  This paper studies the exploitation of networked integrated sensing and
communications (ISAC) to support low-altitude economy (LAE), in which a set of
networked ground base stations (GBSs) transmit wireless signals to
cooperatively communicate with multiple authorized unmanned aerial vehicles
(UAVs) and concurrently use the echo signals to detect the invasion of
unauthorized objects in interested airspace. Under this setup, we jointly
design the cooperative transmit beamforming at multiple GBSs together with the
trajectory control of authorized UAVs and their GBS associations, for enhancing
the authorized UAVs' communication performance while ensuring the sensing
requirements for airspace monitoring. In particular, our objective is to
maximize the average sum rate of authorized UAVs over a particular flight
period, subject to the minimum illumination power constraints for sensing over
the interested airspace, the maximum transmit power constraints at individual
GBSs, and the flight constraints at UAVs. This problem is non-convex and
challenging to solve, due to the involvement of integer variables and the
coupling of optimization variables. To solve this non-convex problem, we
propose an efficient algorithm by using the techniques of alternating
optimization (AO), successive convex approximation (SCA), and semi-definite
relaxation (SDR). Numerical results show that the obtained transmit beamforming
and UAV trajectory designs in the proposed algorithm efficiently balance the
tradeoff between the sensing and communication performances, thus significantly
outperforming various benchmarks.
