# GNSS-IR Snow Depth Retrieval from Multi-GNSS and Multi-Frequency Data

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## Abstract

**:**

## 1. Introduction

## 2. Materials and Methods

#### 2.1. GNSS-IR Snow Depth Retrieval Principle

#### 2.2. Data Source

#### 2.2.1. Station Location and Surrounding Environment

#### 2.2.2. Selection and Analysis of Experimental Data

#### 2.2.3. Reflection Region Analysis

#### 2.2.4. SNR Types

## 3. Experiment and Results

#### 3.1. Experimental Technical Scheme

#### 3.2. Extraction h

#### 3.2.1. Multi-GNSS and Multi-Frequency SNR Sequence Extraction

#### 3.2.2. SNR Sequence Data Processing

#### 3.2.3. LSP Analysis Results of the Snow Surface

#### 3.2.4. LSP Analysis Results of the Snow-Free Surface

#### 3.3. GNSS-IR Snow Depth Retrieval Results

#### 3.3.1. Multi-GNSS and Multi-Frequency GNSS-IR Snow Depth Retrieval Results

#### 3.3.2. Mean Fusion of Multi-Frequency Retrieval Results in the Four GNSS Systems

#### 3.3.3. Mean Fusion Retrieval Results of Multi-GNSS System

## 4. Discussion

#### 4.1. Accuracy Analysis between Multi-GNSS and Multi-Frequency GNSS-IR Snow Depth Retrieval Results and PBO Snow Depth

#### 4.2. Accuracy Analysis of Multi-Frequency Mean Fusion Results in the GNSS Systems

#### 4.3. Accuracy Analysis of Mean Fusion Retrieval between Multi-GNSS System

## 5. Conclusions

- (1)
- QZSS and SBAS systems in multi-GNSS and multi-frequency SNR data provided by PBO are not suitable for use due to the lack of observation arcs. The GPS S1W and S2W data values are the same, and the other frequency SNR data difference is too large and should not be used;
- (2)
- The LSP results of the snow-free surface can be effectively used as the initial reflector height reference value. The snow depth results of multi-GNSS and multi-frequency GNSS-IR retrieval have a strong correlation with PBO snow depth data, and the RMSE of different frequency retrieval results in the multi-GNSS system is between 5 cm and 10 cm. The correlation between the retrieval results of the GPS L1, GLONASS G1, Galileo E1, and BDS B1 bands in the snow depth retrieval results is rather weak;
- (3)
- The mean fusion of multi-frequency retrieval results in GPS, GLONASS, Galileo, and BDS can effectively improve the accuracy and solve the relatively weak results in some bands. The four GNSS systems retrieval results show a strong correlation, and the RMSE is between 4 cm and 7 cm. Comparing the different frequency signals in the multi-GNSS system retrieval results, the multi-frequency mean fusion increase by 11.7% in R and the RMSE decreases by 55.6%, which is the highest;
- (4)
- The mean fusion accuracy of the retrieval results of the GPS, GLONASS, Galileo, and BDS is significantly improved. The R between the retrieval results and the PBO results is 0.99, and the retrieval accuracy is better than 3 cm, which significantly enhances the accuracy. In the comparison of the multi-frequency mean fusion, the multi-GNSS system fusion increases by 5.1% in R and the RMSE decreases by 57.1%, which is the highest.

## Author Contributions

## Funding

## Institutional Review Board Statement

## Informed Consent Statement

## Data Availability Statement

## Acknowledgments

## Conflicts of Interest

## References

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**Figure 1.**Schematic diagram of GNSS-IR snow depth retrieval. After the satellite sends the signal, the right-handed circular polarized (RHCP) antenna receives the direct signal and the surface reflected signal, and produces interference effect at the receiver. The snow surface reflector height (${H}_{s}$) and snow-free surface reflector height (${H}_{sf}$) are calculated, respectively, by analyzing the oscillation effect, and the snow depth (${h}_{sd}$) is calculated by comparing the differences between them. θ is the elevation angle of the satellite.

**Figure 2.**P387 station conditions: (

**a**) station location in the world; (

**b**) site vision; (

**c**) site north; (

**d**) site south; (

**e**) site east; (

**f**) site west.

**Figure 5.**Reflection region and reflection point track: (

**a**) Fresnel reflection region around P387 station; (

**b**) ground motion trajectory of reflection points around P387 station.

**Figure 6.**The technical process of multi-GNSS and multi-frequency GNSS-IR snow depth retrieval. Among the ele is the satellite elevation angle.

**Figure 7.**Multi-GNSS and multi-frequency SNR sequences: (

**a**) DOY 024: GPS SNR sequence; (

**b**) DOY 024: GLONASS SNR sequence; (

**c**) DOY 024: Galileo SNR sequence; (

**d**) DOY 024: BDS SNR sequence.

**Figure 8.**SNR sequence data processing: (

**a**) GPS S1C SNR and direct signal fitting; (

**b**) reflected signal extraction.

**Figure 9.**Multi-GNSS and multi-frequency LSP analysis results: (

**a**) GPS LSP results; (

**b**) GLONASS LSP results; (

**c**) Galileo LSP results; (

**d**) BDS LSP results.

**Figure 10.**The snow-free surface reflector height reference value of multi-GNSS and multi-frequency LSP analysis results.

**Figure 11.**Comparison between multi-GNSS and multi-frequency GNSS-IR snow depth retrieval results and PBO snow depth: (

**a**) GPS snow depth retrieval results; (

**b**) GLONASS snow depth retrieval results; (

**c**) Galileo snow depth retrieval results; (

**d**) BDS snow depth retrieval results.

**Figure 14.**Correlation and RMSE between multi-GNSS and multi-frequency GNSS-IR snow depth retrieval results and PBO snow depth: (

**a**) GPS S1C; (

**b**) GPS S2L; (

**c**) GPS S5Q; (

**d**) GLONASS S1C; (

**e**) GLONASS S2C; (

**f**) Galileo S1C; (

**g**) Galileo S5Q; (

**h**) Galileo S6C; (

**i**) Galileo S7Q; (

**j**) Galileo S8Q; (

**k**) BDS S2I; (

**l**) BDS S6I; (

**m**) BDS S7I.

**Figure 15.**Mean fusion accuracy analysis of multi-frequency retrieval results in the four GNSS systems: (

**a**) GPS multi-frequency fusion; (

**b**) GLONASS multi-frequency fusion; (

**c**) Galileo multi-frequency fusion; (

**d**) BDS multi-frequency fusion.

**Table 1.**Multi-GNSS and multi-frequency SNR types and description information provided by the P387 station.

Satellite System | Frequency Band/Frequency (MHz) | Channel or Code | Carrier Phase | SNR Types | Yes/No Use |
---|---|---|---|---|---|

GPS | L1/1575.42 | C/A | L1C | S1C | YES |

Z-tracking and similar (AS on) | L1W | S1W | |||

L2/1227.60 | L2C(L) | L2L | S2L | ||

Z-tracking and similar (AS on) | L2W | S2W | |||

L5/1176.45 | Q | L5Q | S5Q | ||

GLONASS | G1/(1602 + k*9/16) K = −7 … + 12 | C/A | L1C | S1C | YES |

G2/(1246 + k*7/16) | C/A | L2C | S2C | ||

Galileo | E1/1575.42 | C | L1C | S1C | YES |

E5a/1176.45 | Q | L5Q | S5Q | ||

E6/1278.75 | C | L6C | S6C | ||

E5b/1207.14 | Q | L7Q | S7Q | ||

E5(E5a + E5b)/1191.795 | Q | L8Q | S8Q | ||

BDS | B1/1561.098 | I | L1I | S2I | YES |

B3/1268.52 | I | L6I | S6I | ||

B2/1207.140 | I | L7I | S7I | ||

QZSS | L1/1575.42 | C/A | L1C | S1C | NO |

L2/1227.60 | L2C(L) | L2L | S2L | ||

L5/1176.45 | Q | L5Q | S5Q | ||

SBAS | L1/1575.42 | C/A | L1C | S1C | NO |

L5/1176.45 | I | L5I | S5I |

Satellite System | SNR Types | Mean LSP of 4 Days/m |
---|---|---|

GPS | S1C | 1.834 |

S2L | 1.910 | |

S5Q | 1.918 | |

GLONASS | S1C | 1.815 |

S2C | 1.914 | |

Galileo | S1C | 1.813 |

S5Q | 1.866 | |

S6C | 1.854 | |

S7Q | 1.844 | |

S8Q | 1.854 | |

BDS | S2I | 1.810 |

S6I | 1.826 | |

S7I | 1.830 |

**Table 3.**R and RMSE between multi-GNSS and multi-frequency GNSS-IR snow depth retrieval results and PBO snow depth.

Satellite System | SNR Types | R | RMSE/m |
---|---|---|---|

GPS | S1C | 0.90 | 0.09 |

S2L | 0.99 | 0.05 | |

S5Q | 0.98 | 0.08 | |

GLONASS | S1C | 0.83 | 0.10 |

S2C | 0.97 | 0.10 | |

Galileo | S1C | 0.88 | 0.08 |

S5Q | 0.95 | 0.07 | |

S6C | 0.94 | 0.06 | |

S7Q | 0.96 | 0.05 | |

S8Q | 0.95 | 0.06 | |

BDS | S2I | 0.86 | 0.09 |

S6I | 0.95 | 0.05 | |

S7I | 0.93 | 0.06 |

**Table 4.**Comparison of different frequency signal in the multi-GNSS system retrieval results; multi-frequency mean fusion accuracy increases in R and decreases in the RMSE.

Satellite System | SNR Types | Increases in R | Decreases in the RMSE |
---|---|---|---|

GPS | S1C | 9.1% | 55.6% |

S2L | 0.0% | 20.0% | |

S5Q | 1.0% | 50.0% | |

GLONASS | S1C | 11.7% | 30.0% |

S2C | −3.2% | 30.0% | |

Galileo | S1C | 9.3% | 37.5% |

S5Q | 2.1% | 28.5% | |

S6C | 3.1% | 16.7% | |

S7Q | 1.0% | 0.0% | |

S8Q | 2.1% | 16.7% | |

BDS | S2I | 9.5% | 44.4% |

S6I | 0.0% | 0.0% | |

S7I | 2.1% | 16.7% |

**Table 5.**Comparison of multi-frequency mean fusion; multi-GNSS system fusion accuracy increases in R and decreases in the RMSE.

Satellite System | Increases in R | Decreases in the RMSE |
---|---|---|

GPS | 0.0% | 25.0% |

GLONASS | 5.1% | 57.1% |

Galileo | 2.0% | 40% |

BDS | 4.0% | 40% |

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## Share and Cite

**MDPI and ACS Style**

Tu, J.; Wei, H.; Zhang, R.; Yang, L.; Lv, J.; Li, X.; Nie, S.; Li, P.; Wang, Y.; Li, N.
GNSS-IR Snow Depth Retrieval from Multi-GNSS and Multi-Frequency Data. *Remote Sens.* **2021**, *13*, 4311.
https://doi.org/10.3390/rs13214311

**AMA Style**

Tu J, Wei H, Zhang R, Yang L, Lv J, Li X, Nie S, Li P, Wang Y, Li N.
GNSS-IR Snow Depth Retrieval from Multi-GNSS and Multi-Frequency Data. *Remote Sensing*. 2021; 13(21):4311.
https://doi.org/10.3390/rs13214311

**Chicago/Turabian Style**

Tu, Jinsheng, Haohan Wei, Rui Zhang, Lei Yang, Jichao Lv, Xiaoming Li, Shihai Nie, Peng Li, Yanxia Wang, and Nan Li.
2021. "GNSS-IR Snow Depth Retrieval from Multi-GNSS and Multi-Frequency Data" *Remote Sensing* 13, no. 21: 4311.
https://doi.org/10.3390/rs13214311