Monocular visual error measurement system for cooperative target and error limit quantification method

Abstract

The invention discloses a monocular visual error measurement system for a cooperative target and an error limit quantification method. The monocular visual error measurement system is specifically characterized in that visual marker points are formed in the outer surface of the cooperative target, a calibration target adopts a black and white checkerboard like pattern and is used for the intrinsic and extrinsic parameter calibration of a camera, the camera is used for acquiring the images of the visual marker points and the images of the calibration target in one frame and transmitting the images to the computer, a first theodolite and a second theodolite are used for observing the calibration target to obtain an observation value A, observing the visual markers to obtain an observation value B and transmitting the observation value A and the observation value B to a computer, and the computer is used for receiving the calibration target image and marker image acquired by the camera, the observation value A and the observation value B, computing the camera pose measurement value and the real pose value of the cooperative target relative to the camera and computing a measurement error. By adopting the error limit quantification method, the measurement error can be quantified and decomposed so that each key parameter index is in the error limit.

Description

technical field [0001] The invention belongs to the field of photoelectric measurement, and relates to a monocular vision error measurement system and an error quantification method suitable for cooperative targets, and is especially suitable for the distribution of monocular vision measurement errors of space cooperative targets. Background technique [0002] Space targets mainly include cooperative targets and non-cooperative targets. The former refers to the space target that can provide effective cooperation information (such as target motion information and structural features), which is mainly manifested by the installation of feature marks for measurement; the latter cannot provide effective cooperation information, and its motion information and structural features are completely Unknown or partially unknown, the United States Space Research Council SSB, Aeronautics and Space Engineering Bureau ASEB have given a definition in the evaluation report of the Hubble Teles...

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Problems solved by technology

In Yang Jian's "Theoretical and Experimental Research on the Accuracy of Photographic Visual Measurement", he divided the parameter indicators affecting visual measurement into four categories: camera equipment error, target model error, software algorithm error, and personnel environment error, mainly based on engineering experience Put forward a series of rationalization suggestions on how to decompose and correct errors, and have not yet carried out further theoretical derivation and verification on the problem of error quantification and distribution

Hao Yingming carried out research on the robustness of monocular vision measurement for the purpose of improving the accuracy of the monocular vision measurement system for the design of three-point visual marker patterns in the document "Research on the Accuracy and Robustness of Pose Measurement Based on Point Features". Simplify the assumptions under the conditions, deduce the relationship expressions between the measurement error and the camera calibration error, the target model error, and the image coordinate detection error, and combine the statistical analysis of the error under general conditions to obtain the influence of the above parameters on the measurement results Trends and the conclusions of error synthesis of various factors, etc., only mentioned that error distribution is the reverse problem of error synthesis, but did not analyze and demonstrate in depth

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