Suppressing Clutter and Jammer Interference in UAS Radar Sensors Using Space-Time Adaptive Processing

Unmanned aerial systems (UAS), or drones, are becoming increasingly prevalent in various applications, such as precision agriculture, search and rescue operations, infrastructure inspection, package delivery, environmental monitoring, and the military, making efficient radar systems crucial. However, these systems operate in complex environments that are susceptible to electromagnetic interference and cybersecurity challenges. To address these challenges, a detailed model was developed that encapsulates the interaction of a monostatic radar with a moving target and a stationary barrage jammer. The research focused on the adaptive displaced phase centered antenna (ADPCA) technique, which was integrated into a six-element uniform linear antenna array to mitigate interference and bolster cybersecurity. The results show significant clutter and jammer interference suppression when analyzed in a matrix format within the MxQxN data cube. The weights of the ADPCA canceler exhibited an unprecedented ability to negate noise, producing a significant null within the clutter ridge and isolating the genuine target signal. This research provides vital insight into the potential of space-time adaptive processing algorithms within UAS radar systems, addressing both security and efficiency concerns. The findings illuminate the transformative role of STAP in refining radar efficiency, precision, and cybersecurity readiness in UAS, laying the foundation for future advancements in this domain.