Detection with Uncertainty in Target Direction for Dual Functional Radar and Communication Systems
Mateen Ashraf, Anna Gaydamaka, Dmitri Moltchanov, John Thompson, Mikko, Valkama, Bo Tan

TL;DR
This paper proposes an iterative optimization method for dual functional radar and communication systems that effectively manages target direction uncertainty, maximizing SCNR while satisfying communication QoS constraints.
Contribution
It introduces a novel alternating optimization approach with penalty and Dinkelbach methods to handle nonconvex problems in uncertain target direction scenarios.
Findings
Algorithm converges within 3 iterations.
SCNR performance remains stable across different target directions.
Proposed method outperforms existing approaches in effectiveness.
Abstract
Dual functional radar and communication (DFRC) systems are a viable approach to extend the services of future communication systems. Most studies designing DFRC systems assume that the target direction is known. In our paper, we address a critical scenario where this information is not exactly known. For such a system, a signal-to-clutter-plus-noise ratio (SCNR) maximization problem is formulated. Quality-of-service constraints for communication users (CUs) are also incorporated as constraints on their received signal-to-interference-plus-noise ratios (SINRs). To tackle the nonconvexity, an iterative alternating optimization approach is developed where, at each iteration, the optimization is alternatively performed with respect to transmit and receive beamformers. Specifically, a penalty-based approach is used to obtain an efficient sub-optimal solution for the resulting subproblem with…
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Taxonomy
TopicsRadar Systems and Signal Processing
