28 results about "Transfer alignment" patented technology

The invention relates to the field of inertial navigation alignment, and discloses a self-adaptive transfer alignment method based on resonance inertial navigation, which comprises the following steps: acquiring speed and angular speed information of main and sub inertial navigation; time integral values of the speed difference value and the angular speed difference value are jointly used as observed quantities to suppress deflection deformation interference; constructing an adaptive Kalman filter, updating and measuring a noise covariance matrix in real time based on an innovation sequence so as to adapt to noise time-varying characteristics introduced by integral observation, and accurately estimating a system state error; in the alignment process, the vibration mode angle of the resonant gyroscope is actively controlled in different periods according to a preset strategy, the integral value of the resonant gyroscope in the whole alignment period is close to zero by utilizing the periodic relationship between symmetric drift and the vibration mode angle, and key accumulative errors are eliminated from a physical source. Through the collaborative design of the observation model, adaptive filtering and active physical control, the transfer alignment precision, stability and adaptive ability in a dynamic environment are significantly improved.

The invention discloses a transfer alignment method and transfer alignment equipment based on a Lie group left invariant error model, and belongs to the field of inertial navigation systems. The method comprises the following steps: firstly, establishing a left invariant error state model between a master inertial navigation system and a slave inertial navigation system based on the Lie group theory; secondly, constructing an attitude and speed error differential equation considering the lever arm effect and the installation error angle influence at the same time, then selecting attitude and speed measurement defined under the Lie group, and establishing a corresponding measurement equation; and finally, designing an unscented Kalman filter according to the nonlinear state equation and the measurement equation, and carrying out joint estimation on parameters such as a misalignment angle, a speed error, a lever arm vector, an installation error angle and inertial navigation zero offset. The transfer alignment method provided by the invention not only fully considers the actual lever arm error between the main inertial navigation system and the sub inertial navigation system, improves the integrity of system error modeling, but also adopts the local navigation coordinate system as the reference coordinate system, is closer to the actual engineering requirements, and has good universality and engineering application prospects.

The invention particularly relates to a model-free deflection angle estimation method based on a radial basis function neural network. The method comprises the following steps: acquiring measurement data of a master inertial navigation system and a slave inertial navigation system; based on the distribution characteristics of the measurement data in the training set, updating the clustering centers of the hidden layer radial basis function to obtain the number of the clustering centers; constructing a radial basis function neural network based on the measurement data of the training set and the number of the clustering centers, and training the radial basis function neural network by adopting a minimum mean square error algorithm to obtain a trained radial basis function neural network; and inputting measurement data in the test set into the trained radial basis function neural network to obtain a predicted deflection angle, performing calculation compensation on the pose amount of the master-slave inertial navigation system by combining a transfer alignment error equation according to the predicted deflection angle, and outputting a final alignment result based on a Kalman filtering model of a model-free deflection angle. The dynamic deformation angle modeling compensation method solves the problems that in an existing dynamic deformation angle modeling compensation method, model parameters are difficult to determine, and transfer alignment is caused when the parameters are time-varying.

The application discloses a fast transfer alignment method without singularity for any misalignment angle of precise air-drop inertial navigation device, which comprises the following steps: after the alignment starts, the on-board main inertial navigation device and the precise air-drop inertial navigation device respectively perform attitude updating in the inertial system, and real-time solve the attitude matrix and the inertial navigation sampling period; based on the angular velocity and the specific force measurement of the on-board main inertial navigation device and the precise air-drop inertial navigation device, a matching model of the angular velocity integral and the specific force integral in the inertial system is established; a Kalman filtering state equation is established, and the Kalman filtering time updating is completed; according to the obtained integral quantity, the state equation is combined to construct a measurement equation; the Kalman filtering measurement updating is completed; the attitude tracking error compensation of the precise air-drop inertial navigation device in the inertial system is completed; and the attitude matrix at the alignment end moment of the precise air-drop inertial navigation device is obtained. The method can quickly complete the transfer alignment under the simple circling maneuver of the carrier.

The present application relates to a kind of unmanned plane transfer alignment method based on relative installation error analytical expression model, belong to unmanned plane transfer alignment technical field, including the following steps: S1, the relative installation error analytical expression model between main inertial navigation system and sub inertial navigation system is constructed;S2, based on the relative installation error analytical expression model of step S1 construction, relative installation error is obtained;S3, using the relative installation error of step S2, initial self-alignment error is obtained;S4, based on the relative installation error and initial self-alignment error of step S3 acquisition, transfer alignment is carried out.The method provided by the present application is high in reliability, strong in universality, high in the running efficiency of algorithm, simple in operation, high in precision, and good in practicability.

The invention discloses a real-time dynamic parameter updating transfer alignment method, device and equipment, belongs to the technical field of inertial navigation systems, and particularly relates to transfer alignment of carriers such as airborne weapons and unmanned aerial vehicles in a mounting state dynamic change scene. The problems of static parameter hypothesis, historical data pollution and insufficient real-time performance existing in the current transfer alignment technology are solved; the method comprises the following steps: setting a sliding window starting interval; judging whether the mounting state suddenly changes or not; and updating the dynamic installation error angle in real time. The real-time dynamic parameter updating transfer alignment method, device and equipment are suitable for real-time navigation parameter transfer alignment of carriers such as airborne missiles (weapons) and unmanned aerial vehicles in high-speed maneuvering flight in a mounting state dynamic change scene.

The application discloses a non-singular linear transfer alignment method and system based on a relative attitude matrix, belongs to the technical field of inertial navigation systems, and particularly relates to transfer alignment technology. In view of the problems that existing transfer alignment methods are prone to model singularity and alignment precision reduction when facing large installation error angles or complex dynamic environments, the application proposes the following: a strapdown inertial navigation system carrier coordinate system is acquired to determine a main inertial navigation attitude matrix; a transfer alignment error model is established by using a relative attitude matrix based on the main inertial navigation attitude matrix; flexible rod arm state information is acquired to optimize the transfer alignment error model; and transfer alignment of the strapdown inertial navigation system is realized based on the optimized transfer alignment error model. The application significantly improves alignment precision by optimizing the transfer alignment error model, and can still maintain stable and reliable alignment results under large installation error angles or complex dynamic environments, thereby enhancing the robustness and accuracy of the transfer alignment model.

This invention discloses a transfer alignment method and device based on a left-invariant error model of Lie groups, belonging to the field of inertial navigation systems. The method first establishes a left-invariant error state model between the master and sub-inertial navigation systems based on Lie group theory; secondly, it constructs attitude and velocity error differential equations that simultaneously consider the effects of lever arm effects and installation error angles; then, it selects attitude and velocity measurements defined by the Lie group and establishes corresponding measurement equations; finally, it designs an unscented Kalman filter for the nonlinear state equations and measurement equations to jointly estimate parameters such as misalignment angle, velocity error, lever arm vector, installation error angle, and inertial navigation zero bias. The transfer alignment method proposed in this invention not only fully considers the actual lever arm errors between the master and sub-inertial navigation systems, improving the completeness of system error modeling, but also uses the local navigation coordinate system as the reference coordinate system, which is closer to actual engineering needs and has good versatility and engineering application prospects.

The application discloses a kind of based on main sub inertial navigation combined in-transit muzzle vibration measurement method, this method is: install high-precision inertial navigation on the high overload resistance on turret, install low-precision MEMS inertial navigation at the muzzle of barrel;In initial stage, high-precision main inertial navigation at turret and MEMS sub inertial navigation at muzzle complete transfer alignment;In transfer alignment stage, according to the dynamic modeling of outer lever arm error and deflection deformation according to the characteristics of gun barrel, compensate for lever arm effect and deflection deformation;Establish the transfer alignment Kalman filter of speed and attitude matching mode;In navigation update stage, sub inertial navigation uses the alignment error at the end of transfer alignment as the initial error of navigation solution, carries out navigation state update, completes the vibration measurement of muzzle.The application has the advantages of simple installation, high stability, strong anti-interference ability and high accuracy.

The invention relates to a ground-based aircraft launching alignment method which comprises the following steps: in the erecting process of a ground-based aircraft, updating a Kalman filter of a sub inertial measurement unit of the ground-based aircraft according to navigation parameters bound by a vehicle-mounted reference inertial measurement unit on a launcher, and correcting the navigation parameters of the sub inertial measurement unit; enabling the vehicle-mounted reference inertial measurement unit to carry out transfer alignment on the sub inertial measurement unit of the foundation aircraft; after erecting in place, taking a transfer alignment result of a sub inertial measurement unit of the foundation aircraft as an initial attitude at a launching moment, and initializing a Kalman filter at a flight stage; after the ground-based aircraft is launched, Kalman filtering integrated navigation is carried out by utilizing speed and position information provided by the loaded GNSS equipment, the attitude deviation of the sub inertial measurement unit of the ground-based aircraft is corrected, and when filtering estimation meets an estimation threshold value, alignment correction is completed. According to the method, rapidity and high precision are guaranteed, and the technical problem that a foundation aircraft cannot obtain high alignment precision in a short time in the prior art is solved.

The invention discloses an unmanned aerial vehicle navigation system and method in a high-dynamic throwing environment. The system comprises a mother inertial navigation system, a main inertial navigation system, a backup inertial navigation system, a satellite navigation module, a barometer, an extended Kalman filtering module and a complementary filter. The method comprises the following steps: carrying out transfer alignment on a main inertial navigation by a mother inertial navigation before throwing, judging whether the main inertial navigation exceeds a range after throwing, updating an extended Kalman filter by using a main inertial navigation attitude when the main inertial navigation does not exceed the range, carrying out attitude estimation by switching to a complementary filter based on a backup inertial navigation when the main inertial navigation does not exceed the range, and carrying out weighted fusion on double inertial navigation attitudes after the motion is stable. And finally, after the satellite signal is recovered, resetting the extended Kalman filter and injecting navigation data. According to the invention, continuous and reliable output of navigation information in a high-dynamic throwing process is realized, and adaptability and control stability of the unmanned aerial vehicle in an extreme environment are improved.

The application relates to the technical field of inertial navigation guiding systems, and discloses a method and device for transferring alignment of a large-angle installation error of an underwater micro inertial navigation system, which comprises the following steps: obtaining navigation information of a main inertial navigation system, and calculating analog data of a gyroscope and analog data of an accelerometer of the main inertial navigation system through an inversion algorithm; receiving gyroscope measurement data and accelerometer measurement data output by a micro inertial navigation system; combining the analog data of the gyroscope and the analog data of the accelerometer of the main inertial navigation system to construct a transfer alignment target function with installation error as a variable; and using an optimization algorithm to optimize the transfer alignment target function to obtain an estimated value of the installation error, so as to determine the installation error between the micro inertial navigation system and the high-precision inertial navigation system. The application does not depend on specific platform maneuvering, has high calculation efficiency and strong robustness, and can realize rapid and accurate alignment of a large installation error.

The invention discloses a transfer alignment method based on a Lie group right invariant error model, and belongs to the field of inertial navigation systems. The method comprises the following steps: firstly, referring to a navigation coordinate system, remodeling a right invariant attitude and a speed error based on the Lie group theory to replace a traditional transfer alignment error, incorporating sensor bias and a lever arm and mounting angle error between master and slave inertial navigation, and fully considering a transfer alignment error source; secondly, a system state equation is deduced again under the Lie group framework, and decoupling of calculation parameters and a system model is achieved; then, based on an attitude + speed measurement matching scheme, a system measurement equation is deduced again under a Lie group framework; and finally, aiming at the nonlinear characteristic of the measurement equation, combining with an unscented Kalman filter to accurately estimate the system state. According to the transfer alignment method provided by the invention, an error source objectively existing between the main inertial navigation system and the sub inertial navigation system is fully considered, system error modeling under a Lie group framework is perfected, and a system model is ensured to accurately reflect actual conditions.

The application discloses a transfer alignment method based on aircraft flight state detection, and steps of the method comprise the following steps: step S1: obtaining the flight state of an aircraft through an aircraft flight state detector according to the output of a main inertial navigation system and a sub-inertial navigation system; step S2: when the aircraft is in variable-speed flight, turning or oscillating-wing flight, a first Kalman filter is constructed through the main inertial navigation system and the sub-inertial navigation system to correct errors and estimate the installation error of the heading angle of the main inertial navigation system and the sub-inertial navigation system; when the aircraft is in uniform-speed flight, the installation error of the heading angle is directly used, and a second Kalman filter is constructed by using the output information of the main and sub-inertial navigation systems to correct errors and estimate the gyro zero offset. The application has the advantages of simple principle, high accuracy, fast alignment speed and the like.

Embodiments pertain to systems and / or methods for tracking, relative to a World Coordinate System and / or relative to a platform coordinate system, motion of an object that is movable within a platform by performing transfer alignment between an Inertial Navigation System (INS) of the platform, and an object-mounted Inertial Measurement Unit (IMU). In some examples, the systems are configured to perform, and / or methods comprise: determining, by the object-mounted IMU, IMU-based changing rates of the object relative to the World; determining, by a non-inertial tracker (NIT), NIT-based changing rates of the object relative to the platform, and determining a difference between: the IMU-based changing rates relative to the World; and the NIT-based changing rates relative to the platform, to obtain object-mounted IMU changing rates of the platform relative to the world.

The invention relates to the technical field of inertial navigation guidance systems, and discloses an underwater micro inertial navigation wide-angle installation error transfer alignment method and device, and the method comprises the following steps: obtaining navigation information of a main inertial navigation, and calculating through an inversion algorithm to obtain simulation data of a main inertial navigation gyroscope and simulation data of an accelerometer; receiving gyroscope measurement data and accelerometer measurement data output by the micro inertial navigation, and constructing a transfer alignment target function taking the installation error as a variable by combining the simulation data of the main inertial navigation gyroscope and the simulation data of the accelerometer; and optimizing the transfer alignment target function by adopting an optimization algorithm to obtain an estimated value of the installation error so as to determine the installation error between the micro inertial navigation system and the high-precision inertial navigation system. The method does not depend on specific platform maneuvering, is high in calculation efficiency and robustness, and can realize rapid and accurate alignment of large installation errors.

The invention discloses a photoelectric load transfer alignment and error dynamic compensation method, device and equipment, and belongs to the technical field of transfer error compensation. According to the method, collaborative modeling and an integrated compensation mechanism are carried out on multiple error sources, and large mounting angle alignment is optimized in combination with a virtual sub inertial navigation reference method. A dynamic environment adaptive alignment control strategy is realized, filtering parameters are optimized in real time according to flight states (such as acceleration and angular velocity), and alignment stability under complex electromagnetic interference is ensured. The transfer alignment technology is utilized to align the airborne photoelectric load system, so that the transfer alignment precision can be remarkably improved, accurate navigation and positioning are realized, and the execution efficiency of various tasks is enhanced. And meanwhile, the dependence on maneuvering characteristics and high-precision hardware is reduced, the cost is reduced, and the cost performance and the market competitiveness are improved. In addition, the application scene of the unmanned aerial vehicle is expanded, so that the unmanned aerial vehicle can reliably work in various complex environments, and multi-task requirements are met.

This invention belongs to the technical field of inertial navigation systems, specifically relating to a transfer alignment method based on Hough transform. The method includes the following steps: listing several parameter sets, transmitting acceleration and angular velocity readings, calculating the matching degree, determining whether coarse alignment is complete, relisting the parameter sets, transmitting acceleration and angular velocity readings, calculating the matching degree, and determining whether precise alignment is complete. This invention does not require a dedicated mathematical model of the inertial navigation system and can universally measure the installation angle and delay time of various inertial navigation systems to achieve transfer alignment. Its outstanding advantage is its good versatility.

The invention relates to a rapid high-precision transfer alignment method for a composite inertial system, and belongs to the technical field of initial attitude reference establishment of a movable base of a composite inertial navigation system with a rotating mechanism. According to the method, a high-order transfer alignment Kalman filtering model is constructed, high-precision estimation of a table body attitude misalignment angle of the composite inertial system is realized, meanwhile, an installation error and flexural deflection between a master inertial navigation and a slave inertial navigation are estimated and compensated, and the alignment performance is improved by fully utilizing a high-precision attitude reference; according to the invention, the problems of long alignment time and low precision of the existing composite inertial navigation in the aspect of transfer alignment of the movable base are solved; the method can be applied to the initial attitude reference establishment process of the moving base of a double-axis and three-axis composite inertial system, and has high rapidity and alignment precision.

The application provides a data-driven lever arm error compensation method, and belongs to the technical field of inertial navigation. The application is used for solving the problem that the time-varying equivalent lever arm cannot be directly measured in the inertial navigation of a submerged vehicle, and it is also difficult to accurately separate the lever arm induced error from other sensor errors. The application comprises the following steps: S1, analyzing and modeling the errors affecting transfer alignment; S2, establishing a lever arm error equation and a data-driven compensation model; and S3, velocity error prediction and compensation.

The application relates to the field of inertial navigation alignment, and discloses a self-adaptive transfer alignment method based on resonant inertial navigation, which comprises the following steps: acquiring speed and angular velocity information of main and sub inertial navigation; taking time integral values of speed difference and angular velocity difference as observation values to suppress flexural deformation interference; constructing an adaptive Kalman filter, and updating a measurement noise covariance matrix based on a new sequence to adapt to time-varying characteristics of noise introduced by integral observation and to accurately estimate system state error; and in the alignment process, actively controlling mode angles of resonant gyroscopes according to a preset strategy in time periods, and utilizing a periodic relationship between symmetrical drift and the mode angles to make integral values of the mode angles approach to zero in the whole alignment period, so that key cumulative errors are eliminated from a physical source. Through the collaborative design of an observation model, adaptive filtering and active physical control, the transfer alignment precision, stability and adaptive capacity in a dynamic environment are significantly improved.

The application relates to a high-precision transfer alignment method of an active isolation optical fiber platform and belongs to the technical field of inertial navigation. The application is based on an optical fiber platform system with a multi-axis rotating mechanism, the system can control the rotation of a platform body around a celestial axis to improve the observability of the system, meanwhile, the optical fiber platform can isolate the angular motion of a carrier in a space stable mode, and can keep stable relative to inertial space, so that the influence of external disturbance on the use precision of instruments can be eliminated or reduced. The application uses the speed and position information provided by high-precision master inertial navigation as a reference, adopts a speed+position matching mode, constructs a high-order transfer alignment Kalman filter model, realizes high-precision estimation of the attitude misalignment angle of the platform body of the optical fiber platform, estimates and compensates the zero offset error of the inertial instrument, and fully utilizes the stability of the instrument to improve the alignment performance. The application solves the problems of high requirement and low precision of the existing optical fiber platform inertial navigation in dynamic base transfer alignment.

The invention discloses a dynamic transfer alignment method suitable for attitude turnover, which comprises the following steps: receiving turnover state, working state of main inertial navigation, direction attitude of the main inertial navigation and speed information of the main inertial navigation after a sub inertial navigation is electrified, executing a transfer alignment process when the main inertial navigation finishes initial alignment and the working state is normal, otherwise, enabling the sub inertial navigation to be in a preparation state; compared with the prior art, the scheme can adapt to the influence of the overturning action of the sea-based sub inertial navigation on transfer alignment, and the zero offset of the gyroscope accelerometer is estimated by fully utilizing the overturning action, so that the alignment precision is improved.

The application relates to a high-precision initial alignment method, which comprises the following steps: a transfer alignment step: providing a main inertial navigation system and a sub-inertial navigation system, rotating 90 degrees around a horizontal axis to be erected, obtaining a first attitude matrix of the sub-inertial navigation system after the erection is completed through a transfer alignment algorithm, and completing azimuth fine alignment; a rotation modulation step: rotating the sub-inertial navigation system 180 degrees around the skyward axis to a symmetrical position and then rotating-180 degrees back to the original position for rotation modulation at the in-place position of the transfer alignment step, taking the first attitude matrix as an initial attitude, and obtaining a second attitude matrix of the sub-inertial navigation system to complete horizontal attitude fine alignment; and a fusion step: fusing an azimuth result of the first attitude matrix and a horizontal attitude result of the second attitude matrix to obtain a final attitude matrix to complete initial alignment. The application provides a high-precision initial alignment method which effectively combines the characteristics of rotation modulation alignment and transfer alignment and improves the initial alignment precision.

The application discloses a fixed-wing unmanned aerial vehicle falling body motion horizontal attitude estimation method, which comprises the following steps: step one, pre-processing the gyroscope and accelerometer data, converting the sensor data to the front-right-down body coordinate system and normalizing; step two, preliminarily judging the belly orientation according to the skyward accelerometer; step three, after starting the engine, using a maneuvering strategy to estimate the preliminary constant zero offset of the gyroscope and the accelerometer; and step four, according to the gyroscope and accelerometer data, using an improved adaptive extended Kalman filtering method based on quaternions to fuse the sensor data, further estimating the zero offset of the gyroscope and the accelerometer, and simultaneously obtaining the real-time estimation of the horizontal attitude angle. The application overcomes the shortcoming of the traditional transfer alignment method which has high requirements for the delivery carrier, can determine the opening time of the wings and the starting time of the engine during the delivery process of the fixed-wing unmanned aerial vehicle, and realizes the estimation task of the horizontal attitude and the online estimation of the sensor error.

The invention provides a high-latitude transfer alignment algorithm based on a factor graph, and belongs to the technical field of high-precision navigation. The invention aims to solve the problem that the traditional Kalman filtering method is difficult to deal with the strong nonlinearity and parameter coupling problem of high-dimensional regional navigation, so that the precision and robustness of transfer alignment are reduced. The method comprises the following steps: S1, modeling a high-latitude transfer alignment problem into a time sequence factor graph model; s2, calculating the posterior distribution probability of the system according to the time sequence factor graph model; s3, according to the posterior distribution probability, obtaining an error state estimation value of the sub inertial navigation relative to the main inertial navigation through maximum posterior estimation; and S4, correcting the navigation parameters of the sub inertial navigation according to the error state estimated value, and completing transfer alignment in the high-latitude environment.

The application discloses a kind of multi-source fusion pose measurement and collaborative positioning method and system for human-machine hybrid team. Specifically, error modeling and calibration compensation are carried out on inertial sensors and magnetometers, and secondary compensation is carried out on the nonlinear residual of accelerometer to suppress random noise;For individual node, an extended Kalman filter model is constructed and RSTKF is introduced to suppress motion mutation and measurement anomaly, and pedestrian dead reckoning is realized;Under the condition of human-machine team moving base, rigid body motion and flexural deformation interference are separated, and velocity and attitude matching is used to realize fast transfer alignment of master and slave inertial navigation;A master-slave architecture is constructed, and displacement vector and master-slave UWB ranging are used to construct collaborative measurement, and initial formation side length constraint and shape sub-filter are introduced and fused with federated filtering to realize high-precision collaborative positioning of slave node. The system includes sensor data processing module, single node pose solution module, transfer alignment module and collaborative positioning fusion module. The application reduces communication load and system cost, and improves the positioning accuracy and robustness of human-machine hybrid team.

This invention discloses a transfer alignment method based on a right-invariant error model using Lie groups, belonging to the field of inertial navigation systems. The method includes: first, referencing the navigation coordinate system, remodeling the right-invariant attitude and velocity errors based on Lie group theory to replace traditional transfer alignment errors, and incorporating sensor bias, lever arm and installation angle errors between the master and sub-inertial navigation systems to fully consider transfer alignment error sources; second, re-deriving the system state equations within the Lie group framework to decouple computational parameters from the system model; then, based on an "attitude + velocity" measurement matching scheme, re-deriving the system measurement equations within the Lie group framework; finally, addressing the nonlinear characteristics of the measurement equations, combining an unscented Kalman filter to accurately estimate the system state. The transfer alignment method proposed in this invention fully considers the objectively existing error sources between the master and sub-inertial navigation systems, improves system error modeling within the Lie group framework, and ensures that the system model accurately reflects the actual situation.