High-precision IMU and vision combined unmanned aerial vehicle navigation method

Abstract

The invention provides a high-precision IMU (inertial measurement unit) and vision combined unmanned aerial vehicle navigation method, an unmanned aerial vehicle is provided with a high-precision IMU resolving module, a vision navigation module, a GNSS (global navigation satellite system) module and a main control processor, and the main control processor executes the following steps: judging whether the precision and signal of the current GNSS module meet navigation requirements or not; if the precision and the signal of the current GNSS module do not meet the navigation requirements, judging whether the visual navigation module works normally or not; and if the visual navigation module cannot work normally, acquiring a latitude estimation value output by the high-precision IMU resolving module, and performing navigation according to the latitude estimation value output by the high-precision IMU resolving module. The latitude can be estimated in real time at least by sensing the earth rotation effect through a high-precision IMU, and then the earth rotation angular rate is compensated during attitude calculation; and the vision / laser radar and the high-precision IMU are combined to realize long-time high-precision positioning and navigation.

Description

Technical Field

[0001] This application relates to the field of autonomous navigation technology for unmanned aerial vehicles (UAVs), and in particular to a UAV navigation method that combines a high-precision IMU and vision. Background Technology

[0002] The navigation system is the core technology for UAVs to achieve autonomous flight, including GNSS navigation systems, visual navigation systems, and so on. Modern UAV GNSS modules can simultaneously receive signals from multiple systems such as GPS, BeiDou, GLONASS, and Galileo, improving positioning reliability through multi-band reception. Visual navigation systems can acquire environmental information through visual sensors and combine them with computer vision algorithms to achieve autonomous positioning and path planning.

[0003] However, current UAV navigation processes still have problems such as the inability of UAV navigation systems to obtain latitude information in the absence of GNSS or in environments where GNSS is denied, resulting in an inability to accurately compensate for the Earth's rotation effect, or the visual navigation system being prone to failure when features are missing or lighting conditions are poor, and the rapid divergence of INS solutions after failure. Summary of the Invention

[0004] In view of this, the purpose of this application is to provide a UAV navigation method that combines high-precision IMU and vision, which can at least estimate latitude in real time by sensing the Earth's rotation effect through high-precision IMU, and then compensate for the Earth's rotation angular rate during attitude calculation; and combine vision / LiDAR with high-precision IMU to achieve long-term high-precision positioning and navigation.

[0005] This application provides a high-precision IMU and vision-based UAV navigation method. The UAV is equipped with a high-precision IMU decoding module, a visual navigation module, a GNSS module, and a main control processor. The main control processor performs the following steps:

[0006] Determine whether the accuracy and signal strength of the current GNSS module meet navigation requirements;

[0007] If the accuracy and signal of the current GNSS module do not meet the navigation requirements, then determine whether the visual navigation module is working properly;

[0008] If the visual navigation module fails to function properly, the latitude estimate output by the high-precision IMU solution module is obtained, and navigation is performed based on the latitude estimate output by the high-precision IMU solution module.

[0009] In some embodiments, the method further includes:

[0010] If the visual navigation module is working properly, then obtain the position source and heading source output by the visual navigation module;

[0011] Based on the initial alignment and heading, the visual coordinate system is transformed to the navigation coordinate system for navigation.

[0012] In some embodiments, the visual navigation module performs the following steps:

[0013] Heading alignment can be performed using the heading output from the GNSS module, or self-alignment can be performed using the angular rate output from the high-precision IMU module.

[0014] The GNSS module is a dual-antenna GNSS module, which determines the heading through the following steps:

[0015] The heading angle of the UAV is measured by carrier phase difference.

[0016] In some embodiments, the high-precision IMU solving module performs the following steps:

[0017] Determine whether the high-precision IMU solution module stores the initial latitude value;

[0018] If the high-precision IMU solution module does not store the initial latitude value, the three-axis angular velocity and three-axis acceleration of the machine body measured by the IMU are obtained in a static state, and the attitude and heading angle are estimated based on the principles of gravity and Earth's rotation.

[0019] Based on the three-axis angular rates and attitude matrix measured by the gyroscope, the three-axis angular rates measured by the gyroscope are converted into the angular rates of the navigation system;

[0020] The latitude estimate is obtained based on the decomposition principle of the three-axis angular rate of the navigation system and the Earth's rotation angular rate in the navigation system.

[0021] After navigation, the latitude value and the local Earth rotation rate are updated in real time, and compensation is made for the Earth's angular rate.

[0022] In some embodiments, the method further includes:

[0023] If the high-precision IMU solution module does not store the initial latitude value, the angular rate of the UAV is obtained to estimate the initial latitude.

[0024] After static alignment, the attitude and heading are obtained and then converted into an attitude matrix;

[0025] The projection of the Earth's rotational angular velocity vector onto the navigation coordinate system is calculated using the following formula:

[0026] ;

[0027] Where N, E, and D represent the north, east, and ground directions of the navigation coordinate system, respectively. This is the projection of the Earth's rotational angular velocity vector onto the navigation coordinate system n. The angular velocity of Earth's rotation. (Earth's rotational angular velocity), e represents the Earth system. The projection of the three-axis angular rate measurement of the machine body measured by the gyroscope onto the machine system, where b represents the machine system, i represents the inertial frame, and ib represents the rotation of the machine system relative to the inertial frame. In the stationary state, the output of the high-precision gyroscope is approximately the measured value of the Earth's rotation angular rate.

[0028] The formula for projecting the Earth's rotational angular velocity vector into the local navigation coordinate system is also:

[0029] ;

[0030] in, Latitude (Earth's rotational angular velocity), e represents the Earth system, i represents the inertial frame, and N, E, and D represent the north, east, and ground directions of the navigation coordinate system, respectively. This is the projection of the Earth's rotational angular velocity vector onto the navigation coordinate system;

[0031] Among them, based on the projection formula of the Earth's rotation angular velocity vector in the local navigation coordinate system and the projection of the Earth's rotation angular velocity vector in the navigation coordinate system, the core equation for calculating latitude from gyroscope measurements is as follows:

[0032] ;

[0033] The method further includes: calculating the latitude based on the gyroscope measurement values ​​and determining the carrier angular rate compensation to obtain more accurate attitude and heading information;

[0034] More accurate attitude and heading information can be obtained through the following formula:

[0035] ;

[0036] in, The compensated gyroscope measures the angular rate for attitude calculation, where n represents the navigation system and b represents the mechanical system. The projection of the three-axis angular rate measurements of the machine body, as measured by the gyroscope, onto the machine system. This is the projection of the Earth's rotational angular velocity vector onto the navigation coordinate system. This is the positional velocity of the carrier, caused by the carrier's motion around the Earth.

[0037] In some embodiments, the latitude estimate is updated based on the initial latitude value, the UAV's northward velocity, the meridian curvature radius, and altitude using the following formula:

[0038] ;

[0039] in, Let h be the radius of curvature of the meridian, and h be the height. This is the current latitude estimate. Here, m represents the latitude value at the previous moment. Update the time step for IMU. Northbound speed, with subscript N indicating northbound and superscript n indicating navigation system.

[0040] In some embodiments, the method further includes:

[0041] If the accuracy and signal of the current GNSS module meet the navigation requirements, then obtain the heading angle output by the dual antennas;

[0042] Control the visual data processing module to calculate the initial heading angle;

[0043] Calculate the rotation offset based on the initial heading angle and the heading angle output by the dual antennas;

[0044] The visual coordinate system of the visual data processing module is rotated by the rotation offset to align the visual coordinate system of the visual data processing module with the navigation system.

[0045] In some embodiments, the method further includes:

[0046] The alignment accuracy of the IMU heading is higher than that of the GNSS heading.

[0047] If the IMU heading alignment accuracy is higher than the GNSS heading accuracy, then the IMU heading alignment is used instead of the dual-antenna heading.

[0048] In some embodiments, the method further includes:

[0049] Perform pure inertial navigation;

[0050] Based on GNSS signal strength, the autonomous switching mechanism determines the optimal fusion module according to sensor availability and quality;

[0051] The optimal navigation solution is obtained from the EKF fusion module, and navigation results containing information such as position, attitude, and velocity are output at a fixed frequency.

[0052] Among them, the pure inertial navigation mode includes:

[0053] Continuously receive IMU data (accelerometer and gyroscope);

[0054] Attitude, velocity, and position are calculated in the INS solution module;

[0055] Output preliminary navigation results.

[0056] In some embodiments, the fusion module includes: a GNSS / INS combined mode and a visual / INS combined mode;

[0057] When the fusion module is in GNSS / INS combined mode, the following steps are performed:

[0058] Receive GNSS positioning data;

[0059] The results are fused with the INS solution in the EKF fusion module;

[0060] When the fusion module is in vision / INS combined mode, the following steps are performed:

[0061] The camera module acquires image data;

[0062] Visual odometry calculates relative motion;

[0063] The results are fused with the INS solution in the EKF fusion module.

[0064] This application provides a UAV navigation method that combines a high-precision IMU and vision. It can at least estimate latitude in real time by sensing the Earth's rotation effect through the high-precision IMU, and then compensate for the Earth's rotation angular rate during attitude calculation; and combine vision / LiDAR with the high-precision IMU to achieve long-term high-precision positioning and navigation.

[0065] To make the above-mentioned objectives, features and advantages of this application more apparent and understandable, preferred embodiments are described below in detail with reference to the accompanying drawings. Attached Figure Description

[0066] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of the present invention and should not be regarded as a limitation on the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0067] Figure 1 A flowchart illustrating a high-precision IMU and vision-based unmanned aerial vehicle (UAV) navigation method provided in an embodiment of the present invention;

[0068] Figure 2 A schematic diagram of another high-precision IMU and vision-based UAV navigation method provided in an embodiment of the present invention;

[0069] Figure 3 This is a schematic diagram of a navigation system for an unmanned aerial vehicle (UAV) provided in an embodiment of the present invention. Detailed Implementation

[0070] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. The components of the embodiments of the present invention described and shown in the accompanying drawings can generally be arranged and designed in various different configurations.

[0071] Therefore, the following detailed description of the embodiments of the invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention, but merely to illustrate selected embodiments of the invention. All other embodiments obtained by those skilled in the art based on the embodiments of the invention without inventive effort are within the scope of protection of the invention.

[0072] First, the applicable application scenarios of this application will be introduced. This application can be applied to the field of autonomous navigation technology for unmanned aerial vehicles (UAVs).

[0073] The navigation system is the core technology for UAVs to achieve autonomous flight, including GNSS navigation systems, visual navigation systems, and so on. Modern UAV GNSS modules can simultaneously receive signals from multiple systems such as GPS, BeiDou, GLONASS, and Galileo, improving positioning reliability through multi-band reception. Visual navigation systems can acquire environmental information through visual sensors and combine them with computer vision algorithms to achieve autonomous positioning and path planning.

[0074] However, current UAV navigation processes still have problems such as the inability of UAV navigation systems to obtain latitude information in the absence of GNSS or in environments where GNSS is denied, resulting in an inability to accurately compensate for the Earth's rotation effect, or the visual navigation system being prone to failure when features are missing or lighting conditions are poor, and the rapid divergence of INS solutions after failure.

[0075] Furthermore, traditional pure inertial navigation systems suffer from problems such as rapid error accumulation without external assistance, and exponential divergence between attitude angle error and position error.

[0076] Please see Figure 1 , Figure 1 This is a flowchart illustrating a high-precision IMU and vision-based unmanned aerial vehicle (UAV) navigation method provided in an embodiment of this application. Figure 1 As shown in the embodiments of this application, the high-precision IMU and vision-based UAV navigation method includes:

[0077] S101. Determine whether the accuracy and signal of the current GNSS module meet the navigation requirements.

[0078] If the accuracy and signal of the current GNSS module do not meet the navigation requirements, then execute S102 to determine whether the visual navigation module is working properly.

[0079] If the visual navigation module fails to function properly, then execute S103 to obtain the latitude estimate output by the high-precision IMU solution module, and perform navigation based on the latitude estimate output by the high-precision IMU solution module.

[0080] Please see here. Figure 3 The UAV proposed in this application is equipped with a high-precision IMU solution module, a visual navigation module, a GNSS module, and a main control processor.

[0081] Among them, the high-precision IMU calculation module has an accuracy of 0.01° / h and below.

[0082] Specifically, the residuals of motion estimates (position, attitude) output by the IMU and different navigation modules can be compared, and the chi-square test (χ² test) based on the residuals can be used to determine which GNSS module and visual navigation module has malfunctioned or experienced performance degradation.

[0083] The high-precision IMU solution module performs the following steps:

[0084] Determine whether the high-precision IMU solution module stores the initial latitude value;

[0085] If the high-precision IMU solution module does not store the initial latitude value, the three-axis angular velocity and three-axis acceleration of the machine body measured by the IMU are obtained in a static state, and the attitude and heading angle are estimated based on the principles of gravity and Earth's rotation.

[0086] Based on the three-axis angular rates and attitude matrix measured by the gyroscope, the three-axis angular rates measured by the gyroscope are converted into the angular rates of the navigation system;

[0087] The latitude estimate is obtained based on the decomposition principle of the three-axis angular rate of the navigation system and the Earth's rotation angular rate in the navigation system.

[0088] After navigation, the latitude value and the local Earth rotation rate are updated in real time, and compensation is made for the Earth's angular rate.

[0089] Specifically, the method further includes:

[0090] If the high-precision IMU solution module does not store the initial latitude value, the angular rate of the UAV is obtained to estimate the initial latitude.

[0091] After static alignment to obtain attitude and heading, convert them into an attitude matrix.

[0092] The projection of the Earth's rotational angular velocity vector onto the navigation coordinate system is calculated using the following formula:

[0093] ;

[0094] Where N, E, and D represent the north, east, and ground directions of the navigation coordinate system, respectively. This is the projection of the Earth's rotational angular velocity vector onto the navigation coordinate system. The angular velocity of Earth's rotation. (Earth's rotational angular velocity), e represents the Earth system. The projection of the three-axis angular rate measurement of the machine body measured by the gyroscope onto the machine system is given by b, i, and ib, where b represents the machine system, i represents the inertial frame, and ib represents the rotation of the machine system relative to the inertial frame. In the stationary state, the output of the high-precision gyroscope is approximately the measured value of the Earth's rotation angular rate.

[0095] The formula for projecting the Earth's rotational angular velocity vector into the local navigation coordinate system is also:

[0096] ;

[0097] in, Latitude (Earth's rotational angular velocity), e represents the Earth system, i represents the inertial frame, and N, E, and D represent the north, east, and ground directions of the navigation coordinate system, respectively. This is the projection of the Earth's rotational angular velocity vector onto the navigation coordinate system.

[0098] Based on the above formula, and according to the projection formula of the Earth's rotation angular velocity vector in the local navigation coordinate system and the projection of the Earth's rotation angular velocity vector in the navigation coordinate system, the core equation for calculating latitude from gyroscope measurements is obtained as follows:

[0099] .

[0100] The method further includes: calculating the latitude based on gyroscope measurements and determining the carrier angular rate compensation to obtain more accurate attitude and heading information.

[0101] More accurate attitude and heading information can be obtained through the following formula:

[0102] ;

[0103] in, The compensated gyroscope measures the angular rate for attitude calculation, where n represents the navigation system and b represents the mechanical system. The projection of the three-axis angular rate measurements of the machine body, as measured by the gyroscope, onto the machine system. This is the projection of the Earth's rotational angular velocity vector onto the navigation coordinate system. This is the positional velocity of the carrier, caused by the carrier's motion around the Earth.

[0104] Specifically, the latitude estimate is updated using the following formula based on the initial latitude value, the UAV's northward velocity, the meridian curvature radius, and altitude:

[0105] ;

[0106] in, Let h be the radius of curvature of the meridian, and h be the height. This is the current latitude estimate. Here, m represents the latitude value at the previous moment. Update the time step for IMU. Northbound speed, with subscript N indicating northbound and superscript n indicating navigation system.

[0107] It should be noted that the basic principle of latitude estimation and recursion is as follows: attitude and heading alignment is performed using a high-precision IMU; after alignment, the angular rate measured by the three-axis gyroscope is decomposed into the navigation coordinate system (NED) using the attitude transformation matrix. This value is approximately equal to the three-axis components of the Earth's rotation angular rate in the navigation coordinate system; latitude can be approximately estimated using the geographic rotation model.

[0108] Using the above process, latitude estimation calculations can be performed during the initial and navigation processes.

[0109] In some embodiments, the method further includes:

[0110] If the visual navigation module is working properly, then obtain the position source and heading source output by the visual navigation module;

[0111] Based on the initial alignment and heading, the visual coordinate system is transformed to the navigation coordinate system for navigation.

[0112] Specifically, the method further includes:

[0113] If the accuracy and signal of the current GNSS module meet the navigation requirements, then obtain the heading angle output by the dual antennas;

[0114] Control the visual data processing module to calculate the initial heading angle;

[0115] Calculate the rotation offset based on the initial heading angle and the heading angle output by the dual antennas;

[0116] The visual coordinate system of the visual data processing module is rotated by the rotation offset to align the visual coordinate system of the visual data processing module with the navigation system.

[0117] The method further includes:

[0118] The alignment accuracy of the IMU heading is higher than that of the GNSS heading.

[0119] If the IMU heading alignment accuracy is higher than the GNSS heading accuracy, then the IMU heading alignment is used instead of the dual-antenna heading.

[0120] Specifically, the visual navigation module performs the following steps: Visual coordinates can be aligned using the GNSS dual-antenna heading or the inertial navigation self-alignment heading, allowing for continued geographic navigation velocity and position calculations even in GNSS denied environments; the dual-antenna GNSS measures the heading angle using carrier phase differential measurement, using this heading as the true value to align the visual coordinate system. The process includes: when GNSS is available, acquiring the heading angle ψGNSS output by the dual antennas; simultaneously calculating the initial heading angle ψvisual; calculating the rotation offset ψGNSS − ψvisual; rotating the visual coordinate system by Δψ and aligning it with the navigation system (NED); if there is no dual-antenna heading, a high-precision IMU is required to align the heading instead, with the priority selected based on the sensor's accuracy.

[0121] Specifically, the visual navigation module performs the following steps:

[0122] Heading alignment can be performed using the heading output from the GNSS module, or self-alignment can be performed using the angular rate output from the high-precision IMU module.

[0123] The GNSS module is a dual-antenna GNSS module, which determines the heading through the following steps:

[0124] The heading angle of the UAV is measured by carrier phase difference.

[0125] In some exemplary embodiments, this application can use GNSS / IMU for combined navigation under normal circumstances. If the GNSS accuracy decreases or the signal is lost due to environmental factors, the position source and heading source of visual navigation are switched (at this time, the visual position and heading are basically consistent with GNSS) to continue the navigation task. If the vision fails, navigation is achieved using a high-precision IMU (at this time, due to the self-rotation rate compensation, the performance of the IMU is fully utilized, and long-term pure inertial navigation can be achieved).

[0126] Thus, based on the latitude estimation algorithm based on the Earth motion model proposed in this application, navigation accuracy can be significantly improved and the pure inertial navigation time extended in GNSS-free environments without manual latitude setting. An adaptive integrated navigation switching mechanism is developed to seamlessly connect navigation tasks. In GNSS-denied environments, the system automatically switches between visual position and heading sources, and the position and heading do not change significantly after switching, allowing for continued high-precision navigation. Stable navigation is achieved in visual integrated navigation mode. When visual navigation fails, the pure inertial navigation time is greatly extended (attitude drift speed is reduced from 15° / h to approximately 0.01° / h, achieving navigation accuracy of 1.5 mile / h under pure inertial conditions), fully utilizing the performance of the high-precision IMU. The IMU performs latitude estimation automatically after power-on (0.05° error, sufficient for estimation and compensation of rotation), without the need for GNSS or manual setting.

[0127] As an example, the UAV hardware components proposed in this application include: a high-precision IMU (gyroscope zero-bias stability ≤0.01° / h, accelerometer zero-bias ≤50μg), a camera module, a GNSS module, a main control processor, etc.

[0128] The system initialization phase includes power-on initialization and static latitude estimation. The power-on initialization steps include: starting all sensor modules (high-precision IMU, camera module, GNSS module); executing sensor self-test and calibration procedures; and initializing each algorithm module (latitude estimation, visual odometry, INS calculation, etc.).

[0129] Static latitude estimation includes: in a stationary state (detected by IMU); obtaining initial position information using a GNSS module, or calculating precise latitude using a latitude estimation module.

[0130] For details, please refer to Figure 2 , Figure 2 This is a schematic diagram of another high-precision IMU and vision-based UAV navigation method provided in an embodiment of the present invention.

[0131] During the navigation operation phase, the steps of the pure inertial navigation mode (INS solution) include: continuously receiving IMU data (accelerometer and gyroscope); performing attitude, velocity and position calculations in the INS solution module; and outputting preliminary navigation results.

[0132] Please continue reading. Figure 2 This application can also perform multi-sensor fusion navigation, the specific steps of which include: an autonomous switching mechanism to select the best fusion module based on sensor availability and quality; GNSS / INS combination mode (when GNSS signal is available): receiving GNSS positioning data; and fusing the GNSS and INS solution results in the EKF fusion module.

[0133] Please continue reading. Figure 2 This application can also adopt a visual / INS combined mode, the specific steps of which include: the camera module acquiring image data; the visual odometry calculating relative motion; and fusing the results with the INS solution in the EKF fusion module.

[0134] Finally, real-time navigation output is performed, and the specific steps include: obtaining the optimal navigation solution from the EKF fusion module; and outputting navigation results containing information such as position, attitude, and velocity at a fixed frequency.

[0135] Among them, the EKF (Extended Kalman Filter) fusion module in the UAV is the core component of the flight control system, which achieves high-precision state estimation through multi-sensor data fusion.

[0136] In some embodiments, the method further includes: performing a pure inertial navigation mode; determining the optimal fusion module based on the availability and quality of the sensors according to the GNSS signal strength and an autonomous switching mechanism; obtaining the optimal navigation solution from the EKF fusion module; and outputting navigation results containing information such as position, attitude, and velocity at a fixed frequency.

[0137] The pure inertial navigation mode includes: continuously receiving IMU data (accelerometer and gyroscope); calculating attitude, velocity, and position in the INS calculation module; and outputting preliminary navigation results.

[0138] In some embodiments, the fusion module includes: a GNSS / INS combined mode and a visual / INS combined mode.

[0139] When the fusion module is in GNSS / INS combined mode, the following steps are performed: receiving GNSS positioning data; and fusing it with the INS solution in the EKF fusion module.

[0140] When the fusion module is in visual / INS combined mode, the following steps are performed: the camera module acquires image data; the visual odometry calculates relative motion; and the results are fused with the INS solution in the EKF fusion module.

[0141] Thus, the UAV navigation method combining high-precision IMU and vision proposed in this application can at least estimate latitude in real time by sensing the Earth's rotation effect through the high-precision IMU, and then compensate for the Earth's rotation angular rate during attitude calculation; and achieve long-term high-precision positioning and navigation by combining vision / LiDAR with high-precision IMU.

[0142] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile memory and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, artificial intelligence (AI) processors, etc., and are not limited to these.

[0143] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this application.

[0144] The embodiments described above are merely examples of several implementation methods of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of this patent application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these modifications and improvements all fall within the protection scope of this application.

[0145] It should be understood that although the steps in the flowcharts of the embodiments described above are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the embodiments described above may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages of other steps.

Claims

1. A high-precision IMU and vision-based unmanned aerial vehicle (UAV) navigation method, characterized in that, The UAV is equipped with a high-precision IMU decoding module, a visual navigation module, a GNSS module, and a main control processor. The main control processor performs the following steps: Determine whether the accuracy and signal strength of the current GNSS module meet navigation requirements; If the accuracy and signal of the current GNSS module do not meet the navigation requirements, then determine whether the visual navigation module is working properly; If the visual navigation module fails to function properly, the latitude estimate output by the high-precision IMU solution module is obtained, and navigation is performed based on the latitude estimate output by the high-precision IMU solution module.

2. The method according to claim 1, characterized in that, The method further includes: If the visual navigation module is working properly, then obtain the position source and heading source output by the visual navigation module; The visual coordinate system is transformed to the navigation coordinate system based on the initial alignment heading, and then navigation is performed based on the position source and heading source output by the visual navigation module.

3. The method according to claim 1, characterized in that, The visual navigation module performs the following steps: Heading alignment can be performed using the heading output from the GNSS module, or self-alignment can be performed using the angular rate output from the high-precision IMU module. The GNSS module is a dual-antenna GNSS module, which determines the heading through the following steps: The heading angle of the UAV is measured by carrier phase difference.

4. The method according to claim 1, characterized in that, The high-precision IMU solution module performs the following steps: Determine whether the high-precision IMU solution module stores the initial latitude value; If the high-precision IMU solution module does not store the initial latitude value, the three-axis angular velocity and three-axis acceleration of the machine body measured by the IMU are obtained in a static state, and the attitude and heading angle are estimated based on the principles of gravity and Earth's rotation. Based on the three-axis angular rates and attitude matrix measured by the gyroscope, the three-axis angular rates measured by the gyroscope are converted into the angular rates of the navigation system; The latitude estimate is obtained based on the decomposition principle of the three-axis angular rate of the navigation system and the Earth's rotation angular rate in the navigation system. After navigation, the latitude value and the local Earth rotation rate are updated in real time, and compensation is made for the Earth's angular rate.

5. The method according to claim 4, characterized in that, The method further includes: If the high-precision IMU solution module does not store the initial latitude value, the angular rate of the UAV is obtained to estimate the initial latitude. After static alignment, the attitude and heading are obtained and then converted into an attitude matrix; The projection of the Earth's rotational angular velocity vector onto the navigation coordinate system is calculated using the following formula: ； Where N, E, and D represent the north, east, and ground directions of the navigation coordinate system, respectively. This is the projection of the Earth's rotational angular velocity vector onto the navigation coordinate system. The angular velocity of Earth's rotation. , where is the Earth's rotational angular velocity, and e represents the Earth system. The projection of the three-axis angular rate measurement of the machine body measured by the gyroscope onto the machine system, where b represents the machine system, i represents the inertial frame, and ib represents the rotation of the machine system relative to the inertial frame. In the stationary state, the output of the high-precision gyroscope is approximately the measured value of the Earth's rotation angular rate. The formula for projecting the Earth's rotational angular velocity vector into the local navigation coordinate system is also: ； in, Latitude , where is the Earth's rotational angular velocity, e represents the Earth system, i represents the inertial frame, and N, E, and D represent the north, east, and ground directions of the navigation coordinate system, respectively. This is the projection of the Earth's rotational angular velocity vector onto the navigation coordinate system; Among them, based on the projection formula of the Earth's rotation angular velocity vector in the local navigation coordinate system and the projection of the Earth's rotation angular velocity vector in the navigation coordinate system, the core equation for calculating latitude from gyroscope measurements is as follows: ； The method further includes: calculating the latitude based on the gyroscope measurement values ​​and determining the carrier angular rate compensation to obtain more accurate attitude and heading information; The following formula is used to obtain a more accurate attitude and heading solution: ； in, The compensated gyroscope measures the angular rate for attitude calculation, where n represents the navigation system and b represents the mechanical system. The projection of the three-axis angular rate measurements of the machine body, as measured by the gyroscope, onto the machine system. This is the projection of the Earth's rotational angular velocity vector onto the navigation coordinate system. Let e ​​represent the positional velocity of the carrier, and let e represent the Earth system, which is caused by the carrier's motion around the Earth.

6. The method according to claim 1, characterized in that, The latitude estimate is updated using the following formula based on the initial latitude value, the UAV's northward velocity, the meridian curvature radius, and altitude: ； in, Let h be the radius of curvature of the meridian, and h be the height. This is the current latitude estimate. Here, m represents the latitude value at the previous moment. Update the time step for IMU. Northbound speed, with subscript N indicating northbound and superscript n indicating navigation system.

7. The method according to claim 1, characterized in that, The method further includes: If the accuracy and signal of the current GNSS module meet the navigation requirements, then obtain the heading angle output by the dual antennas; Control the visual data processing module to calculate the initial heading angle; Calculate the rotation offset based on the initial heading angle and the heading angle output by the dual antennas; The visual coordinate system of the visual data processing module is rotated by the rotation offset to align the visual coordinate system of the visual data processing module with the navigation system.

8. The method according to claim 7, characterized in that, The method further includes: The alignment accuracy of the IMU heading is higher than that of the GNSS heading. If the IMU heading accuracy is higher than the GNSS heading accuracy, then the IMU heading accuracy is used instead of the dual-antenna heading accuracy.

9. The method according to claim 1, characterized in that, The method further includes: Perform pure inertial navigation; Based on GNSS signal strength, the autonomous switching mechanism determines the optimal fusion module according to sensor availability and quality; The optimal navigation solution is obtained from the EKF fusion module, and navigation results containing position, attitude, and velocity information are output at a fixed frequency. Among them, the pure inertial navigation mode includes: Continuously receive IMU data; Attitude, velocity, and position are calculated in the INS solution module; Output preliminary navigation results.

10. The method according to claim 9, characterized in that, The fusion module includes: GNSS / INS combined mode and visual / INS combined mode; When the fusion module is in GNSS / INS combined mode, the following steps are performed: Receive GNSS positioning data; The results are fused with the INS solution in the EKF fusion module; When the fusion module is in vision / INS combined mode, the following steps are performed: The camera module acquires image data; Visual odometry calculates relative motion; The results are fused with the INS solution in the EKF fusion module.

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