Underwater surveillance of large areas, such as the North Sea, is an increasingly relevant problem, driven by growing concern over activity targeting undersea infrastructure. A sensor network can address this by measuring the Direction of Arrival (DoA) of a target. Centralised tracking with an Extended Kalman Filter (EKF) requires every measurement to reach a central node, a communication cost that is prohibitive for remote, battery-powered sensors. This thesis instead develops a distributed solution, formulated as a consensus problem and solved using the Primal-Dual Method of Multipliers (PDMM). The EKF is reformulated as a distributed maximum a posteriori (MAP) problem, yielding EKF-PDMM. An equivalent, faster converging formulation is then derived in information form, exploiting the additive structure of the Extended Information Filter (EIF), yielding EIF-PDMM. EIF-PDMM is extended with gating for multi-target association (EIF-PDMM-MT) and with sensor selection to reduce active nodes by an order of magnitude in large networks (EIF-PDMM-