Visual Calculation Method of Spacecraft Docking Error Marginal Density Function

Abstract

The invention provides a method for calculating the marginal density function of visual spacecraft docking error. The method includes the first step of obtaining a docking error joint probability density function p (x, y) according to the docking error historical data of spacecraft docking mechanism, drawing a spacecraft docking error curved surface and forming a docking error joint probability density function cylinder with the curved surface and a XOY plane; the second step of building a marginal density visualization model. The lateral value range X in the marginal density visualization model traversal docking error joint probability density function cylinder obtains a marginal density function pX (x) of the lateral error, through a area value of the transverse plane crossed (X, 0) and parallel to the YOZ plane, which is intercepted by the docking error joint probability density function cylinder. The longitudinal value range y in the traversal docking error joint probability density function cylinder, obtains a marginal density function pY(y) of the lateral error, through a area value of the longitudinal plane crossed (Y, 0) and parallel to the XOZ plane, which is intercepted by the docking error joint probability density function cylinder.

Description

technical field [0001] The invention relates to a visualized calculation method for a spacecraft docking error marginal density function. Background technique [0002] The weak impact docking mechanism of the spacecraft adopts the claw-type docking mechanism. Its working principle is to actively realize the capture of the three passive lock handles through the three claw-type capture and locking mechanisms that can be engaged with each other, and complete the correction and buffering. and locking functions. [0003] The successful docking is mainly affected by three factors, one is the error in the X direction; the other is the error in the Y direction; the third is the extension range of the claw in the Z direction. The extension range of the claw is realized by design, and the actual operation process is mainly affected by the deviation in the X direction and the Y direction. The deviations in the X direction and the Y direction are random, and it is necessary to analyze...

AI Technical Summary

Problems solved by technology

In general, most of the random variables in engineering are continuous, and their integrability is undoubted, but in many cases, especially when the joint probability density function is more complicated, it is often difficult to find its analytical solution;

[0010] Second, the analytical method is not intuitive enough

The intuitive meaning is not obvious enough when the operation is performed by the analytical method;

[0011] Third, the analytical method is not conducive to programming

Analytical methods often set a lot of transformation rules, which is not conducive to the realization of computer algorithms

[0012] Problems in the above aspects bring problems in engineering implementation, understanding, efficiency, etc.

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