CN-122015828-A - Navigation positioning method based on multi-source data fusion

CN122015828ACN 122015828 ACN122015828 ACN 122015828ACN-122015828-A

Abstract

The invention belongs to the technical field of navigation, and discloses a navigation positioning method based on multi-source data fusion, which comprises the following steps: and calculating an error equation of the inertial navigation system, wherein the system state equation is the error equation of the inertial navigation system and mainly comprises an attitude, a speed, a position and an inertial device error equation. The inertia/tacon state equation is calculated. Calculating a filtering state fusion estimation, taking an inertial navigation system as a reference system, forming a sub-filter by the rest satellite navigation systems and the inertial navigation system, carrying out state estimation by Kalman filtering, and then sending a filtering result to a main filter for information fusion. Through the steps, the influence of a single navigation system on the airborne navigation system is effectively reduced, and the reliability of the navigation system in a complex electromagnetic environment is improved.

Inventors

PANG CHUNLEI
CHEN QIUSHI
ZHANG LIANG
ZHANG YANG
WANG MENG
GAO JINGLONG
CHEN JINYU

Assignees

中国人民解放军空军工程大学

Dates

Publication Date: 20260512
Application Date: 20260212

Claims (4)

1. A navigation positioning method based on multi-source data fusion is characterized by comprising the following steps: Acquiring measurement data of an inertial device and an auxiliary navigation system, wherein the auxiliary navigation system comprises one or more of a satellite navigation system and a Takang system; Inputting measurement data of an inertial device into an inertial navigation system, and calculating initial inertial navigation calculation data, wherein the initial inertial navigation calculation data comprises a gesture, a speed and a position; The inertial navigation system is used as a reference system, the auxiliary navigation system and the inertial navigation system form a sub-filter, and state estimation is carried out through Kalman filtering, wherein a state equation of the sub-filter is an error equation of the inertial navigation system, and the error equation of the inertial navigation system comprises an attitude error equation, a speed error equation, a position error equation and an inertial device error equation; Inputting the filtering results of all the sub-filters into a main filter for fusion, and outputting global state estimation; And feeding the global state estimation back to the inertial navigation system to correct the initial inertial navigation calculation data, and outputting final inertial navigation calculation data.
2. The navigation positioning method based on multi-source data fusion according to claim 1, wherein the error equation of the inertial navigation system is specifically: In the formula, As an error equation for an inertial navigation system, As a 15-dimensional state variable, 、、 And 、、 Random constant zero offset of the gyroscope and the accelerometer respectively, Respectively latitude, longitude and altitude errors, The speed errors of the carrier in the east direction, the north direction and the sky direction are respectively, The misalignment angles of the east, north and sky to the platform are respectively, In the form of a system state transition matrix, Is a matrix of 9-dimensional error parameters, Is a subarray of a state transition matrix associated with a gesture, All-zero-valued fill sub-arrays for the system state transition matrix, In order to be a system noise transfer matrix, As a system noise vector, Representing the coordinate system of the carrier System) relative to navigation inertial system Is tied) to the gesture matrix of the device, 、、 And 、、 The gyro angular velocity white noise and the accelerometer specific force white noise are respectively, Is that Row of lines A matrix of all 0's of the columns, Indicating the current time of day and, Representing the transpose of the matrix.
3. The method for positioning navigation based on multi-source data fusion according to claim 1, wherein the performing state estimation by kalman filtering specifically comprises: taking an inertial navigation system as a reference system, and forming a sub-filter by the auxiliary navigation system and the inertial navigation system; Each sub-filter respectively carries out time updating and measurement updating of Kalman filtering to obtain local state estimation; And inputting the filtering result of each sub-filter into the main filter, carrying out information fusion according to the information distribution criterion, outputting global state estimation, and feeding back the global state estimation to each sub-filter for resetting the filtering initial value at the next moment.
4. The method of claim 1, wherein the combination of the inertial navigation system and the assisted navigation system comprises an inertial navigation system/tacon system, an inertial navigation system/satellite navigation system/tacon system, and an inertial navigation system/GNSS.

Description

Navigation positioning method based on multi-source data fusion Technical Field The invention belongs to the technical field of navigation, and particularly relates to a navigation positioning method based on multi-source data fusion. Background The multisource fusion navigation is usually based on inertial navigation and is a technology of fusing other navigation systems, so that the limitation of a single navigation system can be overcome, and a navigation solution with higher precision, higher reliability and stronger anti-interference capability is provided. In particular to carriers such as an airplane, an inertial navigation system can be completely autonomous, and the position, the speed, the gesture and the course can be calculated independently through integral operation by measuring the acceleration and the angular speed of the carrier, and the external signals are not relied on, so that the anti-interference performance is strong, but the navigation errors can be accumulated and diverged along with time, the longer the flight time is, the worse the position precision is, so that the pure inertial navigation cannot independently complete the navigation tasks of long dead time and high precision. It is usually necessary to correct the satellite navigation in combination with means such as satellite navigation, however, satellite navigation cannot provide effective positioning information in an interference environment, so that in increasingly complex flight environments, a combined satellite and inertial system cannot ensure that an aircraft can obtain accurate space-time information in any situation. In summary, the existing multi-source fusion navigation technology has a plurality of defects, and in order to solve the above problems, a scheme capable of reducing the influence of a single navigation system on an airborne navigation system and improving the reliability of the navigation system is needed. Disclosure of Invention In order to achieve the above object, the present invention provides a navigation positioning method based on multi-source data fusion, comprising: Acquiring measurement data of an inertial device and an auxiliary navigation system, wherein the auxiliary navigation system comprises one or more of a satellite navigation system and a Takang system; Inputting measurement data of an inertial device into an inertial navigation system, and calculating initial inertial navigation calculation data, wherein the initial inertial navigation calculation data comprises a gesture, a speed and a position; The inertial navigation system is used as a reference system, the auxiliary navigation system and the inertial navigation system form a sub-filter, and state estimation is carried out through Kalman filtering, wherein a state equation of the sub-filter is an error equation of the inertial navigation system, and the error equation of the inertial navigation system comprises an attitude error equation, a speed error equation, a position error equation and an inertial device error equation; Inputting the filtering results of all the sub-filters into a main filter for fusion, and outputting global state estimation; And feeding the global state estimation back to the inertial navigation system to correct the initial inertial navigation calculation data, and outputting final inertial navigation calculation data. Optionally, the error equation of the inertial navigation system is specifically: In the formula, As an error equation for an inertial navigation system,As a 15-dimensional state variable,、、And、、Random constant zero offset of the gyroscope and the accelerometer respectively,Respectively latitude, longitude and altitude errors,The speed errors of the carrier in the east direction, the north direction and the sky direction are respectively,The misalignment angles of the east, north and sky to the platform are respectively,In the form of a system state transition matrix,Is a matrix of 9-dimensional error parameters,Is a subarray of a state transition matrix associated with a gesture,All-zero-valued fill sub-arrays for the system state transition matrix,In order to be a system noise transfer matrix,As a system noise vector,Representing the coordinate system of the carrierSystem) relative to navigation inertial systemIs tied) to the gesture matrix of the device,、、And、、The gyro angular velocity white noise and the accelerometer specific force white noise are respectively,Is thatRow of linesA matrix of all 0's of the columns,Indicating the current time of day and,Representing the transpose of the matrix. Optionally, the performing state estimation through kalman filtering specifically includes: taking an inertial navigation system as a reference system, and forming a sub-filter by the auxiliary navigation system and the inertial navigation system; Each sub-filter respectively carries out time updating and measurement updating of Kalman filtering to obtain local state estimation; And inputting