missile-borne platform including position, speed and attitude is achieved without adding extra sensors, and the navigation precision is effectively improved.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
FIG. 1 is a flow chart of a missile-borne platform navigation method according to an embodiment of the invention;
FIG. 2 is a schematic diagram of a missile-borne platform navigation system according to an embodiment of the present invention;
FIG. 3 is a flow chart of an embodiment of the present invention;
FIG. 4 is a schematic view of a landmark observation of a map in an embodiment of the invention;
FIG. 5 is a schematic illustration of opportunistic landmark observations in an embodiment of the invention;
FIG. 6 is a schematic diagram of simulated ballistic and landmark simulation in a simulation experiment of the present invention;
FIG. 7 is a schematic diagram of landmark observation events in a simulation experiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
As shown in fig. 1, an embodiment of the present invention provides a missile-borne platform navigation method, including:
s101, acquiring an output state value at the current moment through an inertial navigation device, wherein the output state value comprises the posture and the position of a missile-borne platform;
s102, inquiring a map landmark at the current moment, and calculating an output deviation estimation value based on the map landmark at the current moment according to the inquired map landmark at the current moment;
s103, inquiring the opportunity landmark at the current moment, and calculating an output deviation estimated value based on the opportunity landmark at the current moment according to the inquired opportunity landmark at the current moment;
s104, performing fusion calculation on the output deviation estimated value based on the map landmark at the current moment and the output deviation estimated value based on the opportunity landmark at the current moment to obtain an output deviation compensation item at the current moment;
and S105, substituting the output deviation compensation item into the output state value at the current moment to perform compensation, so as to obtain the corrected posture and position of the missile-borne platform.
Further, before the step S101, the method further includes:
s001, shooting a ground image at the current moment;
and S002, dividing map landmarks or opportunity landmarks at the current moment according to the shot ground images.
Further, the step S002 includes:
s0021, extracting image feature points from the shot ground image;
s0022, traversing each image feature point, and aiming at each image feature point:
s00221, judging whether the image feature points are matched with a preset map landmark library;
s00222, if the image feature points are matched, determining the image feature points as map landmarks;
s00223, if not, calling a ground image shot at the previous moment, and judging whether the image feature point exists in the ground image shot at the previous moment;
s00224, if the image feature points exist, determining the image feature points as opportunity landmarks.
Further, the calculating the output deviation estimation value of the current time based on the map landmark includes:
s1021, constructing a ballistic error propagation equation of the inertial navigation device;
s1022, constructing an implicit observation equation based on the map landmark;
and S1023, calculating the output deviation estimated value based on the map landmark according to the map landmark at the current moment, the ballistic error propagation equation and the implicit observation equation based on the map landmark, and determining a first estimation error covariance matrix according to the output deviation estimated value based on the map landmark.
Further, the calculating the output deviation estimation value of the current time based on the opportunity landmark includes:
s1031, restoring the position of the opportunistic landmark at the current moment according to the output state value of the missile-borne platform inertial navigation device at the previous moment;
s1032, constructing an implicit observation equation based on the opportunity landmark, wherein the implicit observation equation based on the opportunity landmark is created by adopting a sphere-based construction model;
s1033, calculating the output deviation estimation value based on the opportunity landmark according to the position of the opportunity landmark at the current moment, the ballistic error propagation equation and the implicit observation equation based on the opportunity landmark, and determining a second estimation error covariance matrix according to the output deviation estimation value based on the opportunity landmark.
As shown in fig. 2, an embodiment of the present invention provides a missile-borne platform navigation system, including:
21. the inertial navigation device is used for outputting an output state value at the current moment, and the output state value comprises the posture and the position of the missile-borne platform;
22. the output deviation estimation value determining unit is used for inquiring the map landmark at the current moment and calculating the output deviation estimation value based on the map landmark at the current moment according to the inquired map landmark at the current moment; inquiring the opportunity landmark at the current moment, and calculating an output deviation estimation value based on the opportunity landmark at the current moment according to the inquired opportunity landmark at the current moment;
23. the fusion calculation unit is used for performing fusion calculation on the output deviation estimation value based on the map landmark and the output deviation estimation value based on the opportunity landmark to obtain an output deviation compensation item at the current moment;
24. and the adjusting unit is used for substituting the output deviation compensation item into the output state value at the current moment for compensation to obtain the corrected posture and position of the missile-borne platform.
Further, the missile-borne platform navigation system further comprises:
11. the missile-borne platform camera is used for shooting a ground image at the current moment;
23. and the landmark determining unit is used for dividing map landmarks or opportunity landmarks at the current moment according to the shot ground images.
Further, the landmark determining unit 23 is specifically configured to:
extracting image feature points from the shot ground image; traversing each of the image feature points, for each of the image feature points: judging whether the image feature points are matched with a preset map landmark library or not; if so, determining the image feature points as map landmarks; otherwise, calling a ground image shot at the last moment, and judging whether the image feature point exists in the ground image shot at the last moment; and if so, determining the image feature points as opportunity landmarks.
Further, the output deviation estimation value determination unit 22 includes a first output deviation estimation value calculation module 221, configured to construct a ballistic error propagation equation of the inertial navigation device; constructing an implicit observation equation based on the landmark of the map; and calculating the output deviation estimation value based on the map landmark according to the map landmark at the current moment, the ballistic error propagation equation and the implicit observation equation based on the map landmark, and determining a first estimation error covariance matrix according to the output deviation estimation value based on the map landmark.
Further, the output deviation estimation value determination unit 22 includes a second output deviation estimation value calculation module 222, configured to recover the position of the opportunistic landmark at the current time according to the output state value of the missile-borne platform inertial navigation device at the previous time; constructing an implicit observation equation based on the opportunity landmark, wherein the implicit observation equation based on the opportunity landmark is created by adopting a sphere-based construction model; calculating the output deviation estimated value based on the opportunity landmark according to the position of the opportunity landmark at the current moment, the ballistic error propagation equation and the implicit observation equation based on the opportunity landmark, and determining a second estimation error covariance matrix according to the output deviation estimated value based on the opportunity landmark.
An embodiment is described below, and as shown in fig. 3, a detailed flowchart of the missile-borne platform navigation method is provided:
firstly, a system state model adopted by the navigation scheme is a ballistic error propagation equation, and state variables are INS output deviation, gyroscope constant value drift and accelerometer constant value bias. The establishment of the subsequent observation equation and the giving of the fusion estimation are both used for estimating the INS output deviation as accurately as possible so as to further obtain accurate estimation of the state of the missile-borne platform.
The navigation equipment used by the navigation method comprises an inertial navigation device, namely a gyroscope, an accelerometer and a missile-borne camera. The inertial device provides a reference measurement of the state of the missile-borne platform, and the missile-borne platform camera corrects the output deviation of the inertial device by extracting landmark information from the real-time shot image.
As shown in fig. 3, there are two kinds of landmarks which can be used for inertial navigation output deviation correction, one is a map landmark which can be successfully matched with the feature points of the image shot in real time to obtain the exact geographic position of the landmark, and the landmark can correct the output deviation of the inertial device to a greater extent and provide the information of the absolute state of the missile-borne platform. Another is an opportunistic landmark that can be successfully identified by capturing feature points in the image in real time, but whose geographic location is unknown, the successful use of such a landmark in navigation requires that it be continuously observed by the sequence of images. The opportunistic landmarks do not require the successful matching of feature points in real-time shot images and a map landmark library, have low requirements on observation environment conditions, can be used in unknown environments with few or even no map landmarks, expand the available range of the visual navigation technology, and have been applied to the precise autonomous landing field of spacecrafts. However, when the method is used for spacecraft landing, the optical axis of the camera needs to be assumed to be perpendicular to the landing horizontal plane, the assumed landmark is distributed approximately on a horizontal plane, and the method is not suitable for missile-borne navigation systems, especially for medium-distance missiles, the landmark is not distributed on an ideal horizontal plane, so that the method cannot be directly applied to the missile-borne platform navigation method and needs to be correspondingly processed to be applied. The present application therefore assumes that the earth is a standard sphere and makes the assumption that the opportunity landmark is located on the surface of the standard sphere. The hypothesis is more consistent with the real distribution situation of the landmarks identified in the missile flight process, and the application space based on the sequence image navigation method is also expanded.
Aiming at the advantages and disadvantages of the two landmarks, the method comprehensively utilizes the two landmark information to estimate and fuse the INS output deviation, and the basic principle of estimating the INS output deviation based on the two landmarks is as follows.
Firstly, the geographical position of the map landmark is known exactly, and the position and the posture of the missile-borne platform at the current moment are output by combining the INS and the installation matrix of the missile-borne camera, so that the two-dimensional imaging coordinate of the map landmark at the current moment is estimated. This coordinate estimate is biased from the true observation of the map landmark, which is obviously a function of the INS output bias and the current time map landmark coordinate observation error. Thus, an implicit observation equation about the output deviation of the INS at the current time, i.e., the system state variable, can be established. And combining KF (Kalman filter) to obtain the INS output deviation estimation based on the map landmark and a corresponding estimation error covariance matrix.
Because the geographical position of the opportunity landmark is unknown, the geographical coordinate of the opportunity landmark is recovered by the method and the device according to the temporary shot image at the previous moment, the observation coordinate of the opportunity landmark at the previous moment, the posture and the position of the INS to the missile-borne platform at the previous moment. However, according to the attitude and position output of the missile-borne platform by the INS at the previous moment and the observation of the opportunistic landmarks at the previous moment, only the direction vector from the missile-borne camera to the opportunistic landmarks can be obtained, and the distance from the missile-borne platform to the opportunistic landmarks and the geographic location of the opportunistic landmarks cannot be known. For this reason, the present application assumes that the earth is a standard sphere on which to construct the model. According to the known distance from the opportunity landmark to the geocenter, namely the radius of the earth, the vector from the missile-borne platform to the opportunity landmark can be obtained, and the geographic coordinates of the opportunity landmark can be further recovered. And then, according to a similar method established by a terrestrial landmark observation equation, virtual observation of the landmark of the map at the current moment can be established. The difference between the virtual observations and the real observations of the opportunistic landmarks is a function of the INS output bias and the coordinate observation error at the current and previous times. Because the system variables adopted by the method only relate to the INS output deviation at a single moment, and the observation equation is a function of the INS output deviations at two adjacent moments, the method adopts a random cloning method to clone the system variables so as to keep the INS output deviation at the last moment in the system variables at the current moment, and the corresponding estimation error covariance matrix and the state propagation equation need to be correspondingly adjusted. Therefore, INS output deviation estimation based on the opportunity landmark at the current moment and a corresponding estimation error covariance matrix can be obtained by combining the KF.
In order to obtain a fused INS output deviation estimate based on two landmarks, the present application applies the CI (covariance intersection) theory to the state fusion estimate. The method obtains a fusion estimate and a corresponding estimate error covariance matrix by convex combining different estimates and corresponding estimate error covariance matrices. Under the condition that the consistency of the original estimation is guaranteed, the fused estimation obtained by the method is consistent no matter how the different original estimations have correlation. Due to the simplicity and the superiority of the method to different estimation fusion performances, the method applies the CI theory to the fusion of INS deviation estimation based on two different landmarks to obtain higher-precision fusion INS output deviation estimation.
The coordinate system used in the missile-borne platform navigation in the application comprises a launching point inertia coordinate system (li system), a missile body coordinate system (b system) and a landmark sensor coordinate system (s system), and the b system and the s system are set to have the same origin.
The selection li is a navigation coordinate system, and the following full-text variables are expressed in the navigation coordinate system except for special indications. Selecting x (t) ═ Φ (t), δ v (t), δ r (t), ∈ (t), (t)]TIs a state vector of the system, where phi (t) is [ phi [ + ]x(t),φy(t),φz(t)]For mathematical platform misalignment angles, i.e. missile attitude estimation errors, δ V (t) ([ δ V)x(t),δVy(t),δVz(t)]And δ r (t) ([ δ x (t), δ y (t), δ z (t))]Respectively missile velocity and position estimation error, epsilon (t) [ epsilon ]x(t),εy(t),εz(t)]Represents gyroscope constant drift [. v [x(t),▽y(t),▽z(t)]For the accelerometer constant bias, the ballistic error propagation equation, i.e. the state equation of the missile-borne platform navigation system, is shown as the following formula
X(t)＝F(t)X(t)+G(t)W(t) (1)
F (t) and G (t) are respectively a process input matrix and a noise driving matrix, W (t) [. epsilon. ]s(t),▽s(t)]TIs a systematic noise vector, where εs(t)＝[εs,x(t),εs,y(t),εs,z(t)]And +s(t)＝[▽s,x(t),▽s,y(t),▽s,z(t)]The drift errors are output for the gyroscope and accelerometer, respectively.
The traditional system state transition equation can be obtained by discretizing the equation (1) as follows:
Xk+1＝ΦkXk+ΓkWk (2)
wherein the subscript k represents the time of day,
Xk＝[φk,δVk,δrk,εk,▽k]T (3)
when the discrete time step is T and,
Figure BDA0002909399380000081
Figure BDA0002909399380000082
wherein, I15Is an identity matrix of dimension 15. Assume generally that the system noise Wk＝[εs,k,▽s,k]TIs uncorrelated zero mean Gaussian noise with covariance matrix of Qk。
Before an implicit observation equation is established by utilizing two kinds of landmark information, the identification and matching of feature points in an image are needed to be carried out. Matching here refers to matching of the real-time image to the map landmark database for map landmarks and matching of feature points in the sequence images for opportunity landmarks. Therefore, the correct identification and matching of the image feature points are the premise for establishing the implicit observation equation of the application and are the prerequisite for the successful application of the visual navigation. In addition, limited missile-borne computer resources and high-speed movement of missiles require that image feature points can be identified and properly matched at high speeds. First, the image feature points that have been constructed and used are corners, scale-invariant feature transform (SIFT), speeded-up robust feature (SURF), and the like. An angular point is an intersection of two connected edges in an image, which can be detected by a correlation method. However, this method is computationally expensive, for which a Harris detector based on gradient calculations is constructed. However, the angular point characteristics are related to the scaling of the image, and the method has a limitation in the application of the missile-borne platform in the case of variable missile flight height. Unlike the corner points, the SIFT is resistant to rotation, scaling and scale change, is not disturbed by view angle change, affine transformation and noise to a certain extent, and is suitable for being applied to an autonomous navigation system of a missile-borne platform. SIFT has a high computational complexity, and for this reason SURF has been proposed, which detects image feature points by the same criteria as SIFT, but reduces the computational load of feature point identification and extraction. Furthermore, the increase in computational speed of computers and the advent of various efficient image processing algorithms have made real-time feature recognition and matching possible.
In general, only a small number of feature points of an image can be successfully matched with the landmarks of the map stored in the landmark database, and a large number of feature points which cannot be successfully matched can be continuously tracked. Therefore, in order to utilize the navigation information in the real-time images shot by the missile-borne camera as much as possible, the method establishes an implicit observation equation based on two landmarks, estimates the output deviation of the inertial navigation system as high as possible, and derives the implicit observation equation based on the two landmarks.
As shown in fig. 4, if the map landmark i, ρ is obtained by image recognition matchingiFor its known coordinates in the li system, the geometric relationship can then be derived
Figure BDA0002909399380000083
Wherein the content of the first and second substances,
Figure BDA0002909399380000084
for vectors from the missile to the landmark in the s-system, the subscript k represents time, the superscript M represents the landmark type as a map landmark, rkIs the missile position at time k.
Figure BDA0002909399380000085
Is a rotation matrix from s to b, the rotation matrix being a known constant matrix related to the missile-borne camera mounting,
Figure BDA0002909399380000091
for the rotation matrix of time k from b to li, as follows
Figure BDA0002909399380000092
Wherein the content of the first and second substances,
Figure BDA0002909399380000093
ψk,γkthe pitch, yaw and roll angles of the missile at the moment k are respectively. Formula divided by rhoiAnd
Figure BDA0002909399380000094
as is known, others are unknown variables.
Can obtain
Figure BDA0002909399380000095
Wherein the content of the first and second substances,
Figure BDA0002909399380000096
is a rotation matrix from li to b,
Figure BDA0002909399380000097
is a rotation matrix of the system from b to s, and has
Figure BDA0002909399380000098
Figure BDA0002909399380000099
Outputting the true values of the missile position and the attitude at the moment k according to the position of the inertial navigation system if the true values are unavailable
Figure BDA00029093993800000910
Attitude angle output
Figure BDA00029093993800000911
Can obtain
Figure BDA00029093993800000912
Is estimated by
Figure BDA00029093993800000913
Wherein the content of the first and second substances,
Figure BDA00029093993800000914
is and ζkThe corresponding rotation matrix from li to b.
Then
Figure BDA00029093993800000915
Estimation error
Figure BDA00029093993800000916
Wherein for vector ω ═ ωx,ωy,ωz]，h(ζkω) are each
Figure BDA00029093993800000917
Figure BDA00029093993800000918
Figure BDA00029093993800000919
Figure BDA00029093993800000920
Mathematical platform misalignment angle phi for gyro outputkResulting in an attitude error angle phikTo thetakThe conversion relation of (A) is as follows
Figure BDA0002909399380000101
δrk＝[δxk,δyk,δzk]An error is output for the position of the accelerometer.
According to
Figure BDA0002909399380000102
And its estimation error
Figure BDA0002909399380000103
An estimate of the imaging coordinates of the landmark can be derived
Figure BDA0002909399380000104
And its estimation error
Figure BDA0002909399380000105
As shown in formula (17) and formula (18), respectively:
Figure BDA0002909399380000106
Figure BDA0002909399380000107
wherein the content of the first and second substances,
Figure BDA0002909399380000108
Figure BDA0002909399380000109
is composed of
Figure BDA00029093993800001010
F is the camera focal length, I2Is a unit array with dimension of 2 x 2.
And the coordinate observation of the landmark at the moment k
Figure BDA00029093993800001011
Wherein the content of the first and second substances,
Figure BDA00029093993800001012
for two-dimensional coordinate errors of map landmark imaged points, it can be generally assumed
Figure BDA00029093993800001013
Are not correlated and obey a mean of 0 and a variance of
Figure BDA00029093993800001014
A gaussian distribution of (a).
Then a map landmark based implicit observation equation can be constructed according to the above equation as follows
Figure BDA00029093993800001015
Wherein the content of the first and second substances,
Figure BDA00029093993800001016
Figure BDA00029093993800001017
as shown in fig. 5, the process of constructing the observation equation for the opportunity landmark is as follows:
let the missile position vector expressed in li coordinate system at the moment k be rkThe position vector of the chance landmark j in the li system is obtained by camera identification and is rhojIn the s-system, the coordinate of the landmark is
Figure BDA0002909399380000111
Wherein the content of the first and second substances,
Figure BDA0002909399380000112
for the observation error of the opportunistic landmarks, it is generally assumed that they obey a mean of 0 and a variance of 0
Figure BDA0002909399380000113
A gaussian distribution of (a). Where the superscript O represents the landmark type as an opportunistic landmark, then the vector from the missile to the landmark in the s-system is represented as
Figure BDA0002909399380000114
Wherein the content of the first and second substances,
Figure BDA0002909399380000115
is the determined scaling factor. When the method is used in the field of autonomous landing of spacecraft, the opportunistic landmarks are required to be distributed on a roughly horizontal landing plane and are not suitable for a missile-borne navigation system, and the scaling coefficient is deduced on the basis of the assumption that the opportunistic landmarks are located on the surface of a standard sphere
Figure BDA0002909399380000116
From the geometric relationship
Figure BDA0002909399380000117
At time k +1, if landmark j is recognized again by the camera, then there is
Figure BDA0002909399380000118
Thus, can obtain
Figure BDA0002909399380000119
Further comprises
Figure BDA00029093993800001110
At the time k +1, the following equation holds
Figure BDA00029093993800001111
Then at time k +1, the theoretical observation of landmark j is
Figure BDA00029093993800001112
Through the derivation, it can be known that the observation of the opportunistic landmark j at the time k +1 can be obtained by predicting the position and the posture of the missile at the previous time and the position and the posture of the missile at the current time through the theoretical imaging coordinate of the opportunistic landmark at the previous time.
However, the variables on the right side in the formula are real unknown system variables, and for predicting the observation of the landmark j at the time k +1, the unknown variables can be estimated or replaced by the unknown variables, and at this time, an error is introduced into the coordinate prediction, and can be represented by the system variables in the formula, and further, an implicit observation equation based on the opportunity landmark can be constructed.
Then, by
Figure BDA0002909399380000121
Substitution
Figure BDA0002909399380000122
Wherein
Figure BDA0002909399380000123
Figure BDA0002909399380000124
Is estimated error of
Figure BDA0002909399380000125
Missile attitude at time k
Figure BDA0002909399380000126
Position rkAnd the attitude and the position of the missile at the moment of k +1 are unknown and output by an inertial navigation system
Figure BDA0002909399380000127
Figure BDA0002909399380000128
And
Figure BDA0002909399380000129
instead, a prediction of the missile-to-landmark vector expressed in the s-system at time k +1 can thus be obtained
Figure BDA00029093993800001210
Accordingly, the number of the first and second electrodes,
Figure BDA00029093993800001211
is estimated error of
Figure BDA00029093993800001212
Further obtain the
Figure BDA00029093993800001213
Wherein
Figure BDA00029093993800001214
Figure BDA00029093993800001215
Further, by
Figure BDA00029093993800001216
Derived landmark imaging point predictions
Figure BDA00029093993800001217
And its estimation error
Figure BDA00029093993800001218
As follows
Figure BDA00029093993800001219
Figure BDA00029093993800001220
Wherein the content of the first and second substances,
Figure BDA00029093993800001221
is composed of
Figure BDA00029093993800001222
The three components of (a) and (b),
Figure BDA00029093993800001223
then the coordinate observation of the landmark at the time of k +1
Figure BDA0002909399380000131
In combination with the foregoing formulas, the following implicit observation equation based on opportunistic landmarks can be constructed
Figure BDA0002909399380000132
Wherein the content of the first and second substances,
Figure BDA0002909399380000133
Figure BDA0002909399380000134
Figure BDA0002909399380000135
Figure BDA0002909399380000136
Figure BDA0002909399380000137
Figure BDA0002909399380000138
the first two columns of E.
Scaling factor in this application
Figure BDA0002909399380000139
The calculation method of (c) is as follows:
assuming that the earth is a standard sphere with emission points at the earth's surface, the vector pointing from the earth's center to the emission points in the li system is ρ0Then, from the geometric relationship, the vector from the geocenter to the landmark
Figure BDA00029093993800001310
The earth is assumed to be a standard sphere, there are
||ρj||＝||ρ0|| (75)
Where | · | | represents the 2 norm of the vector.
Namely, it is
Figure BDA00029093993800001311
In general, the location of the emission points is known by certainty, i.e., ρ0Is determined for the known missile position r at time kkAttitude matrix
Figure BDA00029093993800001312
And the exact imaging coordinates are known, then the equation can be translated to one for
Figure BDA00029093993800001313
A quadratic equation of one unit of
Figure BDA00029093993800001314
Then the formula can be written as
Figure BDA00029093993800001315
Is obviously about
Figure BDA00029093993800001316
The standard linear equation of (2) has definite analytic solution.
Note the book
a＝(ρ0+rk)Tdk (79)
Then
Figure BDA0002909399380000141
It is clear that,
Figure BDA0002909399380000142
as a smaller solution, i.e.
Figure BDA0002909399380000143
In this application
Figure BDA0002909399380000144
And its estimation error
Figure BDA0002909399380000145
g(ζkω), the calculation process of the expression of c is as follows:
in general, the location of the emission points is known by certainty, i.e., ρ0Is known by certainty. However, the exact rk、
Figure BDA0002909399380000146
And
Figure BDA0002909399380000147
cannot be obtained, here, using inertial navigation output
Figure BDA0002909399380000148
And
Figure BDA0002909399380000149
substitute for rkAnd
Figure BDA00029093993800001410
with coordinate observations of the opportunistic landmarks at the last time
Figure BDA00029093993800001411
Instead of the former
Figure BDA00029093993800001412
So according to
Figure BDA00029093993800001413
And
Figure BDA00029093993800001414
can be obtained about
Figure BDA00029093993800001415
Is estimated by
Figure BDA00029093993800001416
It is clear that,
Figure BDA00029093993800001417
Figure BDA00029093993800001418
and observation errors will propagate to
Figure BDA00029093993800001419
Next, the present application will derive this error propagation equation.
It is known that
Figure BDA00029093993800001420
Has an error of
Figure BDA00029093993800001421
dkIs estimated by
Figure BDA00029093993800001422
Then dkIs estimated error of
Figure BDA00029093993800001423
Wherein for vector ω ═ ωx,ωy,ωz]，g(ζkω) are each
Figure BDA00029093993800001424
Figure BDA00029093993800001425
Figure BDA0002909399380000151
g(ζkω) may follow the expression for h (ζ)kω), are derived, and are omitted here.
Estimation of a
Figure BDA0002909399380000152
Figure BDA0002909399380000153
Is estimated by
Figure BDA0002909399380000154
Note the book
Figure BDA0002909399380000155
Then
Figure BDA0002909399380000156
Is estimated error of
Figure BDA0002909399380000157
Wherein
Figure BDA0002909399380000158
The steps of calculating and fusing the estimation and algorithm of the output deviation estimation value are as follows:
STEP 1: state estimation based on MLs assisted inertial system: suppose that the system state at time k is estimated as
Figure BDA0002909399380000159
The corresponding estimation error covariance matrix is PkAssuming that n map landmarks are matched at time k +1, the INS output bias estimate obtained using only MLs at time k +1
Figure BDA00029093993800001510
And corresponding estimation error covariance matrix
Figure BDA00029093993800001511
Figure BDA00029093993800001512
Figure BDA00029093993800001513
Figure BDA00029093993800001514
Figure BDA00029093993800001515
Figure BDA0002909399380000161
Figure BDA0002909399380000162
Figure BDA0002909399380000163
Figure BDA0002909399380000164
As can be seen, the present application assumes that the observed noise between different map landmarks is uncorrelated. In addition to this, the present invention is,
Figure BDA0002909399380000165
it needs to be calculated one by one according to the formula.
STEP 2: state estimation based on OLs assisted inertial system: since the observation equation based on the opportunistic landmarks is a function of the inertial navigation output deviation at two consecutive moments, in order to estimate the INS output deviation, it is necessary to first estimate the INS output deviation
Figure BDA0002909399380000166
The random cloning is of the following formula,
Figure BDA0002909399380000167
wherein the content of the first and second substances,
Figure BDA0002909399380000168
the corresponding estimation error covariance matrix needs to be extended to
Figure BDA0002909399380000169
Assuming that m landmarks are tracked at the time k and the time k +1, the calculated INS output deviation estimate based on OLs at the time k +1
Figure BDA00029093993800001610
And corresponding estimation error covariance matrix
Figure BDA00029093993800001611
Figure BDA00029093993800001612
Figure BDA00029093993800001613
Figure BDA00029093993800001614
Figure BDA00029093993800001615
Figure BDA0002909399380000171
Figure BDA0002909399380000172
Figure BDA0002909399380000173
Figure BDA0002909399380000174
Figure BDA0002909399380000175
Figure BDA0002909399380000176
It should be noted that, in order to include the INS output deviation at the previous time in the system variables, the present application estimates the state at the previous time
Figure BDA0002909399380000177
Random cloning was performed and the corresponding estimation error covariance matrix was also adjusted. .
It can be seen that the present application assumes that the observation errors at different times and at different opportunities are independent of each other, and as such
Figure BDA0002909399380000178
And calculating one by one according to the corresponding formula.
STEP 3: state fusion estimation based on two landmark observations: STPE1 obtains an INS output bias estimate based on MLs at time k +1
Figure BDA0002909399380000179
And corresponding estimation error covariance matrix
Figure BDA00029093993800001710
STPE2 then yields OLs-based system state estimates
Figure BDA00029093993800001711
And corresponding estimation error covariance matrix
Figure BDA00029093993800001712
Then the application combines the CI theory to fuse two estimations, and gives out a fused estimation based on two landmarks at the k +1 moment
Figure BDA00029093993800001713
And corresponding estimation error covariance matrix Pk+1The calculation formula is as follows
Figure BDA00029093993800001714
Figure BDA00029093993800001715
One simple calculation method for λ is as follows:
Figure BDA00029093993800001716
STEP 4: and compensating the system state estimation at the k +1 moment into the INS output to obtain the missile state estimation, and returning to STEP1 for the missile state estimation at the next moment.
In order to verify the superiority of the proposed algorithm, simulation experiments were performed. Firstly, the application generates a cruise missile cruise section trajectory, the missile at the stage of cruising at a constant altitude of 20km and a cruise time of 300s, the cruise starting point latitude is 39.98 degrees, and the longitude is 116.34 degrees. The cruise terminal latitude is 30.68 ° and the longitude is 133.12 °. At time t, the latitude of the missile position is
Figure BDA0002909399380000181
Longitude is
Figure BDA0002909399380000182
Where t e [0,300]. In the cruise sectionIn the li system, the roll angle, the yaw angle and the yaw angle of the missile are constantly 0. Then the method randomly generates 1500 landmarks in the surface area of the earth skipped by the missile, wherein 500 map landmarks are randomly contained, and the landmark generation area is longitude epsilon [116.34 degrees ], 133.12 degrees]The latitude belongs to [ lat-0.2865 DEG, lat +0.2865 DEG ]]Wherein
Figure BDA0002909399380000183
Then, the parameters of the missile-borne camera, namely the landmark sensor are set as follows, and firstly, the rotation matrix from the coordinate system of the landmark sensor to the coordinate system of the missile body is
Figure BDA0002909399380000184
The camera field angle is 60 degrees, and camera focal length f equals 35mm, and the noise of two kinds of landmark observation coordinates is all obeyed the mean value and is 0 in two coordinate axis directions, and the standard deviation is 5 um's gaussian distribution, and the landmark observation noise mutually independent not equidirectional, different landmarks and different moments. It is noted that the image noise level given here is worse than it is practical.
FIG. 6 illustrates generated cruise trajectories, random landmarks, visible map landmarks, and visible opportunity landmarks.
Fig. 7 records the observation events of landmarks, the abscissa represents the time, the ordinate is the number of a randomly generated landmark, when the landmark with the number i is observed at the time t, the position (t, i) is marked with a real point, otherwise the corresponding position is unmarked.
During missile cruising, the visible map landmarks are relatively few, which may present challenges to the successful application of MLs-based navigation methods. The relatively high number of visible opportunity landmarks relative to MLs may be beneficial for missile state estimation with fewer visible map landmarks. In addition, the visible map landmarks are fewer, and the assumption of more chance landmarks is more consistent with the actual situation: in practice, both map landmarks and opportunity landmarks exist at each time, but the number of map landmarks is in most cases less than the number of opportunity landmarks.
Setting INS related parameters as that the gyro constant drift in three directions is 1 degree/h, the accelerometer constant offset is 100ug, wherein the earth gravity acceleration g is 9.78m2·s-2The standard deviation of the output noise of the gyroscope is 0.5 degree/h, and the standard deviation of the output noise of the accelerometer is 50 ug. The gyroscope output frequency was 100 HZ. At the initial position, the attitude output deviation of the gyroscope in 3 directions is 5 ", the position output deviation is 50m, and the speed estimation deviations in 3 directions are all 0.1m · s-1
In order to compare the performance of the proposed method with the astronomical-inertial integrated navigation system, the present application made comparative simulation experiments with the conventional CINS (astronomical-inertial integrated navigation system) and the deep integrated CINS. In CINS, the attitude estimation precision of the star sensor is 3%, and the sensitivity precision of the altimeter in the deep combination CINS is 50m, which is the general precision level which can be achieved by the current star sensor and the altitude sensor. In addition, the filtering period of the CINS and the filtering period based on the landmark navigation method are both set to be 0.1 s. It is noted that the filter period settings herein are relatively conservative, as current developments with respect to image processing algorithms indicate that GPU and FPGA based feature extraction and matching can be run at speeds above 30 HZ.
Based on the above parameter settings, the present application performed 100 independent monte carlo simulation tests, and from the final result, even though the number of visible map landmarks is small, the method based on MLs can still obtain satisfactory estimation of the position and speed of the missile-borne platform. However, the MLs-based approach performs far less than CINS in attitude estimation. In addition, the navigation method based on the two landmarks successfully integrates the advantages of the two different landmark methods, overcomes the respective defects, and obtains high-precision estimation on all states of the missile-borne platform, including position, speed and attitude.
Table 1 counts the state estimation Root Mean Square Error (RMSE) of different navigation methods, and the data in the table are the average results of 100 simulation experiments. From table 1, on all state estimations of the missile-borne platform, including the position, the speed and the attitude of the missile-borne platform, the navigation method based on two landmarks is superior to the traditional CINS, the deeply-combined CINS and the navigation method using only one landmark. Compared with the CINS, the navigation method based on two landmarks greatly improves the position estimation precision under the condition of not increasing additional sensors, and compared with the deep combination CINS, the navigation method uses fewer sensors to obtain more accurate missile-borne platform state estimation (the deep combination CINS adopts three sensors, namely INS, star sensor and altimeter). In the speed and position estimation of the missile-borne platform, the navigation method based on the two road signs is superior to the method only using the map road signs; in the platform attitude estimation, the estimation precision of two landmarks is obviously better than that of a navigation method only using a single landmark.
The method based on the two landmarks integrates the advantages of the method of using the two landmarks singly, and realizes the state estimation with higher precision.
Figure BDA0002909399380000191
TABLE 1 State estimation RMSE for different navigation methods
The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present invention. To those skilled in the art; various modifications to these embodiments will be readily apparent, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the disclosure. Thus, the present disclosure is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
The above-mentioned embodiments are intended to illustrate the objects, technical solutions and advantages of the present invention in further detail, and it should be understood that the above-mentioned embodiments are merely exemplary embodiments of the present invention, and are not intended to limit the scope of the present invention, and any modifications, equivalent substitutions, improvements and the like made within the spirit and principle of the present invention should be included in the scope of the present invention.

Claims (10)

1. A missile-borne platform navigation method is characterized by comprising the following steps:
acquiring an output state value at the current moment through an inertial navigation device, wherein the output state value comprises the attitude and the position of the missile-borne platform;
inquiring the map landmark at the current moment, and calculating the output deviation estimation value based on the map landmark at the current moment according to the inquired map landmark at the current moment;
inquiring the opportunity landmark at the current moment, and calculating an output deviation estimation value based on the opportunity landmark at the current moment according to the inquired opportunity landmark at the current moment;
performing fusion calculation on the output deviation estimated value based on the map landmark at the current moment and the output deviation estimated value based on the opportunity landmark at the current moment to obtain an output deviation compensation item at the current moment;
and substituting the output deviation compensation item into the output state value at the current moment to perform compensation, so as to obtain the corrected posture and position of the missile-borne platform.
2. The missile-borne platform navigation method of claim 1, wherein before the obtaining of the output state value at the current time by the inertial navigation device, further comprising:
shooting a ground image at the current moment;
and dividing the map landmark and the opportunity landmark at the current moment according to the shot ground image.
3. The missile-borne platform autonomous navigation method of claim 2, wherein the dividing of the map landmark and the opportunity landmark at the current moment according to the captured ground image comprises:
extracting a predetermined number of image feature points from the shot ground image;
traversing each of the image feature points, for each of the image feature points:
judging whether the image feature points are matched with a preset map landmark library or not;
if so, determining the image feature points as map landmarks;
otherwise, calling a ground image shot at the last moment, and judging whether the image feature point exists in the ground image shot at the last moment;
and if so, determining the image feature points as opportunity landmarks.
4. The missile-borne platform navigation method of claim 1, wherein the calculating the output deviation estimate for the current time based on map landmarks comprises:
constructing a ballistic error propagation equation of the inertial navigation device;
constructing an implicit observation equation based on the landmark of the map;
and calculating an output deviation estimation value of the current time based on the map landmark according to the map landmark of the current time, the ballistic error propagation equation and the implicit observation equation based on the map landmark, and determining a first estimation error covariance matrix according to the output deviation estimation value of the current time based on the map landmark.
5. The missile-borne platform navigation method of claim 4, wherein the calculating an output deviation estimate for the current time based on the opportunity landmarks comprises:
recovering the position of the opportunistic landmark at the current moment according to the output state value of the missile-borne platform inertial navigation device at the last moment;
constructing an implicit observation equation based on the opportunity landmark, wherein the implicit observation equation based on the opportunity landmark is created by adopting a sphere-based construction model;
and calculating an output deviation estimation value based on the opportunity landmark at the current moment according to the position of the opportunity landmark at the current moment, the ballistic error propagation equation and the implicit observation equation based on the opportunity landmark, and determining a second estimation error covariance matrix according to the output deviation estimation value based on the opportunity landmark at the current moment.
6. A missile-borne platform navigation system, comprising:
the inertial navigation device is used for outputting an output state value at the current moment, and the output state value comprises the posture and the position of the missile-borne platform;
the output deviation estimation value determining unit is used for inquiring the map landmark at the current moment and calculating the output deviation estimation value based on the map landmark at the current moment according to the inquired map landmark at the current moment; inquiring the opportunity landmark at the current moment, and calculating an output deviation estimation value based on the opportunity landmark at the current moment according to the inquired opportunity landmark at the current moment;
the fusion calculation unit is used for performing fusion calculation on the output deviation estimation value based on the map landmark at the current moment and the output deviation estimation value based on the opportunity landmark at the current moment to obtain an output deviation compensation item at the current moment;
and the adjusting unit is used for substituting the output deviation compensation item into the output state value at the current moment to perform compensation, so as to obtain the corrected posture and position of the missile-borne platform.
7. The missile-borne platform navigation system of claim 6, further comprising:
the missile-borne platform camera is used for shooting a ground image at the current moment;
and the landmark determining unit is used for dividing map landmarks or opportunity landmarks at the current moment according to the shot ground images.
8. The missile-borne platform navigation system of claim 7, wherein the landmark determination unit is specifically configured to:
extracting image feature points from the shot ground image; traversing each of the image feature points, for each of the image feature points: judging whether the image feature points are matched with a preset map landmark library or not; if so, determining the image feature points as map landmarks; otherwise, calling a ground image shot at the last moment, and judging whether the image feature point exists in the ground image shot at the last moment; and if so, determining the image feature points as opportunity landmarks.
9. The missile-borne platform navigation system of claim 6, wherein the output deviation estimate determination unit comprises a first output deviation estimate calculation module configured to construct a ballistic error propagation equation for the inertial navigation device; constructing an implicit observation equation based on the landmark of the map; and calculating an output deviation estimation value of the current time based on the map landmark according to the map landmark of the current time, the ballistic error propagation equation and the implicit observation equation based on the map landmark, and determining a first estimation error covariance matrix according to the output deviation estimation value of the current time based on the map landmark.
10. The missile-borne platform navigation system of claim 9, wherein the output deviation estimate determination unit comprises a second output deviation estimate calculation module for recovering the position of the opportunistic landmark at the current time according to the output state value of the missile-borne platform inertial navigation device at the last time; constructing an implicit observation equation based on the opportunity landmark, wherein the implicit observation equation based on the opportunity landmark is created by adopting a sphere-based construction model; and calculating an output deviation estimation value based on the opportunity landmark at the current moment according to the position of the opportunity landmark at the current moment, the ballistic error propagation equation and the implicit observation equation based on the opportunity landmark, and determining a second estimation error covariance matrix according to the output deviation estimation value based on the opportunity landmark at the current moment.
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