Cognitive ISAR for Congested RF Environments via Waveform Design and Data Recovery Strategies

This paper proposes and analyzes the concept of a cognitive inverse synthetic aperture radar (ISAR) ensuring spectral compatibility in crowded electromagnetic environments. To realize the cognitive paradigm, the perception is carried out by a spectrum sensing module providing the relevant spectral parameters of the sources in the environment. The action stage employs a tailored signal design process, synthesizing a radar waveform with bespoke spectral notches, enabling ISAR imaging over a wide spectral bandwidth without interfering with the other radio frequency (RF) sources. A key enabling requirement for the proposed application is the capability to successfully recover possible gaps in the collected data. This process is carried out resorting to advanced methods based on compressed sensing recovery strategy. The capabilities of the proposed system are assessed exploiting a dataset of drone measurements in the frequency band between 13 GHz and 15 GHz. Results highlight the effectiveness of the devised architecture to enable spectral compatibility while delivering high-quality ISAR images.