Achieving wide-area, near-real-time, and fine-detail Earth observation is crucial for advanced remote sensing applications in the future. This study presents high-resolution dual-axis bidirectional scanning (HRBS), an innovative Earth observation modality that achieves optimal balance between swath expansion and spatial resolution through vertical-axis reciprocating scanning. This imaging architecture exhibits substantial theoretical potential for cost-efficient deployment in future commercial Earth observation satellite constellations (EOSs), due to its inherent decoupling of scanning functionality from satellite platform maneuvers. To address the image motion degradation (IMD) caused by motion mismatches during wide-field scanning, this study proposes a multi-parameter optimized scanning strategy framework. First, we delineate the imaging principle of wide-field, high-resolution bidirectional time-delay integration (TDI) using a two-dimensional scanning mirror. Building on this foundation, we establish a multi-element model to quantify spatiotemporal matching errors (STMEs) and introduce an imaging quality evaluation metric. By integrating engineering constraints into the scanning trajectory solution space, we develop an iterative optimization method for bidirectional scanning paths coupled with a real-time adaptive row transfer frequency (RTF) adjustment strategy. Experimental implementation through high-fidelity numerical simulations validates optimized dual-axis scanning trajectories and detector RTF configurations. Comparative high-fidelity numerical simulations reveal that the optimized HRBS strategy reduces full-orbit phase residuals to below 0.1 pixels, theoretically satisfying stringent image quality requirements for this highly dynamic time-varying imaging modality. These advancements lay a solid theoretical foundation for HRBS, demonstrating its potential as a promising solution for future commercial Earth observation systems demanding both resolution and coverage efficiency, while potentially supporting high-precision remote sensing applications.
Wei et al. (Wed,) studied this question.
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