# Geolocation Accuracy Validation of High-Resolution SAR Satellite Images Based on the Xianning Validation Field

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## Abstract

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## 1. Introduction

- The geometric performance of five representative high-resolution SAR satellites: ALOS, TerraSAR-X, Cosmo-SkyMed, RadarSat-2, and Chinese YG-3, is evaluated on the same benchmark with the rational function model (RFM) based on the Xianning validation field. The experimental analysis concerns the geolocation accuracies of the above satellite products and provides a reference for the application in the field of spaceborne SAR.
- An atmospheric delay correction model is used to evaluate the APD, and the experimental results show that a rough atmospheric correction result might have been added to the parameters of each satellite product in advance.
- A simulated images-based method is proposed to obtain ground control points (GCPs) for SAR images. It is proven effective by the experiment results, which provides an option for improving the geolocation accuracy on rough terrain areas.

## 2. Methods

#### 2.1. Rational Function Model for SAR Images

#### 2.2. Estimation of Atmospheric Propagation Delay

^{16}units (called total election content units, TECU), with typical TECUs ranging from 5 to 10.

^{3}). The constants are ${k}_{1}=77.6\text{}\mathrm{K}/\mathrm{mbar}$, ${k}_{2}=-6.0\text{}\mathrm{K}/\mathrm{mbar}$, ${k}_{3}=3.75\times {10}^{5}{\text{}\mathrm{K}}^{2}/\mathrm{mbar}$, and ${k}_{4}=1.45{\text{}\mathrm{m}}^{3}/\mathrm{g}$. In (7), the first term is the propagation delay related to dry air, and the second and third terms provide the effects related to water vapor. The effects of water droplets by the fourth term can be ignored concerning the total propagation delay [31].

#### 2.3. DEM-Based SAR Image Simulation

- Determine the range of the simulated image and the used DEM. Firstly, extract the covering areas of the DEM and convert them to geodetic coordinates under the WGS84 coordinate system via a transformation based on the RFM. Then, determine the range of the simulated image by combining the covering area of the DEM and real image.
- DEM interpolation and simulated image coordinate solution: Since the resolutions of the DEM and the real SAR image are inconsistent, a DEM with the same resolution as the real image is generated via bilinear interpolation. Then, the SAR image coordinates corresponding to each point on the DEM are solved by using the RFM, building the pixel-corresponding relation between the DEM and the simulated SAR image.
- Determine the backscattered power (grey value) of the simulated image. For one cell (X, Y, Z) in DEM, the coordinate of the corresponding pixel (x, y) in the simulated image can be calculated by using the RFM, and $\left\{\left({\mathrm{x}}_{\mathrm{i}},{\text{}\mathrm{y}}_{\mathrm{i}}\right),\mathrm{i}=1,2,3,4\right\}$ are grid points surrounding (x, y) (as shown in Figure 3). For each pixel in DEM, its contribution of grey value to four adjacent pixels is based on the size of the intersection area. As highlighted in Figure 3, the contribution of (x, y) to pixel $\left({\mathrm{x}}_{1},{\text{}\mathrm{y}}_{1}\right)$ is $\left(1-\mathrm{x}+{x}_{1}\right)\xb7\left(1-\mathrm{y}+{\mathrm{y}}_{1}\right)$. Due to the imaging characteristics of SAR and the geometric distortions such as layover, perspective shrinkage, and shadow, the actual relationship may not be a one-to-one correspondence. Some pixels may have higher brightness when one pixel in the simulated image consists of multiple ground units [39].

## 3. Experiment and Result Analysis

#### 3.1. Dataset and Test-Field Area

^{2}, with elevation ranging from 0 m to 1500 m. In our previous work, the optical high-resolution satellite images were validated in the same test field [40].

#### 3.2. Accuracy Assessment with GPS Measured GCPs

#### 3.3. Accuracy Assessment with Simulated GCPs from Simulated Image

## 4. Conclusions

## Author Contributions

## Funding

## Data Availability Statement

## Acknowledgments

## Conflicts of Interest

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**Figure 5.**(

**a**) Distribution of GPS GCPs in the Xianning test field. (

**b**) One GCP in the SAR image. (

**c**) Measurement photograph of surveyors in the field.

**Figure 6.**Details of simulated and real images. For each satellite, the top is the simulated image and the bottom is the real image.

**Figure 8.**Geolocation accuracy before and after atmospheric delay compensation. (solid diamonds ◆ represent outliers).

**Figure 9.**Geolocation accuracy with different numbers of GCPs. (solid diamonds ◆ represent outliers).

Satellite | ALOS | COSMO-SkyMed | RadarSat-2 | TerraSAR-X | YG-3 |
---|---|---|---|---|---|

Country | Japan | Italy | Canada | Germany | China |

Orbit height | 692 km | 620 km | 800 km | 515 km | 600 km |

Imaging time | 22 December 2008 | 22 July 2012 | 18 March 2013 | 24 July 2012 | 27 April 2012 |

Range spacing | 5.0 m | 3.0 m | 1.6 m | 1.2 m | 3.0 m |

Azimuth spacing | 3.0 m | 2.5 m | 2.8 m | 3.3 m | 3.0 m |

Width of image | 50 km × 70 km | 40 km × 40 km | 20 km × 20 km | 30 km × 50 km | 30 km × 30 km |

Incident angle | 34° | 32° | 31° | 30° | 30° |

Orbit direction and Look | Descending, right | Descending, right | Descending, right | Descending, right | Descending, right |

Imaging mode | Fine Resolution | Himage | UltraFine | StripMap | Strip |

Data level | Level 1.1 | SCS | SLC | SSC | L1B |

Polarization modes | HH | HH | HH | HH | HH |

Image size | 9344 × 18,432 | 19,604 × 22,334 | 8794 × 10,861 | 18,700 × 27,694 | 13,469 × 16,426 |

Satellite | Mean Ionospheric Slant Delay (m) | Mean Tropospheric Slant Delay (m) | Slant Range RMSE of CPs after Compensation (Pixels) |
---|---|---|---|

ALOS-PALSAR | 1.7854 | 3.2194 | 1.923 |

YG-3 | 0.0569 | 2.6988 | 29.765 |

COSMO-SkyMed | 0.0558 | 2.7848 | 2.540 |

TerraSAR-X | 0.0369 | 2.6785 | 4.323 |

RadarSat-2 | 0.1256 | 2.7071 | 2.665 |

Satellite | Number of GCPs | Number of CPs | RMSE of GCPs (Pixels) | RMSE of CPs (Pixels) | ||||
---|---|---|---|---|---|---|---|---|

Range | Azimuth | Plane | Range | Azimuth | Plane | |||

ALOS-PALSAR | 0 | 17 | —— | —— | —— | 1.870 | 3.278 | 3.773 |

4 | 13 | 0.211 | 0.858 | 0.884 | 1.693 | 2.916 | 3.372 | |

8 | 9 | 0.846 | 1.506 | 1.728 | 1.702 | 2.219 | 2.796 | |

YG-3 | 0 | 13 | —— | —— | —— | 27.645 | 3.129 | 27.822 |

4 | 9 | 0.411 | 0.486 | 0.637 | 1.905 | 2.425 | 3.084 | |

8 | 5 | 1.301 | 1.627 | 2.083 | 1.524 | 2.098 | 2.593 | |

COSMO-SkyMed | 0 | 24 | —— | —— | —— | 1.448 | 1.708 | 2.240 |

4 | 20 | 0.699 | 0.004 | 0.699 | 1.728 | 1.942 | 2.599 | |

8 | 12 | 0.977 | 1.257 | 1.592 | 1.467 | 1.442 | 2.057 | |

TerraSAR-X | 0 | 30 | —— | —— | —— | 1.506 | 1.826 | 2.367 |

4 | 26 | 0.327 | 0.056 | 0.332 | 1.324 | 1.477 | 1.984 | |

8 | 22 | 0.548 | 0.805 | 0.974 | 1.371 | 1.263 | 1.864 | |

RadarSat-2 | 0 | 12 | —— | —— | —— | 1.493 | 1.936 | 2.445 |

4 | 8 | 0.601 | 0.460 | 0.757 | 1.801 | 2.176 | 2.824 | |

8 | 4 | 1.189 | 1.082 | 1.489 | 1.489 | 1.752 | 2.300 |

Satellite | Number of GCPs | Number of CPs | RMSE of GCP (Pixels) | RMSE of CP (Pixels) | ||||
---|---|---|---|---|---|---|---|---|

Range | Azimuth | Plane | Range | Azimuth | Plane | |||

ALOS-PALSAR | 0 | 238 | —— | —— | —— | 1.104 | 8.065 | 8.140 |

4 | 234 | 0.080 | 0.178 | 0.196 | 0.341 | 1.038 | 1.092 | |

8 | 230 | 0.180 | 0.469 | 0.502 | 0.339 | 1.093 | 1.197 | |

YG-3 | 0 | 45 | —— | —— | —— | 28.885 | 1.253 | 28.912 |

4 | 41 | 0.427 | 0.345 | 0.549 | 0.741 | 0.849 | 1.127 | |

8 | 37 | 0.452 | 0.554 | 0.715 | 0.701 | 0.909 | 1.148 | |

COSMO-SkyMed | 0 | 29 | —— | —— | —— | 2.644 | 1.120 | 2.872 |

4 | 25 | 0.221 | 0.249 | 0.333 | 1.091 | 0.791 | 1.348 | |

8 | 21 | 0.483 | 0.455 | 0.664 | 0.932 | 0.819 | 1.240 | |

TerraSAR-X | 0 | 84 | —— | —— | —— | 5.630 | 1.635 | 5.863 |

4 | 80 | 0.325 | 0.430 | 0.538 | 0.836 | 0.937 | 1.255 | |

8 | 76 | 0.420 | 0.511 | 0.661 | 0.783 | 0.876 | 1.175 | |

RadarSat-2 | 0 | 183 | —— | —— | —— | 5.648 | 3.317 | 6.550 |

4 | 179 | 0.175 | 0.409 | 0.445 | 0.778 | 0.867 | 1.165 | |

8 | 175 | 0.445 | 0.598 | 0.745 | 0.704 | 0.812 | 1.075 |

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## Share and Cite

**MDPI and ACS Style**

Jiang, B.; Dong, X.; Deng, M.; Wan, F.; Wang, T.; Li, X.; Zhang, G.; Cheng, Q.; Lv, S. Geolocation Accuracy Validation of High-Resolution SAR Satellite Images Based on the Xianning Validation Field. *Remote Sens.* **2023**, *15*, 1794.
https://doi.org/10.3390/rs15071794

**AMA Style**

Jiang B, Dong X, Deng M, Wan F, Wang T, Li X, Zhang G, Cheng Q, Lv S. Geolocation Accuracy Validation of High-Resolution SAR Satellite Images Based on the Xianning Validation Field. *Remote Sensing*. 2023; 15(7):1794.
https://doi.org/10.3390/rs15071794

**Chicago/Turabian Style**

Jiang, Boyang, Xiaohuan Dong, Mingjun Deng, Fangqi Wan, Taoyang Wang, Xin Li, Guo Zhang, Qian Cheng, and Shuying Lv. 2023. "Geolocation Accuracy Validation of High-Resolution SAR Satellite Images Based on the Xianning Validation Field" *Remote Sensing* 15, no. 7: 1794.
https://doi.org/10.3390/rs15071794