Sequence image state expression-based spacecraft autonomous navigation robust filtering algorithm

Abstract

The invention relates to a spacecraft autonomous navigation robust filtering algorithm based on sequence image state expression, and belongs to the technical field of autonomous navigation. The method comprises the following steps: 1, constructing a spatial non-cooperative target autonomous relative navigation system state equation; 2, constructing a monocular camera sequence image measurement equation; 3, constructing a state expression model based on a sequence image, separating a measurement value from a measurement error value by using a trigonometric function formula, and obtaining a measurement noise expectation matrix epsilon k according to measurement error distribution; 4, obtaining a one-step state prediction value at the moment k and a one-step prediction covariance matrix Pkk-1 at the moment k; 5, calculating to obtain an optimal gain Kk of state estimation; step 6, calculating to obtain a state estimation value xkk and a state estimation covariance matrix Pkk at the moment k; according to the method, the anti-interference performance on the inaccurate initial value of the system state can be improved, so that a state estimation result with higher precision is obtained.

Description

technical field [0001] The invention belongs to the technical field of autonomous navigation, and relates to a spacecraft autonomous navigation robust filtering algorithm based on sequence image state expression. Background technique [0002] The relative navigation method based on monocular camera sequence images is a key technical means to determine the relative position of space non-cooperative targets such as failed spacecraft, enemy satellites, and small celestial bodies. important role. [0003] Monocular camera sequence images can only provide line-of-sight angle information, which is poor in observability compared to navigation systems, and service spacecraft need to actively maneuver to provide distance information. In addition, due to the non-linearity of the relative navigation system and the influence of the space environment background, uneven illumination, and vibration of rotating parts on the spacecraft’s in-orbit operation, it is difficult to accurately est...

AI Technical Summary

Problems solved by technology

[0004] In the past nonlinear filtering algorithms, the nonlinear system is often approximated by Taylor expansion or deterministic sampling method. Although these methods can improve the state estimation accuracy of the nonlinear system to a certain extent, there is still a certain truncation error in the state estimation.

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