15 results about "Transfer alignment" patented technology

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.

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.

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 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 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 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.