A Trajectory Estimation Method for Complex Maneuverable Aircraft Based on Learnable Extended Kalman Filter

A technology that extends Kalman and aircraft, applied in the field of information calculation based on knowledge and models, can solve the problem of low precision, achieve the effect of simplifying parameter adjustment and improving the accuracy of track estimation

Active Publication Date: 2022-07-01
HARBIN INST OF TECH
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] The purpose of the present invention is to provide a track estimation method suitable for aircraft with complex maneuvering forms, to solve the problem of low accuracy of existing methods under the complex maneuvering conditions of the target aircraft, and then provide a method based on learnable extended Kalman filter Track Estimation Method for Complex Maneuvering Vehicles

Method used

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  • A Trajectory Estimation Method for Complex Maneuverable Aircraft Based on Learnable Extended Kalman Filter
  • A Trajectory Estimation Method for Complex Maneuverable Aircraft Based on Learnable Extended Kalman Filter
  • A Trajectory Estimation Method for Complex Maneuverable Aircraft Based on Learnable Extended Kalman Filter

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Embodiment Construction

[0059] The learnable extended Kalman filter method for complex maneuvering target track estimation described in this embodiment is implemented according to the following steps:

[0060] Step 1: Build a maneuver model of the target

[0061] Assuming that the earth is a true sphere, ignoring the rotation, the three-dimensional dynamic model of the aircraft is obtained:

[0062]

[0063] Among them, r is the distance from the center of mass of the aircraft to the center of the earth, θ is the longitude, φ is the latitude, v is the velocity, γ is the ballistic inclination, ψ is the ballistic declination, m is the mass of the aircraft, R e =6,378,135m is the radius of the earth, g 0 is the acceleration of gravity, S ref is the characteristic area of ​​the aircraft, ρ=ρ 0 e -βh is the atmospheric density, and is the lift coefficient and drag coefficient when the lift-drag ratio of the aircraft is the largest, c l is the normalized lift coefficient, and σ is the roll angl...

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Abstract

A method for estimating the trajectory of a complex maneuvering aircraft based on the learnable extended Kalman filter, and the invention relates to a method for estimating the trajectory of an aircraft. The invention solves the problem that the existing track estimation method has low precision under complex maneuvering conditions of the target aircraft. The technical points of the present invention are: establishing a dynamic model of the aircraft, and further establishing a maneuvering model of the aircraft; building a learnable extended Kalman filter algorithm for aircraft track estimation, and designing and training the input modification network and gain modification therein. network. The learnable extended Kalman filter algorithm used in the aircraft track estimation in the present invention is obtained by training based on the existing track data, more fully utilizes the prior information of the motion characteristics of the aircraft, and can more accurately describe the complexity of the aircraft The maneuvering mode improves the accuracy of track estimation. This method is suitable for the field of information calculation based on knowledge and patterns.

Description

technical field [0001] The invention relates to a trajectory estimation method of an aircraft, in particular to a learnable extended Kalman filtering method based on a cyclic neural network, and belongs to the field of information estimation based on knowledge and patterns. Background technique [0002] For aircraft with complex maneuvering forms such as high-speed gliding aircraft, the trajectory estimation is more complicated than that of general aircraft. Most of the current aircraft trajectory estimation methods use constant velocity (CV), constant acceleration (CA), current statistics, Singer and other models to describe the target maneuver, and are based on extended Kalman filter (EKF), adaptive Kalman filter (AEKF), etc. method to achieve track estimation. When faced with such complex maneuvering forms of aircraft trajectory estimation, limited by the accuracy of the model, the existing trajectory estimation methods cannot adequately adapt to the complex motion modes...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F30/27G06N3/04G06N3/08G06F119/14
CPCY02T90/00
Inventor 郑天宇贺风华姚郁杨宝庆
Owner HARBIN INST OF TECH
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