Ground-air heterogeneous inertial navigation cooperative positioning method and system in satellite denial environment
By performing plane right-angle arrangement and data link ranging on three high-precision main inertial navigation systems on the ground in a satellite denial environment, combining Newton's iteration and least squares method, using the Kalman filtering algorithm, aerial carrier positioning in the satellite denial environment is solved. The problem of low accuracy enables high-precision navigation and reduces costs.
Patent Information
- Application Number
- CN202411342536.1
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-09-25
- Publication Date
- 2024-12-27
AI Technical Summary
In satellite denial environment, low-precision inertial navigation systems cannot maintain attitude accuracy for a long time, resulting in the carrier control system being instable and out of control. The cost of the prior art is higher when improving navigation accuracy by increasing sensor data fusion.
The coordinated positioning method of ground-space isomorphic inertial guide is adopted. By a plane right-angle triangle arrangement of three high-precision main inertial guide systems on the ground, the data link technology is used to accurately measure the distance, and a nonlinear positioning model is constructed and the Newtonian iteration method is used to minimize. The two-multiple method is linearized and the positioning results of the air carrier are obtained by combining the Kalman filtering algorithm.
It realizes high-precision positioning of aerial carriers in satellite denial environments, reduces integrated flight costs, improves navigation accuracy and ensures the convergence of positioning results.
Smart Images
Figure CN119197532A_ABST
Abstract
Description
Technical Field
[0001] The present invention belongs to the technical field of inertial navigation systems, and in particular relates to a ground-to-air heterogeneous inertial navigation collaborative positioning method and system in a satellite denial environment. Background Art
[0002] Among traditional positioning methods, the inertial navigation system has the advantages of good autonomy, all-weather, and the ability to provide the required position, speed, attitude and full navigation information, but its error will continue to increase over time, and the accuracy of small inertial navigation is relatively low. The satellite navigation system has the advantages of miniaturization and high precision, but due to its weak signal, it is easily interfered by the external electromagnetic environment or blocked by buildings, plants, etc., and has poor autonomy and reliability, forming a satellite denial environment.
[0003] The basic premise for the ground-air cluster to complete the task collaboratively is that each carrier can obtain high-precision positioning information during the collaborative process. Currently, it is mainly through satellite navigation positioning, which uses the receiver's pseudo-range observation data and broadcast ephemeris files to calculate the station coordinates. It is the most commonly used positioning method in navigation and positioning, and is mainly used for the initial approximate position positioning in navigation and positioning. In the case of global navigation satellite system signal denial, the low-precision inertial navigation system cannot maintain attitude accuracy for a long time due to the poor performance of inertial devices, which will cause the carrier control system to become unstable and out of control. At present, the literature research mainly improves the navigation and positioning accuracy by adding sensors for data fusion, but the fusion of multiple sensors for each air carrier leads to high costs. The more air carriers that are integrated for flight, the greater the cost. Summary of the invention
[0004] The technical problem solved by the present invention is: to overcome the shortcomings of the prior art, to provide a ground-to-air heterogeneous inertial navigation collaborative positioning method and system in a satellite denial environment, to achieve the positioning accuracy of a low-precision inertial navigation carrier in the air to the level of high-precision inertial navigation on the ground, to solve the problem of aerial collaborative positioning in a satellite denial environment, and to realize a ground-to-air heterogeneous inertial navigation collaborative positioning method.
[0005] The object of the present invention is achieved through the following technical solutions: a ground-to-air heterogeneous inertial navigation collaborative positioning method in a satellite denial environment, comprising: under the condition of satellite system signal denial, three high-precision main inertial navigation systems on the ground are arranged in a plane right-angle triangle; the three high-precision main inertial navigation systems on the ground are aligned and navigated to obtain the navigation position results of the three high-precision main inertial navigation systems on the ground, and the navigation position results of the three high-precision main inertial navigation systems on the ground and the preset air target points are converted into the navigation position results of the three high-precision main inertial navigation systems on the ground and the air target points in a geocentric earth-fixed coordinate system; according to the three high-precision main inertial navigation systems on the ground in the geocentric earth-fixed coordinate system, the navigation position results of the three high-precision main inertial navigation systems on the ground and the air target points are converted into the navigation position results of the three high-precision main inertial navigation systems on the ground and the air target points. The navigation position results of the navigation system and the position of the aerial target are obtained by obtaining the ranging of the three high-precision main inertial navigation systems on the ground and the aerial target; a nonlinear positioning model is obtained based on the ranging of the three high-precision main inertial navigation systems on the ground and the aerial target, and the estimated values of the roots of the nonlinear positioning model are linearized by the Newton iteration method, and then the aerial positioning calculation results are obtained based on the least squares method; a Kalman state transfer matrix and a measurement matrix are established, and the aerial positioning calculation results are used as Kalman filter measurement values, and the final aerial positioning results are obtained through Kalman filtering; the final aerial positioning results are converted into geographic coordinates of the earth coordinate system as the final positioning and navigation results.
[0006] In the above-mentioned ground-to-air heterogeneous inertial navigation collaborative positioning method in a satellite denial environment, one high-precision main inertial navigation system is taken as the origin, and the other two high-precision main inertial navigation systems are arranged in due south, due north, due east and due west respectively.
[0007] In the above-mentioned ground-to-air heterogeneous inertial navigation collaborative positioning method in a satellite denial environment, when stationary or in relative motion, the distance between the three high-precision main inertial navigation systems is greater than 1 kilometer.
[0008] In the above-mentioned ground-to-air heterogeneous inertial navigation collaborative positioning method in satellite denial environment, the nonlinear positioning model is obtained by the following formula:
[0009]
[0010] Wherein, x is the distance of the aerial target point in the x direction of the earth-centered earth-fixed rectangular coordinate, POS1(1) is the distance of the first high-precision main inertial navigation system in the x direction of the earth-centered earth-fixed rectangular coordinate, v1 is the standard deviation of the direction error, y is the distance of the aerial target point in the y direction of the earth-centered earth-fixed rectangular coordinate, POS1(2) is the distance of the first high-precision main inertial navigation system in the y direction of the earth-centered earth-fixed rectangular coordinate, z is the distance of the aerial target point in the z direction of the earth-centered earth-fixed rectangular coordinate, POS1(3) is the distance of the first high-precision main inertial navigation system in the z direction of the earth-centered earth-fixed rectangular coordinate, D1 is the distance value between the first high-precision main inertial navigation system and the aerial target point, v2 is the standard deviation of the distance measurement error, POS2(1) is the distance of the second high-precision main inertial navigation system POS2(3) is the distance between the second high-precision main inertial navigation system and the aerial target point. POS3(1) is the distance between the third high-precision main inertial navigation system and the aerial target point. POS3(2) is the distance between the third high-precision main inertial navigation system and the aerial target point. POS3(3) is the distance between the third high-precision main inertial navigation system and the aerial target point. D3 is the distance between the third high-precision main inertial navigation system and the aerial target point.
[0011] In the above-mentioned ground-to-air heterogeneous inertial navigation collaborative positioning method in satellite denial environment, the Kalman state transfer matrix and measurement matrix are obtained by the following formula:
[0012] X(k) = [Px, Py, Vx, Vy];
[0013]
[0014] Among them, X(k) is the state vector of the air target point, k is the count of the current state, Px is the longitude position of the air target point, Py is the latitude position of the air target point, Vx is the eastward speed of the air target point, Vy is the northward speed of the air target point, F(k) is the state transfer matrix, dT is the time increment, and H is the measurement matrix
[0015] A ground-to-air heterogeneous inertial navigation collaborative positioning system in a satellite denial environment comprises: a first module, used for arranging three high-precision main inertial navigation systems on the ground in a plane right-angle triangle under the condition of satellite system signal denial; a second module, used for aligning and navigating the three high-precision main inertial navigation systems on the ground to obtain navigation position results of the three high-precision main inertial navigation systems on the ground, and converting the navigation position results of the three high-precision main inertial navigation systems on the ground and preset air target points into navigation position results of the three high-precision main inertial navigation systems on the ground and air target points in an earth-centered earth-fixed coordinate system; a third module, used for aligning and navigating the three high-precision main inertial navigation systems on the ground in an earth-centered earth-fixed coordinate system according to the navigation position results of the three high-precision main inertial navigation systems on the ground in the earth-centered earth-fixed coordinate system. The fourth module is used to obtain a nonlinear positioning model based on the distance measurement between the three high-precision main inertial navigation systems on the ground and the aerial targets, linearize the estimated values of the roots of the nonlinear positioning model through the Newton iteration method, and then obtain the aerial positioning calculation results based on the least squares method; the fifth module is used to establish the Kalman state transfer matrix and the measurement matrix, use the aerial positioning calculation results as the Kalman filter measurement values, and obtain the final aerial positioning results through Kalman filtering; the sixth module is used to convert the final aerial positioning results into geographic coordinates of the earth coordinate system as the final positioning and navigation results.
[0016] In the above-mentioned ground-to-air heterogeneous inertial navigation collaborative positioning system in the satellite denial environment, one high-precision main inertial navigation system is taken as the origin, and the other two high-precision main inertial navigation systems are arranged in due south, due north, due east and due west respectively.
[0017] In the above-mentioned ground-to-air heterogeneous inertial navigation collaborative positioning system in the satellite denial environment, when stationary or in relative motion, the distance between the three high-precision main inertial navigation systems is greater than 1 kilometer.
[0018] In the above-mentioned ground-to-air heterogeneous inertial navigation collaborative positioning system in the satellite denial environment, the nonlinear positioning model is obtained by the following formula:
[0019]
[0020] Wherein, x is the distance of the aerial target point in the x direction of the earth-centered earth-fixed rectangular coordinate, POS1(1) is the distance of the first high-precision main inertial navigation system in the x direction of the earth-centered earth-fixed rectangular coordinate, v1 is the standard deviation of the direction error, y is the distance of the aerial target point in the y direction of the earth-centered earth-fixed rectangular coordinate, POS1(2) is the distance of the first high-precision main inertial navigation system in the y direction of the earth-centered earth-fixed rectangular coordinate, z is the distance of the aerial target point in the z direction of the earth-centered earth-fixed rectangular coordinate, POS1(3) is the distance of the first high-precision main inertial navigation system in the z direction of the earth-centered earth-fixed rectangular coordinate, D1 is the distance value between the first high-precision main inertial navigation system and the aerial target point, v2 is the standard deviation of the distance measurement error, POS2(1) is the distance of the second high-precision main inertial navigation system POS2(3) is the distance between the second high-precision main inertial navigation system and the aerial target point. POS3(1) is the distance between the third high-precision main inertial navigation system and the aerial target point. POS3(2) is the distance between the third high-precision main inertial navigation system and the aerial target point. POS3(3) is the distance between the third high-precision main inertial navigation system and the aerial target point. D3 is the distance between the third high-precision main inertial navigation system and the aerial target point.
[0021] In the above-mentioned ground-to-air heterogeneous inertial navigation collaborative positioning system in satellite denial environment, the Kalman state transfer matrix and measurement matrix are obtained by the following formula:
[0022] X(k) = [Px, Py, Vx, Vy];
[0023]
[0024] Among them, X(k) is the state vector of the aerial target point, k is the count of the current state, Px is the longitude position of the aerial target point, Py is the latitude position of the aerial target point, Vx is the eastward speed of the aerial target point, Vy is the northward speed of the aerial target point, F(k) is the state transfer matrix, dT is the time increment, and H is the measurement matrix.
[0025] Compared with the prior art, the present invention has the following beneficial effects:
[0026] (1) The present invention takes into account the signal denial conditions of the satellite system, based on the precise ranging of the data link, improves the positioning accuracy of the air carrier through high-low matching, and reduces the integrated flight cost, thereby realizing a ground-to-air heterogeneous inertial navigation collaborative positioning method in a satellite denial environment;
[0027] (2) The present invention arranges three high-precision main inertial navigation systems on the ground in a plane right triangle (with one main inertial navigation system as the origin, and the other two main inertial navigation systems are arranged in due south, due north, due east and due west, respectively). When the three main inertial navigation systems are stationary or in relative motion, the distance between them is greater than 1 km, ensuring the convergence of the solution of the earth-centered earth-fixed coordinates.
[0028] (3) The present invention uses the navigation results of three main inertial navigation systems on the ground as input information, combines the data link ranging results to build a positioning model, and uses a combination of the least squares method and the Kalman filter method for precise positioning to obtain the positioning results of the aerial carrier in a dynamic environment. BRIEF DESCRIPTION OF THE DRAWINGS
[0029] Various other advantages and benefits will become apparent to those of ordinary skill in the art by reading the detailed description of the preferred embodiments below. The accompanying drawings are only for the purpose of illustrating the preferred embodiments and are not to be considered as limiting the present invention. Moreover, the same reference symbols are used throughout the accompanying drawings to represent the same components. In the accompanying drawings:
[0030] Figure 1 Schematic diagram of ground-to-air heterogeneous inertial navigation collaborative positioning in a satellite denial environment provided by an embodiment of the present invention;
[0031] Figure 2 It is a flow chart of a method for ground-to-air heterogeneous inertial navigation collaborative positioning in a satellite denial environment provided by an embodiment of the present invention;
[0032] Figure 3 is a schematic diagram of a calculation simulation provided by an embodiment of the present invention;
[0033] Figure 4 It is a schematic diagram of dynamic positioning accuracy error analysis provided by an embodiment of the present invention. DETAILED DESCRIPTION
[0034] Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although exemplary embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments set forth herein. On the contrary, these embodiments are provided in order to enable a more thorough understanding of the present disclosure and to be able to fully convey the scope of the present disclosure to those skilled in the art. It should be noted that, in the absence of conflict, the embodiments of the present invention and the features described in the embodiments can be combined with each other. The present invention will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.
[0035] Taking into account the signal denial of the global satellite system and in order to solve the serious problem of error divergence of the inertial navigation system of the air carrier itself and reduce the integrated flight cost, data link technology is used on the ground to accurately measure the distance between air carriers, and based on the high-precision navigation results on the ground, high-to-low is used to achieve collaborative positioning and navigation in the air through high-low matching.
[0036] The data link technology is specifically that the system uses a time division and code division multiple access method (TDMA+CDMA) to realize the S-band data link networking system. The realization of ranging relies on wireless communication between data processing boards and network time synchronization between machines. When each node is precisely synchronized in the networking completion time, as long as the node receiving the signal measures the time when the signal arrives, it can measure the distance from the node transmitting the signal, thereby completing the distance calculation while communicating.
[0037] Figure 1 Schematic diagram of ground-to-air heterogeneous inertial navigation collaborative positioning in a satellite denial environment provided by an embodiment of the present invention; Figure 2 1 is a flow chart of a method for ground-to-air heterogeneous inertial navigation collaborative positioning in a satellite denial environment provided by an embodiment of the present invention. Figure 1 and Figure 2 As shown, the ground-to-air heterogeneous inertial navigation collaborative positioning method in the satellite denial environment includes:
[0038] Under the condition of satellite system signal denial, three high-precision main inertial navigation systems on the ground are arranged in a plane right-angle triangle;
[0039] Performing alignment navigation on the three high-precision main inertial navigation systems on the ground to obtain the navigation position results of the three high-precision main inertial navigation systems on the ground, and converting the navigation position results of the three high-precision main inertial navigation systems on the ground and the preset air target points into the navigation position results of the three high-precision main inertial navigation systems on the ground and the air target points in the earth-centered earth-fixed coordinate system;
[0040] According to the navigation position results of the three high-precision main inertial navigation systems on the ground and the position of the aerial target in the earth-centered earth-fixed coordinate system, the distance between the three high-precision main inertial navigation systems on the ground and the aerial target is obtained;
[0041] A nonlinear positioning model is obtained based on the distance measurement between the three high-precision main inertial navigation systems on the ground and the aerial targets. The estimated values of the roots of the nonlinear positioning model are linearized by the Newton iteration method, and then the aerial positioning calculation results are obtained based on the least squares method.
[0042] Establish the Kalman state transfer matrix and measurement matrix, use the aerial positioning calculation results as Kalman filter measurement values, and obtain the final aerial positioning results through Kalman filtering;
[0043] The final aerial positioning result is converted into geographic coordinates of the earth coordinate system as the final positioning and navigation result.
[0044] With one high-precision main inertial navigation system as the origin, the other two high-precision main inertial navigation systems are arranged in due south, due north, due east and due west. In the case of static or relative motion, the distance between the three high-precision main inertial navigation systems is greater than 1 km.
[0045] (1) Under the condition of satellite system signal denial, three high-precision main inertial navigation systems on the ground are arranged in a plane right-angle triangle (with one main inertial navigation system as the origin, and the other two main inertial navigation systems are arranged in due south, due north, due east and due west respectively). When the three main inertial navigation systems are stationary or in relative motion, the distance between them is greater than 1 km;
[0046] (2) Alignment and navigation of three high-precision main inertial navigation systems on the ground are carried out. The navigation position results of the three main inertial navigation systems on the ground are used as reference information. The geographic coordinates of the navigation results in the land coordinate system (LLA) are converted into Cartesian coordinates in the Earth-centered Earth-fixed coordinate system (ECEF) through transformation.
[0047] (3) The three main inertial navigation systems on the ground and the low-precision inertial navigation system in the air are accurately measured through data link technology, and then a nonlinear positioning model is constructed. The estimated values of the roots of the positioning model are linearized through the Newton iteration method, and then the air positioning calculation results are obtained based on the least squares method.
[0048] (4) Based on the motion environment, the Kalman state equation and measurement equation with position and velocity as state quantities are established, and the accuracy of dynamic environment positioning solution is improved through filtering estimation, and finally the positioning result in the air is obtained;
[0049] (5) The positioning result of the aerial vehicle in the Earth-centered Earth-fixed coordinate system (ECEF) is converted back to the geographic coordinates of the Land-Locked Coordinate System (LLA) as the final positioning and navigation result output.
[0050] Specifically, the implementation steps are as follows:
[0051] 1. Under the condition of satellite system signal denial, three high-precision main inertial navigation systems on the ground are arranged in a plane right-angle triangle (with one main inertial navigation system as the origin, and the other two main inertial navigation systems are arranged in due south, due north, due east and due west respectively), and the distance between the three main inertial navigation systems is greater than 1 km.
[0052] 2. The initial position coordinates of the three high-precision main inertial navigation systems after alignment are set to POS1 = [116, 40, 100]; POS2 = [116.01, 40, 120]; POS1 = [116, 40.01,
[0053] 110], and set the true value of the aerial target point to POS4 = [116.02, 39.98, 1000].
[0054] 3. Transform the coordinates of the initial points on the ground and in the air into the Earth-centered Earth-fixed coordinate system. The true values D1, D2, and D3 of the three ground nodes and the aerial distance measurement can be obtained through the three-dimensional point distance calculation formula.
[0055] 4. In order to investigate the accuracy of the collaborative positioning algorithm under dynamic conditions, considering the measurement error distribution of the main inertial navigation and data link in real situations, the ground main inertial navigation is moving eastward and northward (northeastward) at a speed of 20m / s. The simulated movement time is 1200s (20 minutes). After 1200s, the horizontal error of the main inertial navigation diverges to 40 meters, and the error of the data link ranging is within 5 meters.
[0056] 5. Construct an aerial target positioning model, where v1 is the standard deviation of the main inertial navigation system, which is 40 meters, and v2 is the standard deviation of the data link ranging system, which is 5 meters.
[0057]
[0058] Wherein, x is the distance of the aerial target point in the x direction of the earth-centered earth-fixed rectangular coordinate, POS1(1) is the distance of the first high-precision main inertial navigation system in the x direction of the earth-centered earth-fixed rectangular coordinate, v1 is the standard deviation of the direction error, y is the distance of the aerial target point in the y direction of the earth-centered earth-fixed rectangular coordinate, POS1(2) is the distance of the first high-precision main inertial navigation system in the y direction of the earth-centered earth-fixed rectangular coordinate, z is the distance of the aerial target point in the z direction of the earth-centered earth-fixed rectangular coordinate, POS1(3) is the distance of the first high-precision main inertial navigation system in the z direction of the earth-centered earth-fixed rectangular coordinate, D1 is the distance value between the first high-precision main inertial navigation system and the aerial target point, v2 is the standard deviation of the distance measurement error, POS2(1) is the distance of the second high-precision main inertial navigation system POS2(3) is the distance between the second high-precision main inertial navigation system and the aerial target point. POS3(1) is the distance between the third high-precision main inertial navigation system and the aerial target point. POS3(2) is the distance between the third high-precision main inertial navigation system and the aerial target point. POS3(3) is the distance between the third high-precision main inertial navigation system and the aerial target point. D3 is the distance between the third high-precision main inertial navigation system and the aerial target point.
[0059] 6. Linearize the above nonlinear model and obtain the Jacobian matrix Solve the tolerance error Δx=(J based on the least squares method T J) -1 J TF, sets the minimum tolerance error, and the positioning result in the air can be obtained by iterative calculation using the Newton iteration method. F is the difference between the calculated Euclidean distance between the three high-precision main inertial navigation nodes and the aerial target point and the actual distance measurement value.
[0060] 7. Take the positioning result as the Kalman filter measurement value, and let X(k) be the state matrix composed of position and velocity: X(k) = [Px, Py, Vx, Vy], and the state transfer matrix is The measurement matrix is
[0061] Among them, X(k) is the state vector of the aerial target point, k is the count of the current state, Px is the longitude position of the aerial target point, Py is the latitude position of the aerial target point, Vx is the eastward speed of the aerial target point, Vy is the northward speed of the aerial target point, F(k) is the state transfer matrix, dT is the time increment, and H is the measurement matrix.
[0062] The Kalman filter can be used to obtain the positioning result in the air. Figure 3 shown.
[0063] 8. The above motion conditions were simulated 1000 times. To intuitively describe the positioning error in the horizontal direction, a 50% probability circular error (CEP) calculation analysis was performed on the simulation results. Figure 4 shown.
[0064] It can be obtained that in the aerial collaborative positioning result data after 1200 seconds of dynamic simulation considering the main inertial navigation and data link errors, the 50% probability of circular error is 45.44m, which is close to the accuracy level of 40m of the main inertial navigation, realizing the ground-to-air heterogeneous inertial navigation collaborative positioning method.
[0065] The present embodiment also provides a ground-to-air heterogeneous inertial navigation collaborative positioning system in a satellite denial environment, the system comprising: a first module, used to arrange three high-precision main inertial navigation systems on the ground in a plane right-angle triangle under the condition of satellite system signal denial; a second module, used to align and navigate the three high-precision main inertial navigation systems on the ground to obtain the navigation position results of the three high-precision main inertial navigation systems on the ground, and convert the navigation position results of the three high-precision main inertial navigation systems on the ground and the preset air target points into the navigation position results and air target points of the three high-precision main inertial navigation systems on the ground in a geocentric earth-fixed coordinate system; a third module, used to perform alignment and navigation on the three high-precision main inertial navigation systems on the ground in the geocentric earth-fixed coordinate system. The navigation position results and the aerial target points are used to obtain the distance between the three high-precision main inertial navigation systems on the ground and the aerial targets; the fourth module is used to obtain a nonlinear positioning model based on the distance between the three high-precision main inertial navigation systems on the ground and the aerial targets, and the estimated values of the roots of the nonlinear positioning model are linearized by the Newton iteration method, and then the aerial positioning calculation results are obtained based on the least squares method; the fifth module is used to establish the Kalman state transfer matrix and the measurement matrix, and the aerial positioning calculation results are used as Kalman filter measurement values, and the final aerial positioning results are obtained through Kalman filtering; the sixth module is used to convert the final aerial positioning results into geographic coordinates of the earth coordinate system as the final positioning and navigation results.
[0066] This embodiment takes into account the signal denial conditions of the satellite system, based on the data link precise ranging, improves the positioning accuracy of the air carrier through high-low matching, and reduces the integrated flight cost, so as to realize the ground-air heterogeneous inertial navigation collaborative positioning method in the satellite denial environment; this embodiment arranges three high-precision main inertial navigation systems on the ground in a plane right-angle triangle (with one main inertial navigation system as the origin, and the other two main inertial navigation systems are arranged in due south, due north, due east and due west respectively). In the case of stillness or relative motion, the distance between the three main inertial navigation systems is greater than 1 kilometer to ensure the convergence of the geocentric and earth-fixed coordinate solution; this embodiment uses the navigation results of the three main inertial navigation systems on the ground as input information, constructs a positioning model in combination with the data link ranging results, and uses the combination of the least squares method and the Kalman filter method for precise positioning to obtain the positioning result of the air carrier in a dynamic environment.
[0067] Although the present invention has been disclosed as above in the form of a preferred embodiment, it is not intended to limit the present invention. Any person skilled in the art may make possible changes and modifications to the technical solution of the present invention by using the methods and technical contents disclosed above without departing from the spirit and scope of the present invention. Therefore, any simple modifications, equivalent changes and modifications made to the above embodiments based on the technical essence of the present invention without departing from the content of the technical solution of the present invention shall fall within the protection scope of the technical solution of the present invention.
Claims
1. A method for collaborative positioning of ground-to-air heterogeneous inertial navigation systems in a satellite denial environment, characterized in that include: Arrange the three high-precision main inertial navigation systems on the ground in a plane right-angle triangle; Performing alignment navigation on the three high-precision main inertial navigation systems on the ground to obtain the navigation position results of the three high-precision main inertial navigation systems on the ground, and converting the navigation position results of the three high-precision main inertial navigation systems on the ground and the preset air target points into the navigation position results of the three high-precision main inertial navigation systems on the ground and the air target points in the earth-centered earth-fixed coordinate system; According to the navigation position results of the three high-precision main inertial navigation systems on the ground and the position of the aerial target in the earth-centered earth-fixed coordinate system, the distance between the three high-precision main inertial navigation systems on the ground and the aerial target is obtained; A nonlinear positioning model is obtained based on the distance measurement between the three high-precision main inertial navigation systems on the ground and the aerial targets. The estimated values of the roots of the nonlinear positioning model are linearized by the Newton iteration method, and then the aerial positioning calculation results are obtained based on the least squares method. Establish the Kalman state transfer matrix and measurement matrix, use the aerial positioning calculation results as Kalman filter measurement values, and obtain the final aerial positioning results through Kalman filtering; The final aerial positioning result is converted into geographic coordinates of the earth coordinate system as the final positioning and navigation result.
2. The method for ground-to-air heterogeneous inertial navigation collaborative positioning in a satellite denial environment according to claim 1, characterized in that: With one high-precision main inertial navigation system as the origin, the other two high-precision main inertial navigation systems are arranged due south, due north, due east and due west respectively.
3. The method for ground-to-air heterogeneous inertial navigation collaborative positioning in a satellite denial environment according to claim 1, characterized in that: When stationary or in relative motion, the three high-precision main inertial navigation systems are more than 1 kilometer apart.
4. The method for ground-to-air heterogeneous inertial navigation collaborative positioning in a satellite denial environment according to claim 1, characterized in that: The nonlinear positioning model is obtained by the following formula: Wherein, x is the distance of the aerial target point in the x direction of the earth-centered earth-fixed rectangular coordinate, POS1(1) is the distance of the first high-precision main inertial navigation system in the x direction of the earth-centered earth-fixed rectangular coordinate, v1 is the standard deviation of the direction error, y is the distance of the aerial target point in the y direction of the earth-centered earth-fixed rectangular coordinate, POS1(2) is the distance of the first high-precision main inertial navigation system in the y direction of the earth-centered earth-fixed rectangular coordinate, z is the distance of the aerial target point in the z direction of the earth-centered earth-fixed rectangular coordinate, POS1(3) is the distance of the first high-precision main inertial navigation system in the z direction of the earth-centered earth-fixed rectangular coordinate, D1 is the distance value between the first high-precision main inertial navigation system and the aerial target point, v2 is the standard deviation of the distance measurement error, POS2(1) is the distance of the second high-precision main inertial navigation system POS2(3) is the distance between the second high-precision main inertial navigation system and the aerial target point. POS3(1) is the distance between the third high-precision main inertial navigation system and the aerial target point. POS3(2) is the distance between the third high-precision main inertial navigation system and the aerial target point. POS3(3) is the distance between the third high-precision main inertial navigation system and the aerial target point. D3 is the distance between the third high-precision main inertial navigation system and the aerial target point.
5. The method for ground-to-air heterogeneous inertial navigation collaborative positioning in a satellite denial environment according to claim 1, characterized in that: The Kalman state transfer matrix and measurement matrix are obtained by the following formula: Among them, k is the count of the current state, F(k) is the state transfer matrix, dT is the time increment, and H is the measurement matrix.
6. A ground-to-air heterogeneous inertial navigation collaborative positioning system in a satellite denial environment, characterized by include: The first module is to arrange the three high-precision main inertial navigation systems on the ground in a plane right-angle triangle; The second module is used to perform alignment navigation on the three high-precision main inertial navigation systems on the ground to obtain the navigation position results of the three high-precision main inertial navigation systems on the ground, and convert the navigation position results of the three high-precision main inertial navigation systems on the ground and the preset air target points into the navigation position results of the three high-precision main inertial navigation systems on the ground and the air target points in the earth-centered earth-fixed coordinate system; The third module is used to obtain the distance between the three high-precision main inertial navigation systems on the ground and the aerial target based on the navigation position results of the three high-precision main inertial navigation systems on the ground in the earth-centered earth-fixed coordinate system and the aerial target point position; The fourth module is used to obtain a nonlinear positioning model based on the distance measurement between the three high-precision main inertial navigation systems on the ground and the aerial targets, linearize the estimated values of the roots of the nonlinear positioning model through the Newton iteration method, and then obtain the aerial positioning calculation results based on the least squares method; The fifth module is used to establish the Kalman state transfer matrix and the measurement matrix, use the aerial positioning calculation result as the Kalman filter measurement value, and obtain the final aerial positioning result through Kalman filtering; The sixth module is used to convert the final aerial positioning result into the geographic coordinates of the earth coordinate system as the final positioning and navigation result.
7. The ground-to-air heterogeneous inertial navigation collaborative positioning system in a satellite denial environment according to claim 6, characterized in that: With one high-precision main inertial navigation system as the origin, the other two high-precision main inertial navigation systems are arranged due south, due north, due east and due west respectively.
8. The ground-to-air heterogeneous inertial navigation collaborative positioning system in a satellite denial environment according to claim 6, characterized in that: When stationary or in relative motion, the three high-precision main inertial navigation systems are more than 1 kilometer apart.
9. The ground-to-air heterogeneous inertial navigation collaborative positioning system in a satellite denial environment according to claim 6, characterized in that: The nonlinear positioning model is obtained by the following formula: Wherein, x is the distance of the aerial target point in the x direction of the earth-centered earth-fixed rectangular coordinate, POS1(1) is the distance of the first high-precision main inertial navigation system in the x direction of the earth-centered earth-fixed rectangular coordinate, v1 is the standard deviation of the direction error, y is the distance of the aerial target point in the y direction of the earth-centered earth-fixed rectangular coordinate, POS1(2) is the distance of the first high-precision main inertial navigation system in the y direction of the earth-centered earth-fixed rectangular coordinate, z is the distance of the aerial target point in the z direction of the earth-centered earth-fixed rectangular coordinate, POS1(3) is the distance of the first high-precision main inertial navigation system in the z direction of the earth-centered earth-fixed rectangular coordinate, D1 is the distance value between the first high-precision main inertial navigation system and the aerial target point, v2 is the standard deviation of the distance measurement error, POS2(1) is the distance of the second high-precision main inertial navigation system POS2(3) is the distance between the second high-precision main inertial navigation system and the aerial target point. POS3(1) is the distance between the third high-precision main inertial navigation system and the aerial target point. POS3(2) is the distance between the third high-precision main inertial navigation system and the aerial target point. POS3(3) is the distance between the third high-precision main inertial navigation system and the aerial target point. D3 is the distance between the third high-precision main inertial navigation system and the aerial target point.
10. The ground-to-air heterogeneous inertial navigation collaborative positioning system in a satellite denial environment according to claim 6, characterized in that: The Kalman state transfer matrix and measurement matrix are obtained by the following formula: Among them, k is the count of the current state, F(k) is the state transfer matrix, dT is the time increment, and H is the measurement matrix.