Skip to Main Content
Wireless sensor networks deployed to perform surveillance and monitoring tasks have to operate under stringent energy and bandwidth limitations. These motivate well distributed estimation scenarios where sensors quantize and transmit only one, or a few bits per observation, for use in forming parameter estimators of interest. In a companion paper, we developed algorithms and studied interesting tradeoffs that emerge even in the simplest distributed setup of estimating a scalar location parameter in the presence of zero-mean additive white Gaussian noise of known variance. Herein, we derive distributed estimators based on binary observations along with their error-variance performance for unknown noise pdfs.