A New Result on Distributed Input and State Estimation for Heterogeneous Sensor Networks


An important research area in sensor networks is the design and analysis of distributed estimation algorithms for dynamic information fusion in the presence of heterogeneity resulting from (i) nonidentical information roles of nodes and (ii) nonidentical modalities of nodes. In particular, (i) implies that both active (i.e., subject to observations of a process of interest) and passive (i.e., subject to no observations) nodes can be present in the sensor network. Furthermore, (ii) implies that active nodes can observe different measurements from a process (e.g., a subset of active nodes can observe position measurements and the rest can observe velocity measurements for a target tracking problem). In this paper, we focus on heterogeneous sensor networks, sensor networks with (i) and (ii), and present a new distributed input and state estimation approach. In addition to the presented theoretical contribution including the stability and performance of the proposed estimation approach, an illustrative numerical example is also given to demonstrate its efficacy.

Meeting Name

ASME 2017 Dynamic Systems and Control Conference, DSCC 2017 (2017: Oct. 11-13, Tysons, VA)


Electrical and Computer Engineering

Keywords and Phrases

Identification (control systems); Motion planning; Multi agent systems; Networked control systems; Robot programming; Robustness (control systems); Sensor networks; State estimation; Target tracking; Vibrations (mechanical); Active node; Design and analysis; Distributed estimation; Dynamic information; Estimation approaches; Heterogeneous sensor networks; New results; Non-identical; Sensor nodes

International Standard Book Number (ISBN)


Document Type

Article - Conference proceedings

Document Version


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© 2017 American Society of Mechanical Engineers (ASME), All rights reserved.

Publication Date

01 Oct 2017