In this study, a hybrid optoelectronic synthetic aperture radar (SAR) moving target detection and imaging (OCMTI) method is introduced to address the challenges faced when processing large volumes of SAR data while focusing on key moving targets. Traditional algorithms often demand substantial computational resources, with the Fourier transform representing a widely implemented yet computationally intensive operation (typically O(N²) or O(NlogN) complexity). In contrast, optical systems can perform Fourier transforms inherently at the speed of light. The OCMTI method leverages this advantage and integrates optical and electronic processing to enable the rapid detection and selective imaging of moving targets. First, imaging parameters are dynamically configured based on the velocity range of the moving targets of interest and multiple coarse images of the entire scene are generated using an optical system. These images are then processed using a computer-aided detection system to identify candidate targets, and each target is subjected to fine imaging and parameter estimation. The refined images of detected targets are finally integrated into a single image with a suppressed background. The OCMTI method can rapidly detect moving targets, and the time complexity of moving target detection is proportional to the number of image pixels. The correct detection rate for a single image can reach 97%. The efficiency of this method in detecting and imaging moving targets is experimentally validated, which reveals it as a promising solution for time-sensitive applications. The OCMTI method bridges optical speed with electronic flexibility, thereby advancing SAR systems toward real-time, target-oriented operations.

In planetary radar observations, accurately scaled inverse synthetic aperture radar (ISAR) images are essential for near-Earth asteroid (NEA) shape reconstruction, rotational-state estimation, and impact risk assessment. However, conventional ISAR cross-range scaling methods typically rely on time–frequency analysis or multidimensional parameter searches, resulting in high computational complexity and limited robustness under the low signal-to-noise ratio (SNR) conditions commonly encountered in NEA observations. To address this challenge, this paper proposes a joint ISAR phase autofocus and cross-range scaling framework based on adaptive phase tracking (APT). The method employs a multi-scale Laplacian of Gaussian (LoG) detector to extract isolated scatterers and reformulates Doppler chirp-rate estimation as a recursive state estimation problem. By adaptively tracking the cross-range Doppler phase of these scatterers, the target’s effective rotation velocity is directly estimated without exhaustive parameter searches. A unified phase compensation function is then constructed to simultaneously achieve range-dependent autofocus and cross-range scaling. Simulation results based on a three-dimensional NEA model with realistic planetary radar imaging parameters demonstrate the effectiveness of the proposed method in near-Earth asteroid imaging scenarios. Experimental results from a UAV turntable setup further verify its capability for cross-range scaling and phase autofocus in a controlled near-field ISAR imaging scenario. These results show that the proposed framework achieves high estimation accuracy and robustness with reduced computational cost, making it an efficient and reliable solution for practical ISAR imaging in challenging radar environments.