106 results about "Position error" patented technology

The invention belongs to the technical field of aircraft design, and particularly relates to a static pressure source position error correction method, which comprises the following steps: performing theoretical appearance static pressure source position error correction analysis based on current numerical simulation and flight test state points to obtain a static pressure source pressure coefficient Cp, a flight test static pressure source pressure coefficient Cp0 and an actually measured static pressure source pressure coefficient Cp1; static pressure source position error correction data optimization is carried out, a static pressure source position error correction relation Cp'during real flight of the theoretical appearance is obtained, and static pressure source position error correction is carried out; appearance measurement, CFD simulation and test flight data comprehensive application are realized; correcting the position error of the static pressure source into a function of Mach number, angle of attack and height; and not only can the requirement of the CCAR25 part for the air pressure height be met, but also the requirement of RVSM operation in AC-21-13 for the error of a height measurement system can be met. The method can be used for atmospheric data correction of transportation aircrafts, and atmospheric data correction of other aircrafts can be used for reference.

The invention discloses a self-adaptive control method and system for a two-stage swing type rotor aircraft hoisting system, and the method comprises the steps: building a two-stage swing type rotor aircraft hoisting system dynamics model, taking the rotor aircraft hoisting system to simultaneously drive four rotors to reach an expected position and inhibit the swing of a lifting hook and a load as a control target, and carrying out the control of an outer ring, generalized lifting hook and load position signals are introduced, an energy storage function is constructed, and the energy storage function is dissipated through the generalized lifting hook and load position signals; the outer loop tracking error is converted into a generalized load position error, and a shaped total storage function is obtained; and designing an adaptive law to estimate the load mass online, obtaining a reconstruction energy function of outer ring control, further obtaining an outer ring controller, and realizing control of system displacement and a load swing angle. By adopting a generalized displacement method of the lifting hook and the load and reconstructing an energy storage function, the dynamic coupling characteristic among the four rotors, the lifting hook and the load is remarkably enhanced, and therefore the transient response characteristic of the system is effectively improved.

The invention discloses an air-drop and air-delivery large unmanned aerial vehicle ultra-low-altitude flight control system and method, and belongs to the field of flight control systems, and the system comprises a flight control module, a drop control module, an environment sensing module, a gravity center balance adjustment module and a data storage and interaction module. The flight control module is used for controlling the unmanned aerial vehicle to fly at an ultra-low altitude and ensuring that the flight attitude is stable, so that the position error is less than or equal to 10m, the height error is less than or equal to 2m and the flight path deviation is less than or equal to 10m when the unmanned aerial vehicle flies at the ultra-low altitude; the delivery control module is used for supporting a single delivery mode and a rapid continuous delivery mode, the maximum delivery of 1.2 tons of goods can be achieved, at most four pieces of goods can be delivered in a single flight, the delivery control module is compatible with parachute air delivery and non-parachute air delivery, and the delivery precision of the parachute air delivery at the high altitude of 300 meters is smaller than 100 meters. According to the invention, the unmanned aerial vehicle delivery precision can be improved, the stability is high, and material waste or incapability of accurately delivering to a target area is avoided.

The invention discloses an aircraft performance constraint compliance control method for contact type nondestructive testing, and belongs to the field of aircraft control. The implementation method comprises the following steps: introducing a saturated contact force controller into a position ring, and dynamically adjusting a confidence factor based on a position error to adaptively adjust normal rigidity and tangential flexibility; a zero-order control barrier function ZOCBF restrains the force controller, a three-dimensional dynamic safety boundary is established by using a sampling data mechanism, and the position, speed and contact force of the unmanned aerial vehicle are optimized and limited through quadratic programming; designing a hybrid torque controller in the attitude ring, and dynamically selecting a balance point through a binary logic switching strategy; the controller performs safety limitation on the attitude and angular velocity of the unmanned aerial vehicle in combination with zero-order control obstacle function constraint; monitoring a quaternion scalar component symbol in real time by defining a manifold switching set and a jump set; by fusing position loop and attitude loop control logic, compliance control during contact-type nondestructive testing of the unmanned aerial vehicle is realized.

A system and method for providing airport docking guidance for an aircraft includes supplying, from an airport gate database, airport gate data parking data indicative of gate position points and a gate aircraft parking headings. Aircraft data is supplied from an aircraft data source. Position error data is supplied from a position error receiving system. Airport gate data for one airport gate is retrieved. A processing system processes the aircraft data and the position error data to determine, for the one airport gate, an aircraft position point, an aircraft position deviation, and an aircraft heading deviation. The position error data may be supplied from a ground-based position error transmission system that at least selectively determines, from airport gate data and a ground-based position measurement system, the position error data and transmits the position error data.

A position error monitoring method and control system of a rotating mechanism, in the position error monitoring method of the rotating mechanism, angular position data of an encoder of a first motor and an encoder of a second motor are acquired as first position data during a process; then, during a non-process, the relative speed between the first motor and the second motor is adjusted while the rotating mechanism remains in a rotating state, so that the relative position of the first rotating part and the second rotating part is dynamically adjusted to a preset calibration phase, and second position data are acquired during operation at the calibration phase; the transition from the process phase to the calibration phase can be completed without stopping the rotating mechanism, time loss and mechanical impact caused by frequent start and stop are avoided, and the operation efficiency and productivity of the rotating mechanism are improved; in addition, whether there is a transmission error is determined by calculating the deviation value between the second position data and the first position data, which helps to find faults in time and improve the consistency and yield of the process.

The invention discloses a position error monitoring method and a control system of a rotating mechanism, and the method comprises the steps: obtaining the angular position data of an encoder of a first motor and an encoder of a second motor as first position data in a process processing period; then, in the non-process treatment period, the relative speed between the first motor and the second motor is adjusted in the rotating state of the rotating mechanism, the relative position of the first rotating component and the relative position of the second rotating component are dynamically adjusted to the preset calibration phase, and second position data are obtained in the calibration phase operation period; transition from a process phase to a calibration phase can be completed without stopping the rotating mechanism, so that time loss and mechanical impact caused by frequent start and stop are avoided, and the operation efficiency and the productivity of the rotating mechanism are improved; in addition, whether transmission errors exist or not is judged by calculating the deviation value between the second position data and the first position data, faults can be found in time, and the consistency and yield of process processing are improved.

The present invention discloses a method for adaptive iterative learning collaborative control of a movable beam and an extrusion rod of an extruder, which relates to the technical field of multi-agent adaptive iterative learning collaborative control and includes the following steps: constructing a dynamic model of the movable beam and the extrusion rod; determining a control target; determining a position error tracking system according to the control target, and designing a controller and a parameter update law based on adaptive iterative learning control theory; and performing theoretical simulation verification. The present invention adopts the above-mentioned method for adaptive iterative learning collaborative control of a movable beam and an extrusion rod of an extruder, regards the movable beam and the extrusion rod of the extruder as intelligent bodies, and combines adaptive iterative learning control theory to effectively realize the collaborative control of the movable beam and the extrusion rod; the method has self-regulating control capabilities, can produce products with higher precision requirements under the influence of nonlinear factors, improve production efficiency and reduce production costs, and is easy to expand and adapt to production needs of different scales.

Method for determining vehicle odometry, comprising: Receiving initial sensor data by a controller (34) of a vehicle (10); Receiving second sensor data by the controller (34) of the vehicle (10); Determining an initial longitudinal position, an initial lateral position and an initial heading of the vehicle (10) by the controller (34) of the vehicle (10) using the first sensor data, wherein the first sensor data are generated by an inertial measurement unit (IMU) of the vehicle (10), a wheel speed sensor (WSS) and a steering angle sensor (SAS) of the vehicle (10); Determining a longitudinal position error, a lateral position error and a course error of the vehicle (10) by the controller (34) of the vehicle (10) using the second sensor data, wherein the second sensor data are generated by a radar device of the vehicle (10); Determining a longitudinal speed of the vehicle (10) using the first sensor data and the second sensor data; Determining a lateral speed of the vehicle (10) using the first sensor data and the second sensor data; Determining a yaw rate of the vehicle (10) using the first sensor data and the second sensor data; Correcting the initial longitudinal position, initial lateral position, and initial heading of the vehicle (10) using the longitudinal position error, lateral position error, and heading error, respectively, thereby generating a corrected longitudinal position, a corrected lateral position, and a corrected heading of the vehicle (10), wherein the corrected longitudinal position, the corrected lateral position, and the corrected heading of the vehicle (10) are determined using an adaptive filter, wherein the corrected longitudinal position is based on the enhancement of a longitudinal position, the corrected lateral position is based on the enhancement of a lateral position, and the corrected heading is based on the enhancement of a heading. where the adaptive filter is implemented using a multitude of equations, and the multitude of equations includes: Δxk + 1 = Δxk + gk, xex, k Δ yk + 1 = Δ yk + gk , yey , k Δ ψ k + 1 = Δ ψ k + gk , ψ e ψ , k where: k is a time step; Δx k+1 is a filtered term for the initial longitudinal position of the vehicle (10); Δy k+1 is a filtered term for the initial lateral position of the vehicle (10); Δψ k+1 is a filtered term for the initial course of the vehicle (10); Δx k is a change in the longitudinal position of the vehicle (10) at time k; Δy k is a change in the lateral position of the vehicle (10) at time k; Δψ k is a change in the course of the vehicle (10) at time k; G k,x is the strengthening of the longitudinal position at time k; G k,y is the strengthening of the transverse position at time k; G k,ψ is the strengthening of the price at time k; ex,k is the error of the longitudinal position at time k; e y,k is the error of the transverse position at time k; and e ψ,k is the error of the course at time k; where the longitudinal position error, the transverse position error, and the course error are calculated using the following equations: ex = vs ( 1 ) . dt − Δ x ˜ ey = vs ( 2 ) . dt − Δ y ˜ e ψ = atan2 (vs (2) vs (1)) − Δ ψ ˜ where: v s is the scene speed of the vehicle as detected by the radar (10); e x is the error term for the x-position (i.e., the longitudinal position) of the vehicle (10); e y is the error term for the y-position (i.e., for the lateral position) of the vehicle (10); e ψ is the error term for the course of the vehicle (10); Δ x ˜ Delta x-position with uncertainty; Δ y ˜ Delta y-position with uncertainty; Δ ψ ˜ Delta price with uncertainty; and t is time; and Steering the vehicle (10) using the corrected longitudinal position, the corrected lateral position and the corrected course.

The invention discloses an aircraft control method and device, electronic equipment, an aircraft and a storage medium. The method comprises the following steps: acquiring a target position corresponding to the multi-rotor aircraft, wherein rotors of the multi-rotor aircraft are provided with mounting angles; determining a position error corresponding to the current moment based on the target position of the multi-rotor aircraft and an actually measured position corresponding to the current moment fed back by the multi-rotor aircraft; determining a target acceleration corresponding to the current moment based on the position error corresponding to the current moment and an actually measured speed corresponding to the current moment fed back by the multi-rotor aircraft; and determining a target rotating speed corresponding to the current moment based on the target acceleration corresponding to the current moment, and controlling the multi-rotor aircraft to work based on the target rotating speed corresponding to the current moment. The method can improve the response speed and control bandwidth of the aircraft controlled in the horizontal direction.

The invention relates to a polarization / inertial navigation combined navigation method with an embedded unmanned aerial vehicle (UAV) dynamics model. The method comprises the following steps: taking the three-dimensional attitude error angle, velocity error, position error, angular velocity error and thrust coefficient error of the UAV dynamics model as state quantities and expanding them into inertial navigation state parameters to form system state quantities, and establishing a system state equation; taking the heading angle solved by a polarization sensor and the attitude, velocity and position of the UAV dynamics model as quantity measurements to establish a system measurement equation; establishing a credibility discriminant function of the polarization heading vector measurement based on heading angle innovation information, and designing a combined navigation mode switching and thrust coefficient error feedback strategy; and using a Kalman filtering method to estimate the system state quantities, namely the inertial navigation attitude misalignment angle, velocity error and position error, and the attitude error angle, velocity error, position error and thrust coefficient error of the UAV dynamics model, to achieve correction of the UAV attitude and position.

The application discloses a satellite ranging auxiliary aircraft trajectory end positioning method, which comprises the following steps: S1, positioning the current position of the aircraft by using an inertial navigation system, and calculating the interval distance from the destination; then, calculating the estimation error of the aircraft positioning based on a Monte Carlo position error estimation method; S2, judging whether the aircraft enters the destination neighborhood range according to the interval distance, if yes, entering step S3, otherwise, entering step S4; S3, judging whether the estimation error is greater than the end threshold, if yes, entering step S5, otherwise, returning to step S1; S4, judging whether the estimation error is greater than the process threshold, if yes, entering step S5, otherwise, returning to step S1; S5, positioning the aircraft by using a single satellite fusion positioning algorithm based on an unscented Kalman filter, and returning to step S1 after a preset time length is executed.

The application provides an aerial docking method and device based on a contact force-position neural network model. The method provided by the application comprises the following steps: building a ground data acquisition device, collecting training data of contact force and corresponding position parameters in three dimensions of horizontal direction, vertical direction and relative angle through the ground data acquisition device; constructing a contact force-position neural network model, training the contact force-position neural network model by using the training data; acquiring relative position and attitude information between a work unmanned aerial vehicle and a target, and predicting contact force based on the contact force-position neural network model; combining the predicted contact force, position error of the work unmanned aerial vehicle and the target, and preset expected docking force to generate a preliminary reference trajectory; introducing a control allocation method to optimize and adjust the preliminary reference trajectory, and performing aerial docking between the work unmanned aerial vehicle and the target based on the optimized trajectory.

The embodiment of the invention provides a control method of an airship hanging load, electronic equipment, a storage medium and a program product, and relates to the technical field of nonlinear control, the control method of the airship hanging load provided by the embodiment of the invention designs a component of a virtual control force along a cable direction in load trajectory tracking control and position error control, so that the control precision of the airship hanging load is improved; and driving the load to approach the expected trajectory. A cable direction error is introduced in cable swing angle suppression, a component perpendicular to a cable is designed, swing is suppressed, stability is guaranteed, in airship driving control implementation, according to the load control requirement, analog control force needed by the airship is solved, dynamic balance is achieved by adjusting a propelling system of the airship, the dynamic coupling effect of an airship speed ring is considered, and the airship swing angle is suppressed. The self-adaptive control of the attitude is realized, the problems of large deviation of load tracking expected trajectory, insufficient cable swing suppression and unstable airship attitude are solved, and the hoisting control precision of the airship hanging load is improved.

The present application relates to a kind of system level calibration method for correcting the zero offset of acceleration channel of inertial measuring device, belongs to the field of inertial measurement.The zero position error of acceleration channel is compensated, the method does not need to disassemble inertial measuring device, by the vertical direction of three axes of aircraft respectively, the zero position error of acceleration channel of inertial measuring device can be calculated.The present application proposes the system level calibration method for quickly correcting the zero offset of acceleration channel of inertial measuring device, by simple calibration path setting, the zero offset error of acceleration channel can be effectively calculated.When the change of accelerometer itself zero offset error occurs, it is no longer necessary to disassemble inertial measuring device from aircraft and re-performs discrete calibration, and the influence of installation error caused by repeated installation of inertial measuring device is avoided.

The present invention discloses an inertial navigation modulation axis control method based on an LQR regulator, which relates to the technical field of inertial navigation, and includes: sampling the current angular velocity and the angular position of the motor and respectively taking the differences from the expected values of the inertial navigation system, and taking the two differences as the angular velocity error and the angular position error respectively and inputting them into the LQR regulator; taking the state equation of the motor as the objective function in the LQR regulator, generating and solving the Riccati equation, inputting the expected acceleration of the motor into the PID controller and tracking the expected acceleration, taking the difference between the expected acceleration and the currently sampled acceleration of the motor, and calculating the control quantity as the output of the PID controller, and the control quantity is the Q-axis control voltage of the motor in the rotating coordinate system; the inertial navigation system calculates and processes the control quantity through the SVPWM algorithm to control the modulation axis of the inertial navigation device, and the modulation axis issues an instruction to the motor to correct the operating state of the motor.

This invention belongs to the field of aircraft control simulation technology and relates to a method for correcting the position error of a static pressure source during the landing phase of an aircraft simulator. It aims to address the problem that existing static pressure source position error correction technologies lack targeted calibration for ground effects during the landing phase. The invention includes: acquiring real flight data and simulated flight data during the landing phase; calculating the difference in flight parameters to obtain the expected residual value; fitting error parameters to obtain the pressure coefficient caused by the static pressure source position error to determine the position error; superimposing the position error onto the flight parameters of the simulated flight data; recalculating the difference until the expected residual value is less than a threshold, thus completing the correction; the error parameters include the pressure coefficient difference at zero angle of attack, the slope of the pressure coefficient difference as a function of the angle of attack, and the influence factor of ground effects on the position error. This invention performs real-time correction of static pressure sensor measurements, effectively eliminating the static pressure source position error caused by ground effects during the landing phase.

This application belongs to the field of aircraft design technology, and particularly relates to a static pressure source position error correction method. Based on current numerical simulation and flight test state points, a static pressure source position error correction analysis is performed on the theoretical configuration, obtaining the static pressure source pressure coefficient Cp, the flight test static pressure source pressure coefficient Cp0, and the measured static pressure source pressure coefficient Cp1. The static pressure source position error correction data is optimized to obtain the static pressure source position error correction relationship Cp′ during actual flight of the theoretical configuration, and then the static pressure source position error is corrected. The application of configuration measurement, CFD simulation, and flight test data is achieved. The static pressure source position error is corrected as a function of Mach number, angle of attack, and altitude. This method not only meets the pressure altitude requirements of CCAR Part 25, but also meets the altitude measurement system error requirements of RVSM operations in AC‑21‑13. This method can be used for atmospheric data correction on transport aircraft and can be used as a reference for atmospheric data correction on other types of aircraft.

The present invention discloses a gravity matching method based on the characteristics of gravity measurement data. The present invention takes into account the variation characteristics of gravity measurement data, analyzes the extreme value measurement points, and combines with the gravity background map to obtain a relatively accurate position estimation point that is not affected by the initial position error of the inertial navigation. Then, taking this position estimation point as the initial position point of the filtering gravity matching algorithm for gravity matching, it can effectively reduce the influence of the matching initial error caused by the inertial navigation system and the real-time gravity measurement data error, and improve the gravity matching positioning accuracy. In addition, the present invention also introduces the concept of direction measurement according to the relationship between the underwater vehicle's heading angle and the navigation displacement direction within the matching period in the filtering gravity matching algorithm, which can effectively solve the problem of slow convergence speed in the filtering gravity matching algorithm. At the same time, the algorithm also has a certain ability to resist outliers.

The invention discloses a satellite ranging-assisted aircraft trajectory tail end positioning method, which comprises the following steps of: S1, positioning the current position of an aircraft by using an inertial navigation system, and calculating the spacing distance between the aircraft and a destination; calculating an estimated error of aircraft positioning based on a position error estimation method of Monte Carlo; s2, judging whether the aircraft enters a destination neighborhood range or not according to the spacing distance, if so, entering step S3, and otherwise, entering step S4; s3, judging whether the pre-estimated error is greater than an end point threshold value or not, if so, entering the step S5, and otherwise, returning to the step S1; s4, judging whether the pre-estimated error is greater than a process threshold value or not, if so, entering the step S5, and otherwise, returning to the step S1; and S5, positioning the aircraft by adopting a single-satellite fusion positioning algorithm based on unscented Kalman filtering, and returning to the step S1 after executing a preset duration.

The invention provides a hovering control method and a hovering control system for a small unmanned helicopter with a mechanical arm, and provides a position-attitude double-loop composite control strategy integrating a disturbance observer and an extended state observer. Wherein a sliding mode controller is provided in a position loop, and a nonlinear disturbance observer is designed; besides, in consideration of the influence of continuous operation of the mechanical arm on the gravity center and rotational inertia of the whole system under wind disturbance, a nonlinear expansion state observer is designed in an attitude ring, and a backstepping sliding mode controller is provided to stabilize the hovering attitude of the helicopter. According to the hovering control method and control system for the small unmanned helicopter with the mechanical arm, the position error is smaller than or equal to 2% under disturbance of equivalent wind power of three levels, and the sliding mode controller is high in control precision, high in robustness and obvious in tremor suppression effect; the maximum amplitude of the hovering attitude angle is smaller than or equal to 0.1 rad, and high-robustness control can be achieved by combining a backstepping sliding mode controller with an improved extended state observer.

An embodiment of the present invention discloses a ship trajectory tracking event-triggered control method and system with a performance game mechanism. The method includes: S1, determining the position error and attitude error corresponding to the ship; S2, designing a first performance index and a first value function; S3, designing the negative gradient estimate of the first value function, the optimal virtual control law, and the online learning law; S4, obtaining the dynamic reference signal and the dynamic control error; S5, defining a second performance index and the corresponding second value function; S6, designing the negative gradient estimate corresponding to the second value function, the optimal control input, and the optimal trigger error; S7, determining whether the trigger rule is satisfied; S8, changing the ship state and continuing to determine whether the navigation task is completed. If not, reconfirm the current state of the ship and return to S1. The present invention solves the problems in the prior art that "it is difficult for operators to obtain the best trigger effect and control accuracy" and "the ship trajectory tracking controller has weak robustness in the marine environment interference".

The present application relates to the technical field of aircraft major component attitude adjustment and matching, in particular to a kind of attitude adjustment and matching driving method, system, equipment and medium based on the space protection distance threshold of multiple positioners;The method first establishes the position error model of three-coordinate positioner spherical hinge center in the aircraft coordinate system, secondly, the space protection distance threshold setting value of multiple positioners is obtained according to the position error model, then according to the space protection distance threshold setting value, the constraint condition of major component attitude adjustment cooperative motion is set, finally, according to the constraint condition of major component attitude adjustment cooperative motion, major component attitude adjustment and matching system is driven to complete attitude adjustment, improve the efficiency of aircraft major component attitude adjustment and matching system, avoid the pulling of aircraft major component or lead to product extrusion deformation, and provide basis for the scheme design of major component attitude adjustment and matching system.

This invention provides a position control method and apparatus based on attitude control error feedforward compensation, relating to the field of rendezvous and docking technology. The method includes: calculating the orbital control error based on the attitude control error; determining the position error at the end of the long-range guidance segment under the influence of the orbital control error; calculating a corresponding compensation amount based on the position error at the end of the long-range guidance segment; and correcting the nominal position value based on the compensation amount, so as to use the corrected nominal position value for position control. This solution can achieve high-precision position control under large-pulse orbital control.

The present invention provides a method for inertial vision landing navigation of a rotor unmanned aerial vehicle. The specific steps of the navigation method are as follows: First step, cooperative target coordinate system error modeling: Convert the displacement amount resolved by the inertial navigation system on the geographic coordinate system to the cooperative target coordinate system, and use the C n a attitude transfer matrix for conversion. Then, perform error modeling under the cooperative target coordinate system; Second step, fuse the inertial navigation and vision navigation information: Fuse the inertial navigation and vision navigation information through the Kalman filtering algorithm; Third step, system measurement noise matrix fitting method: Calculate the relative distance between the rotor unmanned aerial vehicle and the cooperative target, and fit the measurement noise matrix R k ; Fourth step, position error correction: That is, correct each error of the inertial navigation; The present invention realizes the need not to obtain the cooperative target position information in advance, solves the technical problem that the vision navigation accuracy changes with the distance between the unmanned aerial vehicle and the cooperative target, and improves the vision navigation accuracy of the unmanned aerial vehicle.

The invention provides a flight operation robot contact force tracking control method based on variable stiffness admittance. The method comprises the following steps: S1, establishing a dynamic model of a flight operation robot system; s2, designing a self-adaptive variable stiffness admittance model, generating an expected reference trajectory by dynamically adjusting a stiffness coefficient, and compensating the influence of unknown environmental parameters; s3, designing a nonlinear disturbance observer to estimate system disturbance, and providing disturbance compensation for the pose controller; s4, a pose controller is designed based on the obstacle Lyapunov function, reference trajectory tracking is achieved, and the position error is strictly restrained to be within a safe range; s5, the rotating speed of each rotor wing of the flying operation robot is calculated through control input; the flying operation robot is controlled to realize stable contact force tracking; according to the method, uncertainty and contact disturbance in an unknown dynamic environment can be effectively dealt with, and the contact force tracking precision and the operation safety of the flying operation robot are improved.

The application discloses a kind of unmanned plane / ship cooperative path tracking control method under variable speed navigation scene, S1: the nonlinear system model of unmanned plane / ship cooperative system is established;S2: the reference path of virtual ship and the reference path of virtual unmanned plane are constructed;S3: the position error of nonlinear system model is constructed;S4: design first virtual control law;S5: design adaptive sliding surface;S6: design the sliding mode control law and position adaptive law of position controller;S7: design second virtual control law;S8: design the attitude control law and attitude adaptive law of attitude controller;S9: realize nonlinear system model for virtual unmanned plane / ship variable speed path tracking cooperative control.The application solves the problem of existing sea-air cooperative variable speed guidance vacancy, can efficiently plan the tracking path of unmanned plane / ship according to the traffic situation of target port area water area, meanwhile, the application has strong robustness to the system parameter fluctuation and external interference that appear.

The invention provides a missile-borne inertial navigation system aerial fine alignment method and system based on GNSS assistance, and relates to the technical field of integrated navigation, and the method comprises the following steps: obtaining system state data, position data and GNSS assisted navigation data of a missile-borne inertial navigation system, and constructing a measurement equation of the missile-borne inertial navigation system according to the system state data; determining a position error parameter and a system state error parameter according to the measurement equation and the data obtained in the step S1; inputting the data into a position prediction model for prediction to obtain a corresponding state prediction result and a position prediction result; and correcting the state prediction result and the position prediction result according to the state error parameter and the position error parameter of the system to complete the air fine alignment of the missile-borne inertial navigation system. By fusing multi-source data, considering an error model, constructing a decision model and the like, fine alignment in the air of the missile-borne inertial navigation system is realized, and the alignment precision is improved.