A New 3-D Positioning Method Using Zero-Doppler Image Matching for High-Squint Small SAR Satellite

Small-sized satellite constellations equipped with very-high-resolution synthetic aperture radar (SAR) sensors provide frequent revisit times and diverse viewing geometries. These properties create opportunities for real time monitoring of unidentified artificial structures through 3D positioning. SAR radargrammetry provides a practical means to achieve this by estimating the 3D position of targets from multiple SAR acquisitions. However, traditional radargrammetric techniques face challenges in target matching due to significant appearance differences caused by varying viewing geometries. Moreover, they often relied on external topographic data, which can introduce distortion or mismatches—particularly when used with sub-meter-resolution SAR imagery. In order to address these limitations, this study proposes a novel 3D positioning technique that leveraged only SAR images, without requiring external data. The core of the method involved converting zero-Doppler image patches using a reference ellipsoid model, enabling robust target matching by aligning targets into a common representation. A pixel-wise look-up table (LUT) was constructed to establish spatial correspondences between the original and generated images, allowing precise extraction of Doppler centroid frequencies and slant ranges for each target pixel. The 3D position was subsequently estimated via radargrammetric stereo processing. Validation using corner reflector (CR) arrays and real-world applications involving infrastructure targets and mountainous terrain confirmed the robustness and accuracy of the proposed approach. The results demonstrated that the technique enables reliable object level positioning.