Convolutional Neural Network Based Multipath Detection Method for Static and Kinematic GPS High Precision Positioning

• Published in: Remote sensing (Basel, Switzerland) Vol. 10; no. 12; p. 2052
• Main Authors: Quan, Yiming, Lau, Lawrence, Roberts, Gethin Wyn, Meng, Xiaolin, Zhang, Chao
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.12.2018
• Subjects: Accuracy; Algorithms; Artificial intelligence; Artificial neural networks; Back propagation; Civil engineering; Computer simulation; Convolutional Neural Network (CNN); Distance learning; Global Positioning System (GPS); Global positioning systems; GPS; high precision positioning; Kinematics; Machine learning; Methods; Mitigation; multipath detection; Navigation; Neural networks; Noise; Principal components analysis; Receivers & amplifiers; Remote sensing; Satellite navigation systems; Satellites; Software; Sparsity; Stochastic models; Terrestrial environments; Time series; Voice recognition; United Kingdom > UK; China; Faroe Islands; Ningbo China

Global Positioning System (GPS) has been used in many aerial and terrestrial high precision positioning applications. Multipath affects positioning and navigation performance. This paper proposes a convolutional neural network based carrier-phase multipath detection method. The method is based on th...