On the Genericity Properties in Networked Estimation: Topology Design and Sensor Placement
In this paper, the authors consider networked estimation of linear, discrete-time dynamical systems monitored by a network of agents. In order to minimize the power requirement at the (possibly, battery-operated) agents, they require that the agents can exchange information with their neighbors only once per dynamical system time-step; in contrast to consensus-based estimation where the agents exchange information until they reach a consensus. It can be verified that with this restriction on information exchange, measurement fusion alone results in an unbounded estimation error at every such agent that does not have an observable set of measurements in its neighborhood. To overcome this challenge, state-estimate fusion has been proposed to recover the system observability.