  The employment of unmanned aerial vehicles (UAVs) aligned with multistatic
sensing in integrated sensing and communication (ISAC) systems can provide
remarkable performance gains in sensing, by taking advantage of the cell-free
massive multiple-input multiple-output (mMIMO) architecture. Under these
considerations, in this paper, the achievable sensing
signal-to-noise-plus-interference ratio (SINR) of a cell-free mMIMO ISAC
UAV-based network is evaluated for two different deployments of UAVs, namely,
mobile and tethered. In both scenarios, a transmit precoder that jointly
optimizes the sensing and communication requirements subjected to power
constraints is designed. Specifically, for the scenario with mobile UAVs,
beyond the transmit precoding, we also optimize the position of the transmit
UAVs through particle swarm optimization (PSO). The results show that, although
tethered UAVs have a more efficient power allocation, the proposed position
control algorithm for the mobile UAVs can achieve a superior gain in terms of
sensing SINR.
