Design of Multiple Spatial Context Detection Method Considering Elongated Top-Bounded Spaces Based on GPS Signal-To-Noise Ratio and Fuzzy Inference
Abstract
:1. Introduction
2. Related Work
3. Design of Multiple Spatial Context Detection Method Considering ETBS
3.1. Requirements for ETBS Stay Detection
3.2. Design of Multiple Spatial Context Detection Method Considering ETBS
3.2.1. Overview
3.2.2. Satellite Classification Using the Entry Angle Threshold and Side Open Orientation
3.2.3. Design of the Decision Flow for Multiple Spatial Context Detection Using Fuzzy Inference
4. Evaluation Experiments
4.1. Evaluation for Multiple Spatial Context Detection Using Our Proposed Method
4.2. Evaluation of Differences in the Detection Accuracy by the Receiving Devices
5. Discussions
6. Conclusions
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
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ID | Contents |
---|---|
R1 | If is HIGH, and is HIGH, then = 1 |
R2 | If is HIGH, and is MIDDLE, then =−1 |
R3 | If is MIDDLE, and is HIGH, then =−1 |
R4 | If is MIDDLE, and is MIDDLE, then =−1 |
ID | Contents |
---|---|
R1 | If is MIDDLE, and is MIDDLE, then = 1 |
R2 | If is MIDDLE, and is LOW, then = −1 |
R3 | If is LOW, and is MIDDLE, then = −1 |
R4 | If is LOW, and is LOW, then = −1 |
aveSNR Value (dB-Hz) | P1 | P2 | P3 and P4 | P5 | P6 | |||||
---|---|---|---|---|---|---|---|---|---|---|
Group 1 | Group 2 | Group 1 | Group 2 | Group 1 | Group 2 | Group 1 | Group 2 | Group 1 | Group 2 | |
Average | 36.5 | 35.1 | 36.9 | 36.2 | 27.6 | 34.9 | 21.2 | 23.2 | 19.9 | 19.7 |
Max | 40.6 | 40 | 38.4 | 39.6 | 35.4 | 40.6 | 24.2 | 26.6 | 24 | 21.2 |
Min | 33.4 | 33 | 35.4 | 33.8 | 20.8 | 28.8 | 19 | 20.2 | 16 | 18.2 |
Standard Deviation | 2.02 | 1.95 | 1.11 | 1.55 | 3.92 | 2.92 | 1.57 | 1.86 | 2.45 | 0.92 |
Number of Measurement | Number of Correct Detections | Detection Accuracy | ||
---|---|---|---|---|
Outdoor | P1 | 12 | 12 | 100.0% |
P2 | 12 | 12 | 100.0% | |
Elongated top-bounded space (ETBS) | P3 and P4 | 24 | 21 | 87.5% |
Indoor | P5 | 12 | 10 | 83.3% |
P6 | 12 | 12 | 100.0% | |
Total | 72 | 67 | 93.1% |
Model A | Model B | ||||
---|---|---|---|---|---|
Model Name | Fujitsu Arrows m4 | Google Pixel3a | |||
OS version | Android 7.1.1 | Android 10 | |||
Group 1 | Group 2 | Group 1 | Group 2 | ||
Average of aveSNR (dB-Hz) | P1 | 37.2 | 35.9 | 36.9 | 40.6 |
P2 | 36.8 | 36.5 | 35.7 | 41.5 | |
P3 and P4 | 27.7 | 33 | 27.7 | 34.8 | |
P5 | 21.4 | 22 | 22 | 25.2 | |
P6 | 20.7 | 18.9 | 19.7 | 21.4 |
Model A | Model B | |||
---|---|---|---|---|
Number of Measurement | Number of Correct Detections | Number of Correct Detections | ||
Outdoor | P1 | 6 | 6 | 6 |
P2 | 6 | 6 | 6 | |
Elongated top-bounded space (ETBS) | P3 and P4 | 12 | 10 | 9 |
Indoor | P4 | 6 | 5 | 3 |
P5 | 6 | 6 | 6 | |
Total | 36 | 33 | 30 |
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Tabata, K.; Nakajima, M.; Kohtake, N. Design of Multiple Spatial Context Detection Method Considering Elongated Top-Bounded Spaces Based on GPS Signal-To-Noise Ratio and Fuzzy Inference. ISPRS Int. J. Geo-Inf. 2020, 9, 717. https://doi.org/10.3390/ijgi9120717
Tabata K, Nakajima M, Kohtake N. Design of Multiple Spatial Context Detection Method Considering Elongated Top-Bounded Spaces Based on GPS Signal-To-Noise Ratio and Fuzzy Inference. ISPRS International Journal of Geo-Information. 2020; 9(12):717. https://doi.org/10.3390/ijgi9120717
Chicago/Turabian StyleTabata, Kenichi, Madoka Nakajima, and Naohiko Kohtake. 2020. "Design of Multiple Spatial Context Detection Method Considering Elongated Top-Bounded Spaces Based on GPS Signal-To-Noise Ratio and Fuzzy Inference" ISPRS International Journal of Geo-Information 9, no. 12: 717. https://doi.org/10.3390/ijgi9120717
APA StyleTabata, K., Nakajima, M., & Kohtake, N. (2020). Design of Multiple Spatial Context Detection Method Considering Elongated Top-Bounded Spaces Based on GPS Signal-To-Noise Ratio and Fuzzy Inference. ISPRS International Journal of Geo-Information, 9(12), 717. https://doi.org/10.3390/ijgi9120717