ISSN : 1796-2056
Volume : 1    Issue : 2    Date : June 2006

Localized Recursive Estimation in Energy Constrained Wireless Sensor Networks
Bang Wang, Kee Chaing Chua, and Vikram Srinivasan
Page(s): 18-26
Full Text:
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This paper proposes a localized recursive estimation scheme for parameter estimation in wireless
sensor networks. Given any parameter of a target occurring at some location and time, a number of
sensors recursively estimate the parameter by using their local measurements of the parameter
that is attenuated with the distance between a sensor and the target location and corrupted by noise.
Compared with centralized estimation schemes that transmit all encoded measurements to a sink
(or a fusion center), the recursive scheme needs only to transmit the final estimate to a sink. When
the sink is faraway from the sensors and multihop communications have to be used, using localized
recursive estimation can help to reduce energy consumption and reduce network traffic load. A
sensor sequence with the fastest convergence rate is identified, by which the variance of estimation
error reduces faster than all other sequences. In the case of adjustable transmission power, a
heuristic has been proposed to find a sensor sequence with the minimum total transmission power
when performing the recursive estimation. Numerical examples have been used to compare the
performance of the proposed scheme with that of a centralized estimation scheme and have also
shown the effectiveness of the proposed heuristic.

Index Terms
parameter estimation, recursive estimation, energy efficiency, wireless sensor networks.