WeChat Mini Program
Old Version Features

基于多频载波相位的隧道内定位实验

Research and Exploration in Laboratory(2023)

中国矿业大学

Cited 0|Views6
Abstract
针对隧道等复杂作业环境导致定位精度差对作业人员安全隐患提出的挑战,设计了一种基于多频载波相位的隧道移动目标定位方法.实验融合了通信电子电路、数字信号处理、通信原理等学科相关知识,使学生了解隧道标签阵列定位系统模型,学习MFDAE空域滤波和WMMSENS多频载波相位测距算法,抑制隧道内密集多径干扰和解决相位模糊问题,掌握移动目标定位实测场景规划,培养学生软硬件设计思维,通过实验能直观得到最优结果,提高学生的实践能力和创新能力.
More
求助PDF
上传PDF
Bibtex
AI Read Science
AI Summary
AI Summary is the key point extracted automatically understanding the full text of the paper, including the background, methods, results, conclusions, icons and other key content, so that you can get the outline of the paper at a glance.
Example
Background
Key content
Introduction
Methods
Results
Related work
Fund
Key content
  • Pretraining has recently greatly promoted the development of natural language processing (NLP)
  • We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
  • We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
  • The model is scaled to large model with 10 billion parameters with sophisticated deployment, and the 10 -parameter M6-large is the largest pretrained model in Chinese
  • Experimental results show that our proposed M6 outperforms the baseline in a number of downstream tasks concerning both single modality and multiple modalities We will continue the pretraining of extremely large models by increasing data to explore the limit of its performance
Upload PDF to Generate Summary
Must-Reading Tree
Example
Generate MRT to find the research sequence of this paper
Data Disclaimer
The page data are from open Internet sources, cooperative publishers and automatic analysis results through AI technology. We do not make any commitments and guarantees for the validity, accuracy, correctness, reliability, completeness and timeliness of the page data. If you have any questions, please contact us by email: report@aminer.cn
Chat Paper
Summary is being generated by the instructions you defined