A Delayed and Subsampled Wideband Sparse Array for Joint Angle and Frequency Estimation
Feiyu Wang (TU Delft - Signal Processing Systems)
G.J.T. Leus (TU Delft - Signal Processing Systems)
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Abstract
In this paper we consider the problem of joint wideband spectrum sensing and direction-of-arrival (DoA) estimation, where a number of uncorrelated narrowband sources spread over a wide frequency band impinge on a sparse linear array (SLA). To overcome the sampling rate bottleneck for wideband spectrum sensing, we rely on sub-Nyquist sampling for the receiver, and to resolve the sources both in the angle and frequency domain, an additional delayed branch is included for every antenna to gain an extra degree of freedom (DoF). Appropriately designing the delays at the different antennas allows us to use the contemporary machinery of co-array processing. We accordingly propose a joint eigenvalue decomposition (EVD) based algorithm to jointly estimate the angles and frequencies of the different sources with automatic pairing. Furthermore, as a consequence of the co-array processing, we can handle more sources than the number of physical antennas. Simulation results are included to corroborate our findings.