Prof. He-xuan Hu Profile

Prof. He-xuan Hu

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Proceedings Article | 28 July 2023 Paper

A belief propagation cooperative localization algorithm in GNSS-loss environments

Fei Ma, Guoping Tan, Siyuan Zhou, Hexuan Hu

Proceedings Volume 12716, 1271606 (2023) https://doi.org/10.1117/12.2685589

KEYWORDS: Distance measurement, Signal attenuation, Satellite navigation systems, Particles, Roads, Motion models, Statistical modeling, Global Positioning System, Telecommunications, Linear regression

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When vehicles are in driving environments such as urban roads and tunnels, the global navigation satellite system (GNSS) signal can fail to achieve positioning due to occlusion. Cooperative positioning can effectively improve the accuracy and coverage of vehicle positioning. In this paper, we address the vehicle localization issue in GNSS-Loss driving environments and with random packet loss due to wireless communications. We propose an improved cooperative localization algorithm based on belief propagation, which first linearizes the measurement model of distance by statistical linear regression method, then performs belief propagation based on the linearized model, and solves the packet loss problem by expanding the dimension of the vehicle state. From the simulation results, the algorithm can effectively reduce the impact of packet loss and improve the vehicle localization accuracy.

Proceedings Article | 30 June 2021 Paper

Optimization of reservoir operation scheme based on fuzzy optimization and convolutional neural network

He-xuan Hu, Yue-qing Miao, Qiang Hu, Ye Zhang, Zhen-yun Hu, Rui Ma

Proceedings Volume 11878, 118782C (2021) https://doi.org/10.1117/12.2601054

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The evaluation and optimization of reservoir operation schemes belong to a multi-objective, multi-level and multi-attribute decision-making problem. The reservoir multi-objective dispatching model generates many Pareto feasible solutions, and decision-makers often make decisions difficult. The traditional scheme selection method has the problems that the index weight is greatly affected by subjectivity, the single weight determination method is one-sided, the model calculation is complicated, and the characteristics of the evaluation index cannot be fully extracted. Therefore, this paper proposes a new method for reservoir operation plan optimization based on fuzzy optimization and convolutional neural network. First, establish the evaluation index system of the reservoir operation plan based on the fuzzy optimization theory, select the analytic hierarchy process to determine the subjective weight of the index, the entropy weight method to determine the objective weight, use the game theory to couple the subjective and objective weights, and calculate the comprehensive evaluation value of the plan through fuzzy comprehensive evaluation. Secondly, the evaluation index and comprehensive evaluation value are used as the input and output of the convolutional neural network to establish the optimal model of the reservoir operation plan. The results of the case analysis show that the research method has high accuracy and reliability, and can provide a scientific basis for reservoir operation decision-making.

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