Time and frequency domain mixed identification method of non-cooperative target motion and inertial parameters

Abstract

The invention relates to a time and frequency domain mixed identification method of non-cooperative target motion and inertial parameters. Firstly, target pose information is obtained through a visioncamera. According to the invention, on the basis of visual measurement of target pose, translation and rotation in motion course are decoupled, time and frequency domain synchronous identification oftarget states and kinetic parameters is achieved, translation-related parameters are identified by DFT in the frequency domain, kinetic equation of a target floating in a space is linearized in the time domain, and rotation-related parameters are identified by EFIR.

Description

technical field [0001] The invention belongs to the field of spacecraft parameter identification, and relates to a time-frequency domain hybrid identification method of motion and inertia parameters of a non-cooperative target. Background technique [0002] Space operations, as the direction of future aerospace technology development, are getting more and more attention from aerospace powers. The space manipulator robot consisting of a platform base and an operating manipulator can be widely used in on-orbit service tasks such as on-orbit refueling, maintenance of faulty satellites, orbital garbage cleaning, and auxiliary orbit changes. The space manipulator robot is a kind of space robot, which has a large working space and dexterous operation performance. It has become the main means of current space operations. [0003] The premise of space operation is to capture the target. Since the captured target is a non-cooperative target, its motion state and inertia parameters ...

AI Technical Summary

Problems solved by technology

[0003] The premise of space operation is to capture the target. Since the captured target is a non-cooperative target, its motion state and inertia parameters are unknown, which has a great impact on the capture and the stability control of the complex after capture. Some research results and experiments are aimed at cooperative targets whose parameters are known, or use incentives to identify them, and need to be physically connected to the target, which is risky when the target is completely unknown

However, the existing vision-based parameter identification is processed in the time domain, and the measurement noise and process noise need to be known or assumed in advance, which is extremely harsh under the complex space background conditions.

And because there are more parameters to be estimated, longer processing time is required, which is extremely detrimental to the identification accuracy and fuel consumption

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