West Virginia University
This paper is to reliably estimate a vector of unknown deterministic parameters associated with an underlying function at a fusion center of a wireless sensor network based on its noisy samples made at distributed local sensors. A set of noisy samples of a deterministic function characterized by a finite set of unknown parameters to be estimated is observed by distributed sensors. The parameters to be estimated can be some attributes associated with the underlying function, such as its height, its center, its variances in different directions, or even the weights of its specific components over a predefined basis set. Each local sensor processes its observation and sends its processed sample to a fusion center through parallel impaired communication channels.