Distributed adaptive state estimation and tracking by using active‐passive sensor networks. (13th January 2020)

• Record Type: Journal Article
• Authors: Raj, Akhilesh; Jagannathan, Sarangapani; Yucelen, Tansel
• Is Part Of: International journal of adaptive control and signal processing. Volume 34:Number 3(2020)
• Page Start: 330
• Page End: 353
• Publication Date: 2020-01-13
• Subjects: adaptive observer -- distributed estimation for linear systems -- Lyapunov stability -- Sensor networks; Adaptive control systems -- Periodicals; Adaptive signal processing -- Periodicals; 629.836
• DOI: 10.1002/acs.3088
• Languages: English
• ISSNs: 0890-6327

Abstract

Summary: Heterogeneous sensor networks (HSN) find a wide range of applications in the field of military and civilian environments, where sensor nodes are utilized to estimate the position of a target with both dynamics and control input being unknown for the purposes of tracking. In the HSN, nodes are considered active depending upon their ability to sense the target output while the others are taken passive. Accurate estimation requires local information exchange among the spatially located sensor nodes, so that the active nodes as well as the passive nodes converge simultaneously to the same value. 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 scheme is introduced via adaptive observer where the nodes are allowed to have different sensor modalities. Using the estimated information, a subset of active and passive nodes, referred to as mobile nodes, can track the moving target. By using a constant state feedback controller at each mobile node, the state and parameter estimation as well as the tracking errors are shown to be uniformly ultimately bounded. Simulation results verify theoretical claims.