  Utilization of directional antennas is a promising solution for efficient
spectrum sensing and accurate source localization and tracking. Spectrum
sensors equipped with directional antennas should constantly scan the space in
order to track emitting sources and discover new activities in the area of
interest. In this paper, we propose a new formulation that unifies
received-signal-strength (RSS) and direction of arrival (DoA) in a compressive
sensing (CS) framework. The underlying CS measurement matrix is a function of
beamforming vectors of sensors and is referred to as the propagation matrix.
Comparing to the omni-directional antenna case, our employed propagation matrix
provides more incoherent projections, an essential factor in the compressive
sensing theory. Based on the new formulation, we optimize the antenna beams,
enhance spectrum sensing efficiency, track active primary users accurately and
monitor spectrum activities in an area of interest. In many practical scenarios
there is no fusion center to integrate received data from spectrum sensors. We
propose the distributed version of our algorithm for such cases. Experimental
results show a significant improvement in source localization accuracy,
compared with the scenario when sensors are equipped with omni-directional
antennas. Applicability of the proposed framework for dynamic radio cartography
is shown. Moreover, comparing the estimated dynamic RF map over time with the
ground truth demonstrates the effectiveness of our proposed method for accurate
signal estimation and recovery.
