  In this paper, we study the trajectory optimization of a cellular-connected
unmanned aerial vehicle (UAV) which aims to sense the location of a target
while maintaining satisfactory communication quality with the ground base
stations (GBSs). In contrast to most existing works which assumed the target's
location is known, we focus on a more challenging scenario where the exact
location of the target to be sensed is unknown and random, while its
distribution is known a priori and stored in a novel target location
distribution map. Based on this map, the probability for the UAV to
successfully sense the target can be expressed as a function of the UAV's
trajectory. We aim to optimize the UAV's trajectory between two pre-determined
locations to maximize the overall sensing probability during its flight,
subject to a GBS-UAV communication quality constraint at each time instant and
a maximum mission completion time constraint. Despite the non-convexity and
NP-hardness of this problem, we devise three high-quality suboptimal solutions
tailored for it with polynomial complexity. Numerical results show that our
proposed designs outperform various benchmark schemes.
