In the last few years, valuable research in frequency diverse arrays (FDAs) has been conducted. However, emphasis had mainly been on uniform linear arrays (ULAs) and uniform rectangular arrays (URAs). Not much attention has been devoted to other configurations. Circular symmetry of uniform circular arrays (UCAs) has been an attraction to researchers for several reasons such as the ability to scan azimuthally through 360°and better spatial resolutions. Motivated by the potential advantages of UCA, this letter presents an in-depth investigation of circular geometries in FDA radars. In this letter theory, analysis and basic beam steering in uniform circular frequency diverse arrays (UCFDAs) is presented along with comparison with linear and rectangular counterparts.
Null steering has been a challenge in radar communications for the past few decades. In this paper, a novel cognitive null steering technique in frequency diverse array radars using frequency offset selection is presented. The proposed system is a complete implementable framework that provides precise and deep null placement in the range and angle locations of the interference source. The proposed system is cognitive such that the transmitter and receiver are connected via a feedback loop. System extracts interference source location parameters from the radar scene using Multiple Signal Classification, a super resolution direction of arrival estimation technique. Neural networks known for minimum computation time, and good non-linear and non-parametric approximation have been utilized for prediction of next location of the interference source. Simulation results validate the proposed frequency offset selection by demonstrating precise and deep nulls at the desired locations.
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