Published in Mengoulis, A., Viswanathan, R., & Mahajan, A. (2002). Signal parameter estimation based on one-bit quantized data from multiple sensors. Proceedings of the Fifth International Conference on Information Fusion, 2002, v. 1 259-265. doi: 10.1109/ICIF.2002.1021159 ©2002 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.


We consider the problem of signal parameter estimation using a collection of distributed sensors. Each sensor quantizes its data to one-bit information and sends it to a fusion processor for the estimation of the parameter. Estimation of a constant signal in additive noise is considered. Since the emphasis is for the case of a moderately large number of sensors, we consider in this study two cases of estimation with 8 sensors and 20 sensors. We formulate several estimators based on one-bit sensor data and evaluate their mean squared error performances through simulation studies. Two parametric noise densities are simulated to ascertain the efficacies of various estimators. Results from this study show that robust estimation of parameter is possible by using a moderately large number of one-bit quantized sensor data.