Paper | Classification algorithm | QI | Classification accuracy (%) |
---|---|---|---|
Yozevitch et al. (2012) | Naïve threshold | C/N0 | 70–80 |
Hsu (2017) | SVM | C/N0 | 67.1 |
Hsu (2017) | SVM | Change rate of C/N0 | 39.4 |
Hsu (2017) | SVM | pseudorange residual | 40.5 |
Hsu (2017) | SVM | difference between delta pseudorange and pseudorange rate | 65.4 |
GBDT | C/N0 | 74.1 | |
Yozevitch et al. (2016) | Decision tree | C/N0, elevation angle, measurement, carrier lock, satellite clock bias, indifferent features | 78.9 |
Hsu (2017) | SVM | C/N0, Change rate of C/N0, pseudorange residual, difference between delta pseudorange and pseudorange rate | 75.4 |
Xu et al. (2019) | SVM | Correlator-Level and RINEX/NMEA-Level features | 90.4 |
GBDT | C/N0, pseudorange residual, elevation angle | 89.0 | |
Decision tree | C/N0, pseudorange residual, elevation angle | 76.0 | |
Distance-weighted KNN | C/N0, pseudorange residual, elevation angle | 88.5 | |
ANFIS | C/N0, pseudorange residual, elevation angle | 82.7 | |
This paper, 2023 | Random forest | The standard deviation of pseudorange, C/N0, elevation angle, and difference of azimuth angle | 93.4 |