Batch Processing for Enhanced InISAR Imaging of Space Targets

High-precision 3D reconstruction of satellites is critical for automatic target recognition (ATR). This paper introduces a batch processing-based method to enhance the performance of interferometric inverse synthetic aperture radar (InISAR) imaging. By utilizing the phase information within the inverse synthetic aperture radar (ISAR) image sequence, the main error components of height estimation are accurately estimated via the ordinary least squares (OLS) method. Additionally, an arc interval determination strategy for optimizing the batch processing performance is proposed. To ensure accurate phase unwrapping in challenging imaging scenarios, a phase unwrapping method based on the minimum standard deviation criterion is also proposed. Simulation experiments validate the effectiveness and superiority of the proposed algorithms. Compared with the traditional two-ISAR-image InISAR imaging method, the batch processing approach improves the precision of height estimation by approximately 50% with an arc length of approximately 15°.