Satellite geometric feature and attitude estimation method based on foundation observation luminosity signal

Abstract

The invention discloses a satellite geometric feature and attitude estimation method based on a foundation observation luminosity signal. The method comprises the following steps: S1, establishing a satellite luminosity signal observation model under a foundation observation condition; S2, establishing a 'geometry-attitude-luminosity' database of the satellite; S3, identifying a geometric model and a scale of the satellite; S4, establishing an attitude kinematics equation of the observed satellite; S5, setting an initial parameter of the non-destructive Kalman filter; S6, taking the attitude kinematics equation and the satellite luminosity signal observation model as a time updating model and an observation updating model of a non-destructive Kalman filtering algorithm respectively, and performing updating estimation on satellite attitude parameters at the next observation moment by adopting the non-destructive Kalman filtering algorithm; and S7, taking the satellite attitude parameter estimated in the step S6 as a new observation moment satellite state parameter, repeating the step S6, and stopping iteration when the error of a satellite attitude parameter estimation value is smaller than a set threshold value or the satellite exceeds an observation range so as to obtain a high-precision satellite attitude parameter estimation value.

Description

technical field [0001] The invention relates to the technical field of space optical information processing, in particular to a satellite geometric feature and attitude estimation method based on ground-based observation photometric signals. Background technique [0002] In recent years, the increasingly tense space resources and international relations have put forward higher and newer requirements for the space situational awareness capabilities of countries. Accurate identification of key features of space targets is one of the main tasks of space situational awareness, and is of great significance to tasks such as target type identification, status judgment, threat assessment, and strategic decision-making. The ground-based photometric signal only contains energy information, which is the result of the coupling of various key features of the space target. It can comprehensively reflect the time series changes of the geometric shape, scale and attitude of the space target...

AI Technical Summary

Problems solved by technology

However, most current studies on photometric curves still have some limitations. On the one hand, these studies are mostly based on the known geometric model of the target, but in fact, the accurate geometric characteristics of the target are difficult to obtain, leading t

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