  In this paper, we investigate joint 3-dimensional (3D) trajectory planning
and resource allocation for rotary-wing unmanned aerial vehicle (UAV) synthetic
aperture radar (SAR) sensing. To support emerging real-time SAR applications
and enable live mission control, we incorporate real-time communication with a
ground station (GS). The UAV's main mission is the mapping of large areas of
interest (AoIs) using an onboard SAR system and transferring the unprocessed
raw radar data to the ground in real time. We propose a robust trajectory and
resource allocation design that takes into account random UAV trajectory
deviations. To this end, we model the UAV trajectory deviations and study their
effect on the radar coverage. Then, we formulate a robust non-convex
mixed-integer non-linear program (MINLP) such that the UAV 3D trajectory and
resources are jointly optimized for maximization of the radar ground coverage.
A low-complexity sub-optimal solution for the formulated problem is presented.
Furthermore, to assess the performance of the sub-optimal algorithm, we derive
an upper bound on the optimal solution based on monotonic optimization theory.
Simulation results show that the proposed sub-optimal algorithm achieves
close-to-optimal performance and not only outperforms several benchmark schemes
but is also robust with respect to UAV trajectory deviations.
