@inproceedings{3c3b83580c8b43f9a6ddff5652a3e70b,
title = "Risk-unbiased bound for random signal estimation in the presence of unknown deterministic channel",
abstract = "Estimation of a signal transmitted through a communication channel usually involves channel identification. This scenario can be modeled as random parameter estimation in the presence of unknown deterministic parameter. In this paper, we address the question of how accurately one can estimate a random signal intercepted by an array of sensors, subject to an unknown deterministic array response. The commonly used hybrid Cram{\'e}r-Rao bound (HCRB) is restricted to mean-unbiased estimation of all model parameters with no distinction of their character and leads to optimistic and unachievable performance analysis. Instead, A Bayesian Cram{\'e}r-Rao (CR)- type bound on the mean-square-error (MSE) is derived for the considered scenario. The bound is based on the risk-unbiased bound (RUB) which assumes risk-unbiased estimation of the signals of interest. Simulations show that the RUB provides a tight and achievable performance analysis for the MSE of conventional hybrid estimators.",
keywords = "MSE, combined minimum MSE-maximum likelihood (MS-ML), joint maximum a-posteriori probability-maximum likelihood (JMAP-ML), risk-unbiased bound",
author = "Shahar Bar and Joseph Tabrikian",
note = "Publisher Copyright: {\textcopyright} 2015 IEEE.; 6th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, CAMSAP 2015 ; Conference date: 13-12-2015 Through 16-12-2015",
year = "2015",
month = jan,
day = "1",
doi = "10.1109/CAMSAP.2015.7383838",
language = "English",
series = "2015 IEEE 6th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, CAMSAP 2015",
publisher = "Institute of Electrical and Electronics Engineers",
pages = "469--472",
booktitle = "2015 IEEE 6th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, CAMSAP 2015",
address = "United States",
}