Quality of service resource management for a radar network

The resource management problem for a network of radars is formulated in this paper as a quality of service constrained optimisation problem. Conditions for the optimal solution to the problem are derived from the Karush-Kuhn-Tucker (KKT) conditions. An algorithm is presented that extends the single radar Q-RAM algorithm by satisfying the KKT conditions for the radar network case. The algorithm is demonstrated on a target tracking control problem, where it is shown that the proposed multiple sensor Q-RAM (MSQRAM) method enables an increased number of targets to be tracked with a better estimation error in comparison to locally optimised radar nodes

Sensor management for radar networks

Advancements in communication and information-processing technologies are driving an interest in networked radar systems, which are capable of compensating for the weaker attributes of the individual radars in the network. The role of a network of radar systems is to perform joint assessment of a surveillance region by fusing data generated at the individual radar nodes. To achieve best possible performance for the network, it is necessary to optimally configure the network and allocate its finite resources, such as radar time/energy budget, bandwidth, communication capacity and processing capacity. This chapter describes sensor and resources management techniques that can be applied to radar networks, focussing on radar network measurement scheduling and networked radar quality of service-based resources management