On-Board Geometric Rectification for Micro-Satellite Based on Lightweight Feature Database

Abstract

On-board processing is increasingly prevalent due to its efficient utilization of satellite resources. Among these resources, geometric rectification can significantly enhance positioning accuracy for subsequent tasks, such as object detection. This approach mitigates the heavy burden on downlink bandwidth and minimizes time delays by transmitting targeted patches rather than raw data. However, existing rectification methods are often unsuitable due to the limitations and conditions imposed on satellites. Factors like hardware quality, heat dissipation, storage space, and geographic positioning are frequently constrained and prone to inaccuracies. This paper proposes a novel on-board rectification method. The method introduces a two-step matching framework to address substantial positioning errors and incorporates a feature-compression strategy to reduce the storage space of reference patches. Quantitative and practical experiments demonstrate the method’s efficacy in terms of storage space, time efficiency, and geometric rectification accuracy.

GPU Acceleration for SAR Satellite Image Ortho-Rectification

“…Zhang et al [16] verified the substitutability of the RPC model for the rigorous imaging model of SAR from both theoretical and experimental aspects, demonstrating the feasibility of using the RPC model to fit SAR image imaging. The experimental results showed that the RPC model can achieve high fitting accuracy for SAR systems of different resolutions and can be used for the photogrammetric processing of SAR images.…”

“…Therefore, in order to adapt to the joint processing of multi-source remote sensing image data, generic positioning models emerged, among which the most widely used is the Rational Function Model (RFM) [12][13][14][15]. RFM uses a rational polynomial form to fit the rigorous model and was initially used for the geolocation of optical images [16][17][18]. With continuous research by scientists, RFM began to be gradually applied to the geolocation of SAR images [19][20][21].…”