  Most existing works on dual-function radar-communication (DFRC) systems
mainly focus on active sensing, but ignore passive sensing. To leverage
multi-static sensing capability, we explore integrated active and passive
sensing (IAPS) in DFRC systems to remedy sensing performance. The multi-antenna
base station (BS) is responsible for communication and active sensing by
transmitting signals to user equipments while detecting a target according to
echo signals. In contrast, passive sensing is performed at the receive access
points (RAPs). We consider both the cases where the capacity of the backhaul
links between the RAPs and BS is unlimited or limited and adopt different
fusion strategies. Specifically, when the backhaul capacity is unlimited, the
BS and RAPs transfer sensing signals they have received to the central
controller (CC) for signal fusion. The CC processes the signals and leverages
the generalized likelihood ratio test detector to determine the present of a
target. However, when the backhaul capacity is limited, each RAP, as well as
the BS, makes decisions independently and sends its binary inference results to
the CC for result fusion via voting aggregation. Then, aiming at maximize the
target detection probability under communication quality of service
constraints, two power optimization algorithms are proposed. Finally, numerical
simulations demonstrate that the sensing performance in case of unlimited
backhaul capacity is much better than that in case of limited backhaul
capacity. Moreover, it implied that the proposed IAPS scheme outperforms
only-passive and only-active sensing schemes, especially in unlimited capacity
case.
