Distributed State Estimation by Using Active-Passive Sensor Networks

Abstract

This paper proposes a novel adaptive observer for heterogeneous sensor networks (HSNs) to estimate state vector of an unknown target or process by using the sensed output when the input to the target/process is also not known. In an HSN, nodes are considered either active or passive depending upon their ability to sense the target output. The local information exchange among the nodes is dictated by a connected graph. By using the criterion of collective observability, a novel distributed adaptive estimation is introduced where the nodes are allowed to have different sensor modalities. Stability analysis shows uniform ultimate boundedness of the state estimation and parameter estimation errors. Simulation results are included to validate the proposed approach.