Fathin Nurzaman, Yuta Izumi, Motoyuki Sato, Koki Urano, Shima Kawamura, Josaphat Tetuko Sri Sumantyo, Kaoru Ota, Mianxiong Dong, and Wedyanto Kuntjoro, “Integration of ground-based markerless photogrammetry for the geocoding of a ground-based SAR observation,” in ISPRS Journal of Photogrammetry and Remote Sensing, Vol. 229, pp 323-335, Aug. 2025.
Abstract
A novel radar geocoding technique for ground-based Synthetic Aperture Radar (SAR) data has been introduced utilizing ground-based markerless photogrammetry. The technique offers a resource advantage, requiring only a consumer-grade camera. Combined with its markerless approach, it is fully independent of external data and remains non-invasive, which complements the strengths of ground-based radar. The ground-based photogrammetry involves taking photos from the radar’s position on the ground. This shared perspective between the radar measurements and photogrammetry ensures that the resulting 3D model aligns well with the radar data, as only the radar-illuminated surface is reconstructed, which facilitates the subsequent geocoding operation. However, the typically limited possibilities on the ground to acquire photos often result in a poor photogrammetric network. This suboptimal photogrammetric network causes distortion in the obtained 3D model, which is also caused by the nonexistence of ground control points associated with the markerless approach. A geometric correction method is proposed here, which removes this distortion by relying on the already available SAR image obtained from the ground-based radar measurement, owing to its absolute range measurement that is free from distortion. The distortion parameters were thoroughly examined, which includes the radial distortion typical of a suboptimal photogrammetric network, from which the transformation model is formulated. The 3D model is then restituted with the SAR image as reference using the transformation model, which effectively removes distortion and at the same time achieves the quality of alignment needed in the subsequent reprojection within the geocoding process.
The technique is being implemented in an ongoing ground-based SAR campaign monitoring a residential area. A significant improvement in tie point alignment between the 3D model and SAR image was demonstrated after applying the geometric correction process. The final geocoding result was compared with one obtained using a freely available global Digital Elevation Model (DEM), showing that the proposed technique yields satisfactory positional accuracy for the SAR signal. Improvement of mean positional error from 4.30 m to 1.69 m was achieved.