High-Resolution BVLOS Radar Imaging Method for Noncooperative Complex Maneuvering Targets

The rapid growth of commercial aviation and the increasing prevalence of small targets such as unmanned aerial vehicles (UAVs) have underscored the critical need for advanced beyond visual line of sight (BVLOS) radar situational awareness techniques, particularly for UAV detection. High-resolution imaging of BVLOS targets is paramount for accurate target sensing. Unlike traditional large-size targets, UAVs exhibit weak radar returns and complex, high-order time-varying dynamics, posing significant challenges for detection and tracking. Existing methods often focus on sensing imaging designed for large, less maneuverable targets, thereby limiting effectiveness in imaging UAVs with distinct high-order time-varying characteristics. To address these challenges, this article proposes a multiparameter collaborative sensing imaging framework driven by inverse synthetic aperture radar (ISAR) technology. Leveraging the principles of ISAR, the framework analyzes the relationship between far-field echo characteristics of targets and their complex 3-D high-order time-varying motion, establishing an innovative equation for high-order far-field echoes. Based on this analysis, we introduce a novel multiparameter dynamic imaging algorithm that exploits variations in target surface point scattering intensity to construct high-resolution sensing images of targets. This approach offers enhanced noise robustness compared to conventional cascaded-mode methods. Furthermore, extensive simulations and real-data experiments validate the superior performance of the proposed algorithm over existing methodologies.