1170 results about "Inertial navigation system" patented technology

The invention discloses a hemispherical resonator gyroscope inertial navigation system error online calibration method, device and system and a readable storage medium. The method comprises the following steps: establishing a dynamic observation equation of a gain error and a misalignment angle error; adaptively extracting error features of different time scales, and constructing a high-dimensional feature vector; decoupling the gain error and the misalignment angle error to obtain an error estimation value; constructing a dynamic compensation matrix, and correcting and measuring the angular velocity in real time; an online self-correction mechanism of the error compensation model is designed, and a compensation matrix is dynamically adjusted to adapt to dynamic changes of errors; an adaptive time sequence regression model is introduced to predict an error long-term drift trend, and a nonlinear compensation method is combined to actively counteract an error accumulation effect; dynamically adjusting the optimization rate of the compensation matrix through stability analysis; and dynamically optimizing error model parameters based on convergence evaluation of error residual errors. According to the invention, the limitation of a traditional method in a dynamic environment, especially the coupling problem of a gain error and a misalignment angle error, is solved.

The invention discloses a multi-sensor fusion positioning mapping and thermal imaging device and a computer readable medium. The equipment integrates positioning mapping sensors such as a thermal imaging camera, a visible light camera, a laser radar and an inertial navigation system, and is specially designed for high-risk and complex fire emergency environments. Through an end-cloud integrated cluster cooperation system and a multi-link stable transmission technology and in combination with intelligent decision support, high-precision real-time positioning and dynamic 3D temperature measurement mapping can be realized in an environment in which satellite navigation signals are weak or unavailable. The multi-mode portability and environmental adaptability design of the system ensures the high efficiency and safety of an operator / unmanned system under extreme conditions, and the advanced data processing and analysis technology of the system significantly improves the accuracy and response speed of rescue operation. Due to the innovative characteristics, the method has remarkable practical application value and market prospect in the field of fire-fighting emergency rescue.

The invention discloses a tunneling equipment position calibration method and system adopting a cursor frame, and relates to the technical field of coal mine tunnel construction tagging. Geologic feature data in a coal mine tunnel are collected in real time through a dynamic environment data set, an environment adaptability index Szp is calculated, and the influence of the environment on equipment calibration is evaluated; a calibration error evaluation coefficient Gz and an error growth trend value Wczs are combined, a calibration strategy is dynamically optimized, adaptive filtering and a multi-modal fusion algorithm are adopted to improve positioning precision, and stable work in an environment with large geological change is ensured; meanwhile, calibration parameters are adjusted in real time by using a deep learning model and a self-adaptive path calibration algorithm, and the adaptability to complex geological conditions is enhanced; the interference compensation module processes electromagnetic interference through Kalman filtering, particle filtering and other algorithms, optimizes the error coefficient Ins of the inertial navigation system, corrects the deviation of the sensor, reduces the influence of external interference on the calibration precision, and guarantees the high precision and stability of the system.

The invention discloses a multimode GNSS / inertia tight combination factor graph optimization method based on variance component estimation, and belongs to the technical field of satellite / inertia combination navigation. The implementation method comprises the following steps: fusing observed quantities of a multimode GNSS and an inertial navigation system on the basis of a factor graph optimization method under the condition of distributing prior weights among multiple GNSS systems; on the basis of a posteriori state estimation result obtained after factor graph optimization, combining a multi-mode GNSS observation equation, calculating a posteriori residual error, and utilizing a variance component estimation method to adaptively adjust weights among the multiple GNSS systems in real time according to the signal quality of satellites of the satellite navigation systems; on the basis of gross error detection and a weight reduction algorithm, weight reduction processing is carried out on the satellite observed quantity containing gross errors before the weight between the systems is adjusted in a self-adaptive mode. According to the invention, the robust variance component estimation is used to determine the weight among multiple GNSS systems, the reliability of satellite observation information of different satellite navigation systems is adjusted in real time, and the precision and robustness of the multimode GNSS / inertial tight integration navigation system are improved.

The invention discloses a vehicle positioning method and system based on UWB and vehicle constraint, and relates to the field of vehicle positioning, and the method comprises the steps: deploying a UWB reference station in a well mining environment, and enabling a vehicle to be provided with a UWB tag; obtaining distance measurement data of at least two UWB reference stations, and detecting and compensating the distance measurement data to obtain a vehicle UWB position; collecting vehicle-mounted IMU (Inertial Measurement Unit) data, and obtaining a vehicle attitude quaternion through attitude calculation; collecting vehicle wheel speed meter data, and correcting the vehicle wheel speed meter data according to vehicle motion constraint conditions; according to the vehicle UWB position, the vehicle attitude quaternion and the corrected vehicle wheel speed meter data, the vehicle position is obtained through an adaptive Kalman filtering fusion algorithm. Aiming at low positioning precision caused by easy accumulation of errors and drifting of a traditional inertial navigation system in a well mine closed space in the prior art, the invention reduces the influence of a multipath effect in the traditional inertial navigation system on the positioning precision.

The invention provides a satellite navigation and atmosphere fusion positioning method and system based on an inertial navigation system, and relates to the field of navigation. The method comprises the following steps: firstly, acquiring multi-source navigation original data, including inertial navigation data, satellite navigation data and atmosphere information data; performing feature extraction through deep learning to obtain multi-modal feature data; and performing quality evaluation on the satellite navigation data, and judging whether the satellite navigation signal is effective or not. When the satellite navigation signal is effective, carrying out combined navigation calculation by adopting a federated filtering algorithm, and establishing an atmospheric information error model; and when the satellite navigation signal is invalid, the error model is utilized to compensate the atmosphere information, and is fused with inertial navigation data, so that high-precision navigation is realized, and the flight safety of the unmanned aerial vehicle in a complex environment is guaranteed.

The invention relates to the technical field of communication, in particular to an airborne Tiantong phased-array antenna and an application method thereof. According to the method, phased-array antenna beams are driven to perform electronic scanning according to a geometric azimuth angle, beacon signal blind acquisition is performed in a preset airspace in a wide beam mode, and when an initial signal is detected, the mode is immediately switched to a narrow beam scanning mode; dynamically adjusting a phase weighting coefficient to realize pointing adjustment, so that a signal quality parameter is continuously converged in an optimal threshold interval; carrying aircraft maneuvering acceleration feedback is introduced, beam pointing offset is dynamically compensated based on a pre-constructed interference feature library, and signal fluctuation caused by a multipath effect is suppressed; and continuously checking a data validity flag bit of the main inertial navigation system, seamlessly switching to an antenna built-in inertial navigation data stream when a failure threshold is triggered, and activating a rapid recapture program to maintain zero interruption of a communication link. Through dual-source inertial navigation data fusion and intelligent beam control, rapid and accurate tracking of Tiantong satellites in an airborne environment is realized.

The invention relates to the technical field of unmanned aerial vehicle control, in particular to an unmanned aerial vehicle self-adaptive navigation system which comprises an inertial navigation system, a visible light sensor, a data fusion module, a database and a navigation control module. The inertial navigation system provides attitude, speed and acceleration data; the visible light sensor collects an image and obtains environment feature points through deep learning algorithm processing to realize visual positioning; and the data fusion module fuses two kinds of sensor data by using a dynamic weighted Kalman filtering algorithm, and dynamically adjusts the weight according to the environment to optimize the positioning information. The map library and the feature library store environment data to assist in positioning and dynamically update; the navigation control module generates an instruction according to the fused positioning information, and automatically adjusts a flight strategy by considering various factors based on an adaptive control algorithm. The system improves the positioning precision and environmental adaptability, enhances the flight safety and stability, is high in intelligence and autonomy degree, has flexibility and expandability, and can be widely applied to the field of unmanned aerial vehicles.

The invention relates to the technical field of calibration test, and particularly discloses a strapdown inertial navigation automatic calibration test method of a temperature control biaxial rate position turntable. Comprising the following steps: S1, multi-dimensional error modeling and layered calibration architecture: constructing a comprehensive error model containing a sensor scale factor error, an installation non-orthogonal error, a zero offset error, a cross axis coupling error and a temperature related error; s2, a wide temperature range self-adaptive compensation mechanism: carrying out heat preservation at a preset temperature point and executing turntable positioning and rate movement; s3, performing automatic data processing and parameter estimation; and S4, performing real-time error correction and dynamic verification: performing real-time error correction based on the estimated parameters, and evaluating navigation performance indexes such as position, speed and attitude precision. Through technical innovation, high-precision, automatic and wide-temperature-range calibration of the strapdown inertial navigation system is realized, and the method is suitable for aerospace, intelligent equipment and other scenes with strict navigation precision requirements, and has remarkable engineering application value and market competitiveness.

The invention relates to the technical field of underwater intelligent navigation and integrated navigation, in particular to a submersible integrated navigation multi-source data fusion method based on an elastic random model, which comprises the following steps: preprocessing multi-source navigation data output by an inertial navigation system (INS), a Doppler velocimeter, an ultra-short baseline / long baseline, an altimeter and a depthometer; constructing a state space model containing navigation parameter errors and sensor errors, and screening an optimal sensor combination mode; the method comprises the following steps: constructing an elastic correction parameter model and a dynamic adjustment state and observation noise covariance matrix by combining an elastic PNT framework, performing local filtering on multi-source data by adopting a plurality of parallel elastic self-adaptive robust volume Kalman filters (CKF), outputting a fusion resolving result, and realizing optimal estimation of a global navigation state through a dynamic information distribution strategy. The method has relatively high anti-interference performance, self-adaptive capability and combination switching robustness, and is suitable for navigation and positioning tasks of a high-precision submersible in a complex underwater environment.

The invention focuses on enhancing indoor positioning and navigation through advanced synchronous fusion methodologies that integrate various technologies, including Inertial Navigation Systems (INS), Inertial Measurement Units (IMU), LiDAR, stereo vision, and Sonar. This comprehensive system aims to achieve high-precision data collection with centimeter-level accuracy, crucial for creating detailed three-dimensional indoor maps. A significant aspect of this innovation is its ability to address privacy concerns by incorporating measures that abstract sensitive segments of the environment when necessary, ensuring personal privacy is maintained during data collection. Additionally, the system tackles challenges such as voids in stereo imaging and temperature variations in ultrasound and LiDAR measurements through sophisticated algorithms and corrections, including back propagation techniques that utilize stereo depth data. By employing particle swarm optimization and Neuro-Fuzzy algorithms, the framework enhances the accuracy and reliability of navigation in complex environments, making it particularly beneficial for emergency responders and personal navigation in unfamiliar settings.

The invention provides an unmanned aerial vehicle obstacle avoidance method and system based on inertial navigation, and belongs to the technical field of unmanned aerial vehicle obstacle avoidance systems. The problem that an existing unmanned aerial vehicle is insufficient in obstacle avoidance capacity under the environment that GPS signals are weak, vision is limited or a sensor detection blind area exists is solved. Acquiring broadband high-frequency dynamic response data output by the inertial navigation system of the unmanned aerial vehicle in real time; establishing or acquiring a reference high-frequency dynamic response model when the unmanned aerial vehicle is in a specific flight state and a power system working mode and is not influenced by an external obstacle; the signal is dynamically responded according to high frequency; identifying whether a specific air medium disturbance echo feature formed by disturbance generated by motion of the unmanned aerial vehicle through an external obstacle exists or not; and finally, generating and executing an obstacle avoidance flight instruction according to the estimation information. The method does not depend on a traditional external environment sensor for initial detection, physical interaction is sensed through the INS, and the autonomous obstacle avoidance capacity and safety of the unmanned aerial vehicle in the complex and challenging environment are improved.

The invention relates to the technical field of communication engineering, in particular to a communication optical cable line intelligent inspection fault point rapid positioning method and device, and the method comprises the steps: obtaining optical cable line state data, constructing an intelligent fault detection model, recognizing an abnormal signal through wavelet transform and a threshold determination method, training an LSTM neural network in combination with historical fault data, and pre-judging a fault type. When a fault is detected, an unmanned aerial vehicle inspection unit is triggered, an inspection path is planned based on an improved Dijkstra algorithm according to the fault type and suspected fault area geographic information, an optical cable line is scanned and detected through a laser radar, physical fault features are recognized through a YOLOv5 algorithm, and geographic coordinates of a fault point are calibrated in combination with an inertial navigation system; and fusing sensor data and a detection result, evaluating a fault confidence level by adopting a DS evidence theory, and generating an alarm work order. Therefore, the problems of long positioning time consumption, high omission ratio, difficulty in distinguishing fault types and the like in the prior art are solved.

The invention relates to the technical field of underwater navigation, and discloses a real-time attitude estimation method of an underwater inertial navigation system. The method comprises the steps that the underwater vehicle collects multi-axis angular velocity and linear acceleration data through an inertial measurement unit and uploads the data to a central processing module, and the central processing module conducts kinematics modeling on the data to generate attitude change initial feature vectors; receiving water flow velocity data of a Doppler velocimeter and pressure data of a depth sensor, and performing flow field interference compensation optimization on the attitude change initial feature vector based on the data to generate an anti-interference attitude feature vector; fusing the anti-interference attitude feature vector and a historical attitude estimation result to generate space-time fusion attitude state representation, and then resolving a real-time Euler angle through a nonlinear filter; and matching a corresponding attitude stability control instruction from the navigation strategy library according to the real-time Euler angle, and issuing the attitude stability control instruction to a propeller execution unit. The method can effectively cope with underwater complex environment interference and guarantee stable operation of the underwater vehicle.

The invention provides an intelligent road crack detection method, and belongs to the technical field of electrical digital data processing.The intelligent road crack detection method comprises the steps that firstly, a line structured light scanner is adopted to obtain road surface point cloud data, and attitude compensation processing is conducted in combination with an inertial navigation system; then noise is eliminated through bidirectional moving average filtering, and the depth matrix is converted into an image and segmented; gaussian background modeling is used to screen abnormal points, a connected graph is constructed through a minimum spanning tree algorithm, and pruning is carried out to obtain a crack skeleton; using a feature enhancement function to optimize the crack saliency; and finally, inputting a pre-trained multi-scale pavement damage identification network, and outputting a crack identification result and classification. According to the method, three-dimensional point cloud data, geometric feature analysis and a deep learning technology are fused, the technical problem of poor adaptability of a complex pavement environment is solved, and accurate identification of various crack types is realized.

The invention provides a visual navigation method and system based on an improved optical flow method, and relates to the technical field of computer vision and inertial navigation. A collaborative optimization framework of an inertial navigation system and visual feature navigation is constructed, carrier motion state parameters are obtained through dead reckoning of an inertial measurement unit, variance parameters of pose variation are calculated, and the layering depth of a pyramid LK optical flow method is dynamically adjusted based on the variance parameters. When the inertial navigation output variance exceeds a preset threshold value, the number of layers of an image pyramid is increased to cope with large-range motion, and otherwise, calculation levels are reduced to improve real-time performance. A dual-period optical flow / feature matching tracking mechanism is designed, improved sub-pixel-level optical flow tracking is adopted in a short period, the calculation complexity is reduced while the positioning precision is guaranteed, feature matching is switched to in a long period, accumulative errors are eliminated, and a period parameter N is determined by inertial navigation precision. According to the method, the calculation complexity can be reduced, and a better effect can be achieved on a low-calculation-performance platform.

The embodiment of the invention discloses an agricultural vehicle positioning method and device, electronic equipment and a storage medium, and the method comprises the steps: determining the posture, position and speed of an agricultural vehicle under a geographic coordinate system according to inertial navigation data obtained by an inertial navigation system; establishing an initial observation equation according to a satellite observation equation corresponding to a global satellite positioning system and a visual observation equation corresponding to a visual sensor; when it is detected that satellite data collected by a global satellite positioning system is valid, the initial observation equation serves as a target observation equation; when it is detected that the satellite data collected by the global satellite positioning system is invalid, the initial observation equation with the satellite observation equations removed serves as a target observation equation; the current error state quantity of the inertial navigation system is corrected according to the target observation equation, and the attitude, position and speed of the agricultural vehicle are corrected according to the updated error state quantity, so that the actual positioning information of the agricultural vehicle is obtained, and the robustness of the positioning result of the agricultural vehicle is improved.

Disclosed in the present invention are a multi-source aviation remote sensing data acquisition apparatus, system and control method, which are applied to the technical field of aerial survey remote sensing. The apparatus comprises: a flight platform and an airborne device disposed on the flight platform. The airborne device comprises: a multi-sensor ultra-compact integrated device, an airborne integrated synchronization control device, and a GNSS receiving antenna. The multi-sensor ultra-compact integrated device and the airborne integrated synchronization control device are connected by means of cables, and the GNSS receiving antenna is disposed on an upper end face of the flight platform. The multi-sensor ultra-compact integrated device is used for acquiring multi-source remote sensing data; and the airborne integrated synchronization control device is used for controlling the operation of the multi-sensor ultra-compact integrated device. The present invention ultra-compactly integrates a LiDAR, a hyperspectral camera, a thermal infrared camera, and a visible-light camera on the basis of a high-precision inertial navigation system, and achieves efficient synchronous acquisition of texture, spectral, temperature, and geometric information by means of using an integrated control subsystem.

The invention discloses a GNSS (Global Navigation Satellite System) / inertial navigation tightly integrated navigation method and system based on robust auto-velocity constraint factor graph optimization, and the method specifically comprises the following steps: extracting pseudo-range and Doppler observation data from original observation information of a GNSS satellite, and obtaining accelerometer and gyroscope data from an INS (Inertial Navigation System); constructing a pseudo-range residual block, a Doppler residual block, an inertial navigation pre-integration residual block and a speed constraint factor, and integrating into a sliding window estimator based on factor graph optimization; according to the size of a set sliding window, adding all residual blocks in the window to form an optimized objective function; performing a first round of factor graph optimization to obtain a preliminary state estimation result, and endowing the observed quantity containing gross error with a relatively low weight; and updating the prior weight matrix, and carrying out second round of optimization to obtain a joint optimal estimation result of a plurality of moment states in the current time window. According to the method, the influence of gross error-containing observation information on weight estimation and state estimation is suppressed, the positioning precision is high, the robustness is strong, and the reliability is high.

The invention provides a water surface target grabbing system and a control method thereof, and relates to the technical field of marine operation equipment. The system comprises an unmanned ship and a cooperative mechanical arm, the unmanned ship and the cooperative mechanical arm share a processor; the unmanned ship supplies power to the cooperative mechanical arm; the unmanned ship is positioned through an inertial navigation system on the unmanned ship and a scene camera and a depth camera on the cooperative mechanical arm; a scene camera, a depth camera and an integrated sensor on the cooperative mechanical arm transmit data to a processor on the unmanned ship through a local area network, the processor calculates and analyzes the data transmitted by the scene camera and the depth camera, and an action instruction is sent to the cooperative mechanical arm through a CAN bus. According to the water surface target grabbing system, automatic grabbing is achieved, and the grabbing precision, stability and adaptability of the system in the dynamic marine environment are improved.

The invention discloses a missile erection filtering method, system and device and a readable storage medium, and relates to the technical field of inertial navigation and the field of initial alignment. Based on the reference inertial unit pitch angle before erection, the reference inertial unit pitch angle at the current moment, the inertial unit angular velocity on the missile and the trajectory launching inclination angle, whether the missile is in any one of the non-target states of the non-erection state, the just erection state, the to-be-erected in-place state and the erection completion state or not is judged; if yes, measurement updating is not carried out in the Kalman filtering calculation process of the current moment, and time updating is carried out based on the state transition matrix of the current moment, the state vector of the previous moment, the mean square error matrix of the previous moment and the process noise variance matrix; and attitude information output by the inertial navigation system at the current moment is used as a missile attitude result for calculation at the next moment. According to the method, shaking between the guided missile and the launching box in the erecting process before launching is considered, and the attitude precision of initial alignment of the guided missile is improved.

The invention discloses a vehicle-mounted laser gas pollution detection and prediction system, which comprises a mobile laser detection platform, a machine prediction system and a dynamic pollution map generation system, and is characterized in that the mobile laser detection platform is carried on a new energy vehicle and is integrated with a laser gas detector, a high-precision positioning module, an inertial navigation system and an environment sensor group; the machine prediction system receives real-time traffic flow data, weather forecast data and topographic data and outputs a pollution diffusion prediction result; the dynamic pollution map generation system comprises a space-time synchronization module, a data fusion module and a pollution event marking module. And the space-time synchronization module binds the gas pollution data with the positioning coordinates and the millisecond timestamp through hardware clock synchronization.

The invention discloses a hemispherical resonator gyroscope inertial navigation system temperature compensation method and compensation system, and the method comprises the steps: constructing a dynamic temperature space model, and achieving temperature drift characteristic modeling; designing an incremental adaptive neural network structure to enable the compensation model to adapt to the temperature change, and optimizing the compensation precision through a successive approximation incremental learning mode; temperature compensation and increment optimization are carried out in real time through combination of a dynamic temperature space model and an increment adaptive neural network, and compensation precision is maintained through dynamic updating of a temperature space and an increment learning mechanism of the increment adaptive neural network; output signal drift and compensation errors are monitored through a self-adaptive feedback mechanism, a dynamic temperature space model and incremental self-adaptive neural network parameters are dynamically adjusted, and the stability and the compensation effect are improved through an online correction and model self-optimization mechanism. According to the method, the problems of insufficient temperature drift modeling precision, poor adaptability and compensation precision attenuation after long-time operation in a traditional compensation method are solved.

The invention relates to the technical field of vehicle navigation and path planning, and provides a marine inertial navigation path planning method and system, and the method comprises the steps: obtaining environment risk information of a path corresponding to the driving direction of an autonomous underwater vehicle; adjusting a deviation tolerance threshold value corresponding to an inertial navigation system on the autonomous underwater vehicle according to the environmental risk information; acquiring a position calculation deviation of the inertial navigation system; the position calculation deviation is compared with a deviation tolerance threshold value, and triggering of a communication correction action is decided according to the backlog condition of the emergency event data; and when the communication correction action is triggered, planning and executing a communication correction track to realize position correction of the autonomous underwater vehicle. The method has the advantages that the navigation strategy is dynamically adjusted according to the environment risk and the data backlog condition, the communication correction opportunity is intelligently decided, and the autonomous navigation capability and the task adaptability of the autonomous underwater vehicle in the complex marine environment are improved.

The invention relates to the technical field of intelligent driving, and provides a vehicle control decision-making method and device based on the perceptual fusion technology and electronic device.The vehicle control decision-making method based on the perceptual fusion technology comprises the steps that first positioning information of a vehicle is obtained through data fusion of at least two complementary sensors, the complementary sensor comprises an inertial navigation system, a visual odometer and a laser radar odometer or odometer; correcting the first positioning information through a roadside assisted positioning technology to obtain second positioning information; state information of a target vehicle is acquired through a cellular Internet of Vehicles communication technology; fusing the environment sensing data collected by the vehicle-mounted sensor and the roadside equipment of the vehicle and the state information of the target vehicle, and constructing a global environment model; and making a control decision based on the second positioning information and the global environment model to realize safe vehicle distance keeping and collision avoidance. The method improves the perception, decision and control capabilities of the vehicle.

The invention discloses a combined navigation method and system of an unmanned surface vehicle. The method comprises the following steps: forming a GNSS (Global Navigation Satellite System) / INS (Inertial Navigation System) integrated navigation system by using a GNSS (Global Navigation Satellite System) and a strapdown inertial navigation system (INS), and establishing a mathematical model of a GNSS / INS integrated navigation system filter; the mathematical model comprises a state equation and a measurement equation; establishing a mathematical model of the influence of the GNSS auxiliary information on the GNSS positioning precision so as to preliminarily adjust the measurement noise in the measurement equation; through an improved Sage-Husa adaptive filtering algorithm, adaptive estimation is carried out on the preliminarily adjusted measurement noise, and a measurement noise estimation final value is obtained; and according to the motion characteristics of the unmanned surface vehicle, adding motion constraint conditions to the measurement equation. The GNSS auxiliary information mathematical model based on multivariate function fitting is established, the influence of the external environment on the positioning precision is objectively reflected, the measurement noise in the filter is dynamically adjusted, and the positioning precision of the integrated navigation system under the interference condition is remarkably improved.

The invention provides a comprehensive test bench for an aircraft system, and relates to the technical field of equipment testing. Platform function support is provided through the simulation flight system, the comprehensive control and test auxiliary system, the data acquisition analysis system, the software test system, the airborne system integration module and the fault injection system. Through a platform I / O resource pool, a simulation power supply and distribution system, a test network, a reflection memory network and a wiring and tandem system, different aircraft system test benches are cooperated to carry out a linkage comprehensive experiment. According to the invention, the building of the aircraft system comprehensive test bench is realized among the power device system test bench, the atmospheric inertial navigation system test bench, the passenger cabin information system test bench, the copper bird test bench and the iron bird test bench, so that the linkage test operation requirement is met.

The invention relates to the technical field of flight control, in particular to a hybrid control FPV unmanned aerial vehicle flight control system and method. The method comprises the following steps: acquiring triaxial angular velocity data of the unmanned aerial vehicle in real time by using an inertial navigation system, eliminating high-frequency noise and performing zero offset calibration; constructing a corresponding linear extended state observer to adjust a gain parameter in real time based on an absolute value of an observation error, and filtering tiny noise disturbance through a dead zone function to realize high-precision estimation of the system state and total disturbance of the unmanned aerial vehicle so as to obtain an error and an error change rate; and designing a self-adaptive PID control law to dynamically adjust PID control quantities corresponding to proportion, integral and differential gains, carrying out dynamic weighted stacking according to a flight mode, generating a three-axis control quantity, carrying out flight control on the FPV unmanned aerial vehicle, and meanwhile, realizing real-time visual verification of a control effect corresponding to the flight control. According to the invention, high-precision and high-robustness attitude control can be realized.

The invention relates to a CNN-GRU-MHSA navigation method and a CNN-GRU-MHSA navigation system for improving pseudo measurement noise covariance under GNSS interruption. Comprising the following steps of: combining three-dimensional output of a gyroscope and three-dimensional output of an accelerometer in an IMU (Inertial Measurement Unit) in a GNSS (Global Navigation Satellite System) observation period as well as a three-dimensional speed and a three-dimensional course angle calculated by an INS (Inertial Navigation System) into an input vector, inputting the input vector into a trained CNN-GRU-MHSA (Global Navigation Satellite System) hybrid neural network, and outputting to obtain a pseudo GNSS position increment in the GNSS observation period. And synthesizing the pseudo GNSS position increment and the GNSS position information of the previous epoch to obtain pseudo GNSS position information of the current epoch. And then, adding an accumulated error compensation factor related to time into Sage-husa adaptive filtering to estimate a pseudo measurement noise covariance matrix. And finally, transmitting the pseudo GNSS position information and the pseudo measurement noise covariance matrix into an integrated navigation Kalman filter for resolving so as to correct an INS navigation resolving result.

The invention relates to the technical field of angle measurement, in particular to a well deviation angle measurement method and system based on inertial navigation. The method comprises the following steps: carrying out equipment underground operation real-time monitoring and inertial state Kalman filtering processing on the operation process of the drilling equipment to obtain inertial state triaxial acceleration filtering data and inertial state triaxial angular velocity filtering data; performing three-axis attitude angle integral operation and three-axis attitude space conversion on the inertial state three-axis acceleration filtering data and the inertial state three-axis angular velocity filtering data to generate an inertial state three-axis attitude angle simulation space; the method comprises the following steps: acquiring an initial reference point of underground inertial navigation, carrying out three-axis attitude geometric mining analysis and well deviation angle inverse solution calculation, and carrying out error compensation derivation calculation and well deviation calibration treatment on corresponding sensor output in an underground inertial navigation system to obtain an inertial navigation well deviation calibration angle. According to the invention, the real-time and accurate measurement process of the well inclination angle can be realized.