| Item type |
SIG Technical Reports(1) |
| 公開日 |
2023-09-18 |
| タイトル |
|
|
タイトル |
Preliminary Investigation of Indoor GPS Satellite Reception Prediction via Neural Networks |
| タイトル |
|
|
言語 |
en |
|
タイトル |
Preliminary Investigation of Indoor GPS Satellite Reception Prediction via Neural Networks |
| 言語 |
|
|
言語 |
eng |
| キーワード |
|
|
主題Scheme |
Other |
|
主題 |
スマートテクノロジーとデバイス |
| 資源タイプ |
|
|
資源タイプ識別子 |
http://purl.org/coar/resource_type/c_18gh |
|
資源タイプ |
technical report |
| 著者所属 |
|
|
|
Department of Multimedia Engineering, Graduate School of Information Science and Technology, Osaka University |
| 著者所属 |
|
|
|
Department of Multimedia Engineering, Graduate School of Information Science and Technology, Osaka University |
| 著者所属(英) |
|
|
|
en |
|
|
Department of Multimedia Engineering, Graduate School of Information Science and Technology, Osaka University |
| 著者所属(英) |
|
|
|
en |
|
|
Department of Multimedia Engineering, Graduate School of Information Science and Technology, Osaka University |
| 著者名 |
Heng, Zhou
Takuya, Maekawa
|
| 著者名(英) |
Heng, Zhou
Takuya, Maekawa
|
| 論文抄録 |
|
|
内容記述タイプ |
Other |
|
内容記述 |
The application of GPS in indoor environments remains a challenge due to the loss of signal precision. This research introduces a novel method for predicting the GPS signal strength received by smart-phones at arbitrary positions within a specified floor of a building. These predicted signal strengths could serve as a simple indoor fingerprinting system, obviating the need for an additional signaling infrastructure. We suggested a neural network-based system for signal strength prediction that mainly depends on the current position of the satellite of interest and the floor plan of the target floor incorporating wall and window information. Furthermore, we employ information about the azimuthal and elevation angles of the GPS satellite, as well as shapes and heights of nearby tall buildings, to estimate the line of sight (LOS) from each satellite to the target environment, which also serves as input. Preliminary experiments of this framework using real-world building data have been conducted. |
| 論文抄録(英) |
|
|
内容記述タイプ |
Other |
|
内容記述 |
The application of GPS in indoor environments remains a challenge due to the loss of signal precision. This research introduces a novel method for predicting the GPS signal strength received by smart-phones at arbitrary positions within a specified floor of a building. These predicted signal strengths could serve as a simple indoor fingerprinting system, obviating the need for an additional signaling infrastructure. We suggested a neural network-based system for signal strength prediction that mainly depends on the current position of the satellite of interest and the floor plan of the target floor incorporating wall and window information. Furthermore, we employ information about the azimuthal and elevation angles of the GPS satellite, as well as shapes and heights of nearby tall buildings, to estimate the line of sight (LOS) from each satellite to the target environment, which also serves as input. Preliminary experiments of this framework using real-world building data have been conducted. |
| 書誌レコードID |
|
|
収録物識別子タイプ |
NCID |
|
収録物識別子 |
AA11851388 |
| 書誌情報 |
研究報告モバイルコンピューティングと新社会システム（MBL）
巻 2023-MBL-108,
号 47,
p. 1-8,
発行日 2023-09-18
|
| ISSN |
|
|
収録物識別子タイプ |
ISSN |
|
収録物識別子 |
2188-8817 |
| Notice |
|
|
|
SIG Technical Reports are nonrefereed and hence may later appear in any journals, conferences, symposia, etc. |
| 出版者 |
|
|
言語 |
ja |
|
出版者 |
情報処理学会 |
IPSJ-MBL23108047.pdf (3.2 MB)
