Paper Publications

Hits:

Affiliation of Author(s):School of Artificial Intelligence

Teaching and Research Group:智能信息工程系

Journal:SN Applied Sciences

Place of Publication:Switzerland AG

Funded by:National Natural Science Foundation of China,Huawei Technologies Co., Ltd.

Key Words:vertical positioning，and data correction， parameter estimation，MLR, SVM, GPS

Abstract:In this paper, a method of improving vertical positioning accuracy with the Global Positioning System (GPS) information and barometric pressure values is proposed. First, we clear null values for the raw data collected in various environments, and use the 3$\sigma$-rule to identify outliers. Secondly, the Weighted Multinomial Logistic Regression (WMLR) classifier is trained to obtain the predicted altitude of outliers. The numerical results show that the vertical positioning accuracy is improved from 5.9 meters (the MLR method), 5.4 meters (the SVM method) to 5 . meters (the WMLR).

Indexed by:Journal paper

First Author:Yiyan Yao

Correspondence Author:luoxinlong

Document Code:1445

Discipline:Engineering

First-Level Discipline:Computer science and technology *

Document Type:J

Volume:2

Issue:8

Page Number:1-8

ISSN No.:2523-3971

Translation or Not:no

Date of Publication:2020-08-01

Links to published journals:http://doi.org/10.1007/s42452-020-03240-w

Attachments: