Tightly integrated navigation method of GNSS / DR based on SINS

Abstract

The invention belongs to the technical field of positioning and navigation, and particularly discloses a GNSS / DR (Global Navigation Satellite System / Digital Radio) tight integration navigation method based on an SINS (Strapdown Inertial Navigation System). The method comprises the following steps of: inputting a difference value between a pseudo range calculated by a GNSS (Global Navigation Satellite System) and a position calculated by an SINS (Strapdown Inertial Navigation System) into a filter as an observed quantity, and performing state error estimation; and correcting a navigation positioning result by using a state error estimation result, and outputting the corrected positioning result as a tightly integrated navigation positioning result. According to the scheme, the technical problems that an existing SINS / GNSS integrated navigation system is weak in anti-interference capacity, poor in system observability and low in precision are solved.

Description

Technical Field

[0001] This invention belongs to the technical field of positioning and navigation, specifically relating to a tightly integrated navigation method based on SINS and GNSS / DR. Background Technology

[0002] Currently, the Global Positioning System (GNSS) can provide users with all-weather, continuous, and real-time position, velocity, and time information, but it is easily affected by obstructions. Dead reckoning (DR) uses inertial and velocity sensors for positioning and is a commonly used vehicle positioning technology, but inertial sensor errors accumulate over time, so dead reckoning cannot be used for extended periods. This has led to the development of GNSS / DR integrated navigation, which can achieve continuous vehicle navigation and positioning.

[0003] Current vehicle navigation systems employ a loosely coupled GNSS / DR navigation approach based on SINS. In this system, dead reckoning (DR) using attitude azimuth and odometer distance traveled, and GNSS using satellite receivers to receive radio signals, operate independently, each outputting position and velocity measurements. The difference between these two calculations is used as the measurement input, and a Kalman filter estimates the SINS error. This estimated error is then used for feedback correction to provide the optimal combined navigation result. This system leverages the advantages of both satellite navigation and inertial navigation and is widely used in practical engineering. However, this approach has drawbacks: low accuracy; when the number of GNSS satellites is less than four, GNSS cannot provide position information, forcing the vehicle navigation system to switch to DR mode for navigation and positioning, resulting in low accuracy; the system is prone to oscillations when subjected to external interference, causing positioning results to diverge, thus exhibiting weak anti-interference capabilities; and traditional combined navigation systems have poor observability and weak compensation and suppression of SINS and GNSS errors. Summary of the Invention

[0004] The purpose of this invention is to provide a tightly integrated navigation method based on SINS and GNSS / DR to solve the technical problems of weak anti-interference ability, poor system observability, and low accuracy in current SINS / GNSS integrated navigation systems.

[0005] To achieve the above objectives, the present invention adopts the following technical solution: A compact GNSS / DR navigation method based on SINS includes: inputting the difference between the pseudorange calculated by GNSS and the position calculated by SINS as an observation into a filter to perform state error estimation; correcting the navigation and positioning results using the state error estimation results; and outputting the corrected positioning results as the compact GNSS / DR positioning results.

[0006] A tightly integrated GNSS / DR navigation system based on SINS includes: an error estimation module, used to input the difference between the pseudorange calculated by GNSS and the position calculated by SINS as an observation into a filter to perform state error estimation; and a correction output module, used to correct the navigation and positioning results using the state error estimation results, and output the corrected positioning results as the tightly integrated navigation and positioning results.

[0007] A computer-readable storage medium storing a computer program configured to execute the aforementioned SINS-based GNSS / DR tightly coupled navigation method at runtime.

[0008] An electronic device includes a memory and a processor, wherein the memory stores a computer program and the processor is configured to execute the aforementioned SINS-based GNSS / DR tightly coupled navigation method via the computer program.

[0009] In this invention, the difference between the pseudorange calculated by the GNSS receiver and the corresponding position output value of the SINS is used as a measurement for the Kalman filter to estimate the state error. The gyroscope and accelerometer error terms in the estimated value are used to perform feedback correction on the SINS. At the same time, the output feedback is used to directly correct the navigation output of the SINS. Thus, the ephemeris information obtained by GNSS and the pseudorange information between the receiver and the satellite are provided to the integrated navigation filter. By correcting the errors of the inertial devices, the navigation accuracy of the SINS is improved. At the same time, the pseudorange information is corrected, and the accuracy of GNSS is improved. This invention solves the technical problems of weak anti-interference ability, poor system observability, and low accuracy in the current SINS / GNSS integrated navigation system. It achieves the technical effects of improving the ability to track satellites, improving the dynamic characteristics of the receiver, and improving the anti-interference ability. Attached Figure Description

[0010] Figure 1 This is a flowchart illustrating a tightly integrated GNSS / DR navigation method based on SINS in an embodiment of the present invention. Figure 2 This is a flowchart illustrating a tightly integrated GNSS / DR navigation method based on SINS in an embodiment of the present invention. Figure 3 This is a schematic diagram of the structure of a tightly integrated GNSS / DR navigation system based on SINS in an embodiment of the present invention. Detailed Implementation

[0011] The present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments. The advantages and features of the present invention will become clearer from the following description and claims. It should be noted that the drawings are all in a very simplified form and are not to a precise scale, and are only used to facilitate and clarify the illustration of the embodiments of the present invention.

[0012] It should be noted that, in order to clearly illustrate the content of this invention, several embodiments are provided to further explain different implementations of the invention. These embodiments are enumerated rather than exhaustive. Furthermore, for the sake of brevity, content mentioned in the preceding embodiments is often omitted in the following embodiments. Therefore, content not mentioned in the later embodiments can be referred to in the preceding embodiments.

[0013] Example 1 A compactly integrated GNSS / DR navigation method based on SINS, such as Figure 1 As shown, the method includes: S102, the difference between the pseudorange calculated by GNSS and the position calculated by SINS is used as the observation input to the filter to perform state error estimation; S104, use the state error estimation result to correct the navigation and positioning result, and output the corrected positioning result as the compact combination navigation and positioning result.

[0014] As an optional implementation method, obtaining the pseudorange calculated by GNSS includes: capturing satellite signals using a receiver, and obtaining the pseudorange and pseudorange rate through radio frequency signal processing and a tracking loop.

[0015] As an optional implementation method, obtaining the position calculated by SINS includes: obtaining the INS position obtained by inertial navigation calculation using SINS combined with ephemeris.

[0016] As an optional implementation, state error estimation includes: using the IMU linearized error equation as the system equation, and employing a filtering algorithm to perform optimal estimation of the observations.

[0017] As an optional implementation, the observations also include: attitude error, velocity error, dead reckoning (DR) error, gyro drift error, accelerometer error, and odometer coefficient error.

[0018] As an optional implementation, the original SINS measurement is corrected using the accelerometer error estimation results and gyroscope drift error estimation results in the estimation results, so as to perform real-time calibration and correction of the SINS measurement.

[0019] Specifically, the SINS-based GNSS / DR compact navigation method utilizes acceleration and angular velocity information measured by the IMU to estimate pseudorange and pseudorange rate consistent with the output parameters of each GNSS channel. This is compared with the pseudorange and pseudorange rate output by the GNSS, and the difference is used as a measurement for the navigation filter. After optimal estimation by the filter, correction information is provided. Simultaneously, the corrected IMU information is used to assist the GNSS receiver tracking loop, increasing the system's dynamic performance. By improving the GNSS receiver's acquisition capability under poor satellite conditions, the overall capability of the integrated navigation system is enhanced. Since the compact combination mode utilizes raw information such as pseudorange and pseudorange rate output by each GNSS receiver channel, no velocity and position calculations are required. Therefore, when the number of satellites received is less than four, the integrated navigation algorithm filter can still filter normally, thereby using the state estimation results to correct IMU device parameters and system navigation errors. Furthermore, because the pseudorange and pseudorange rate in the compact combination mode are not time-dependent compared to the position and velocity output by the GNSS receiver, they are more beneficial to the results of the integrated filtering.

[0020] Alternatively, the overall architecture of the above-described compact navigation method is not limited to, for example... Figure 2 As shown, the workflow is as follows: After the satellite signal is acquired and tracked by the satellite receiver loop, information such as pseudorange and pseudorange rate is obtained. The initial position, velocity, attitude and other information of the integrated navigation system are used to initialize the SINS module. Combined with the satellite ephemeris information, the IMU measurement data is calculated by navigation to obtain information such as pseudorange and pseudorange rate. In the navigation filter, pseudorange and pseudorange rate are used as observations. The IMU linearized error equation is used as the system equation. The filtering algorithm is used to make the optimal estimate of the IMU's position, velocity, attitude and inertial device error, thereby giving the navigation and positioning solution of the system.

[0021] The SINS-based GNSS / DR tightly integrated navigation method in this application integrates GNSS and DR observations into the integrated navigation algorithm on the basis of existing GNSS / IMU integrated navigation, thereby suppressing inertial navigation divergence.

[0022] Specifically, the state equation for the Kalman filter is expressed as: (1) In the formula: The system transition matrix; The system noise matrix; This represents system noise.

[0023] In this embodiment, the GNSS output positioning result, DR output information, and odometer coefficient error are all included in the state vector. The INS portion of the filter state vector is not limited to including: attitude error, velocity error, position error, dead reckoning (DR) error, gyro drift error, accelerometer error, and odometer coefficient error, and is not limited to being represented as: (2) The equations for attitude, velocity, and position errors are not limited to those expressed as: (3) The system matrix of INS is represented as follows: (4) System noise vector The random noise from the gyroscope and accelerometer is specifically expressed as: (5) System noise distribution matrix Specifically, it is expressed as follows: (6) Traditional vehicle navigation systems employ a loosely integrated GNSS / DR navigation method based on SINS, using only speed and position information as measurements. This fails to fully utilize GNSS pseudorange and other information to estimate and suppress SINS / DR errors. In this application's embodiment, GNSS pseudorange is selected as the state variable. Its differential equation is expressed as: (7) The system matrix, system noise, and noise distribution matrix are respectively , , .

[0024] Combining the SINS and GNSS state equations, the system state equation is expressed as follows: (8) The system measurement involves SINS calculating the pseudorange between itself and the satellite based on ephemeris information provided by GNSS, and then subtracting this pseudorange from the preprocessed pseudorange from the receiver. This difference is used as the measurement. To fully integrate GNSS measurement results with SINS / DR calculation results and improve navigation accuracy, the process quantities output by GNSS are directly used in integrated navigation to improve navigation efficiency and ensure real-time performance. The pseudorange measurement equation is expressed as follows: (9) In the formula, , in, , ; The representation is: , , , (10) ( , , ) represents the location of the receiver. , , () represents the position of the i-th visible star; Let be the distance from the receiver to the i-th visible star.

[0025] , , This refers to the clock bias of the GNSS receiver.

[0026] Since DR observations are calculated based on the geographic coordinate system, while GNSS pseudorange observations are calculated based on the WGS-84 coordinate system, they must be unified into the same coordinate system to achieve information fusion. Because DR does not contain elevation information, this invention unifies both into the geographic coordinate system, reducing conversion errors and further improving the accuracy of tightly coupled navigation.

[0027] The filtering process specifically includes: The one-step state prediction equation is expressed as: (11)

[0028] The state estimation equation is expressed as: (12)

[0029] Filter gain equation: (13)

[0030] The one-step prediction mean square error equation is expressed as: (14) The equation for estimating the mean square error is expressed as: (15)

[0031] or (16)

[0032] In this embodiment, the SINS-based GNSS / DR tightly integrated navigation system inputs the difference between the pseudoranges obtained from the GNSS carrier tracking loop output and the pseudoranges calculated by SINS based on ephemeris into a Kalman filter as an observation. The filtered update result is used to correct the positioning result calculated by the navigation and positioning system, outputting the tightly integrated navigation result. Simultaneously, the constant zero bias of the accelerometer and gyroscope is used to correct the original measurements of the inertial devices, achieving real-time calibration of the integrated navigation system. This method improves the integrated navigation system's ability to track dynamic information, enhancing signal reliability and positioning accuracy. GNSS clock bias and SINS filter the pseudoranges of GNSS and SINS, while SINS provides velocity assistance to GNSS, addressing current issues in SINS / GNSS integrated navigation systems such as weak anti-interference capability, poor system observability, and low accuracy. This improves the ability to track satellites, thereby enhancing the receiver's dynamic characteristics and anti-interference capability.

[0033] In a loosely integrated GNSS / DR navigation system based on SINS, when satellite reception is poor, the GNSS receiver cannot guarantee normal navigation and positioning calculations, resulting in poor navigation performance for the DR system. However, the tightly integrated SINS / GNSS navigation system in this embodiment uses pseudorange and pseudorange rate of GNSS and SINS as measurements for filtering, improving its satellite tracking capability and thus enhancing the dynamic characteristics and anti-interference capability of the integrated navigation system. Therefore, compared with the traditional loosely integrated SINS / GNSS / DR navigation system, the tightly integrated navigation method in this embodiment has stronger observability and anti-interference capability.

[0034] Example 2 A tightly integrated GNSS / DR navigation system based on SINS, such as Figure 3 As shown, the system includes: The error estimation module 302 is used to input the difference between the pseudorange calculated by GNSS and the position calculated by SINS as the observation into the filter to perform state error estimation. The correction output module 304 is used to correct the navigation and positioning results using the state error estimation results, and output the corrected positioning results as compact combination navigation and positioning results.

[0035] As an optional implementation, the SINS-based GNSS / DR tightly integrated navigation system also includes a calibration and correction module, which is used to correct the original SINS measurements using the accelerometer error estimation results and gyroscope drift error estimation results in the estimation results, so as to perform real-time calibration and correction of SINS measurements.

[0036] As an optional implementation, the pseudorange calculated by GNSS in a tightly integrated navigation system based on SINS and GNSS / DR is obtained by: acquiring satellite signals using a receiver, and obtaining the pseudorange and pseudorange rate through radio frequency signal processing and a tracking loop.

[0037] As an optional implementation, the SINS-based GNSS / DR tightly integrated navigation system obtains the position calculated by SINS, including: obtaining the INS position obtained by inertial navigation calculation using SINS combined with ephemeris.

[0038] As an optional implementation, the state error estimation of the SINS-based GNSS / DR tightly integrated navigation system includes: using the IMU linearized error equation as the system equation and employing a filtering algorithm to perform optimal estimation of the observations.

[0039] As an optional implementation, the observations of the SINS-based tightly integrated GNSS / DR navigation system also include: attitude error, velocity error, dead reckoning (DR) error, gyro drift error, accelerometer error, and odometer coefficient error.

[0040] In this embodiment, the state error is estimated by subtracting the pseudorange calculated by the GNSS receiver from the corresponding position output value of the SINS, and using this difference as a measurement for the Kalman filter. The gyroscope and accelerometer error terms in the estimated value are used to perform feedback correction on the SINS. At the same time, the navigation output of the SINS is directly corrected by the output feedback. Thus, the ephemeris information obtained by GNSS and the pseudorange information between the satellite and the system are provided to the integrated navigation filter. By correcting the errors of the inertial devices, the navigation accuracy of the SINS is improved. At the same time, the pseudorange information is corrected, and the accuracy of GNSS is improved. This solves the technical problems of weak anti-interference ability, poor system observability, and low accuracy in the current SINS / GNSS integrated navigation system. It achieves the technical effects of improving the ability to track satellites, improving the dynamic characteristics of the receiver, and improving the anti-interference ability.

[0041] Example 3 In another aspect, the present invention provides an electronic device for implementing the above-described tightly integrated navigation method based on SINS GNSS / DR. This electronic device is not limited to a terminal device or server within a system. The electronic device includes, but is not limited to, a memory and a processor. The memory stores a computer program, and the processor is configured to execute the steps of any of the above-described method embodiments via the computer program.

[0042] Example 4 In another aspect, the present invention provides a computer program product or computer program including computer instructions stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium and executes the computer instructions, causing the computer device to perform the methods provided in various alternative embodiments of the SINS-based GNSS / DR tightly coupled navigation method described above. The computer program is configured to execute the steps in any of the above method embodiments during runtime.

Claims

1. A SINS-based GNSS / DR tight-coupled navigation method, characterized in that, include: The difference between the pseudorange calculated by GNSS and the position calculated by SINS is used as the observation input to the filter for state error estimation. The navigation and positioning results are corrected using the state error estimation results, and the corrected positioning results are output as compact combination navigation and positioning results.

2. The SINS-based GNSS / DR tight-coupled navigation method of claim 1, wherein, Obtaining pseudorange calculated by GNSS includes: using a receiver to capture satellite signals, and obtaining pseudorange and pseudorange rate through radio frequency signal processing and tracking loop.

3. The SINS-based GNSS / DR tight-coupled navigation method of claim 1, wherein, Obtain the position calculated by SINS, including: obtaining the INS position obtained by inertial navigation calculation using SINS combined with ephemeris.

4. The SINS-based GNSS / DR tight-coupled navigation method of claim 1, wherein, State error estimation includes: using the IMU linearized error equation as the system equation, and employing a filtering algorithm to perform optimal estimation of the observations.

5. The SINS-based GNSS / DR tight-coupled navigation method of claim 1, wherein, The observations also include: attitude error, velocity error, dead reckoning (DR) error, gyro drift error, accelerometer error, and odometer coefficient error.

6. The SINS-based GNSS / DR tight-coupled navigation method of claim 5, wherein, The original SINS measurements are corrected using the accelerometer error estimation results and gyroscope drift error estimation results from the estimation results, so as to perform real-time calibration and correction of SINS measurements.

7. A tightly coupled GNSS / DR navigation system based on SINS, characterized in that, include: The error estimation module is used to input the difference between the pseudorange calculated by GNSS and the position calculated by SINS as the observation into the filter to perform state error estimation. The correction output module is used to correct the navigation and positioning results using the state error estimation results, and outputs the corrected positioning results as compact combination navigation and positioning results.

8. The SINS-based GNSS / DR tight-coupled navigation system of claim 7, wherein, It also includes a calibration and correction module, which is used to perform real-time calibration and correction of SINS measurements by using the accelerometer error estimation results and gyroscope drift error estimation results in the estimation results.

9. A computer-readable storage medium having stored therein a computer program, wherein The computer program is configured to execute the tightly integrated navigation method based on SINS GNSS / DR as described in any one of claims 1 to 6 at runtime.

10. An electronic device comprising a memory and a processor, the memory storing a computer program, the processor being configured to execute, via the computer program, the compact combination navigation method of SINS-based GNSS / DR according to any one of claims 1 to 6.

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