An Analysis Software for Visual Position and Attitude Measurement Algorithm

Proceedings of the 2023 2nd Asia Conference on Algorithms, Computing and Machine Learning Pub Date : 2023-03-17 DOI:10.1145/3590003.3590043

Tao-rang Xu, Jing Zhang, Bin Cai, Yafei Wang

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Abstract

Visual position and attitude measurement (VPAM) system has been widely used in obtaining space target information. In order to better obtain different target information and meet the requirements, it is particularly important to select a correct and effective measurement algorithm. In this paper, a performance evaluation software of VPAM algorithm is designed, which can compare and analyze the accuracy and complexity of algorithms used by different VPAM models, and help users select appropriate position models to obtain more accurate target information. Finally, the software is verified by using the dual photogrammetric model in the shipborne helicopter landing system, and the validity of the analysis software is verified by comparing the calculation results with the theoretical value of the algorithm accuracy analysis. The main contribution of this paper is that, as far as we know, it is the first time to try to evaluate the complexity and accuracy of the algorithm by building analysis software instead of theoretical analysis.

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一种视觉位置姿态测量算法分析软件

视觉位置姿态测量(VPAM)系统在获取空间目标信息方面得到了广泛的应用。为了更好地获取不同的目标信息，满足测量要求，选择正确有效的测量算法显得尤为重要。本文设计了VPAM算法的性能评价软件，可以对不同VPAM模型所使用的算法的精度和复杂度进行比较分析，帮助用户选择合适的位置模型，获得更准确的目标信息。最后，在舰载直升机着陆系统中使用双摄影测量模型对软件进行验证，并将计算结果与算法精度分析的理论值进行比较，验证分析软件的有效性。本文的主要贡献在于，据我们所知，这是第一次尝试通过构建分析软件来评估算法的复杂性和准确性，而不是理论分析。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Proceedings of the 2023 2nd Asia Conference on Algorithms, Computing and Machine Learning

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