Minimum error rate detection: An adaptive bayesian approach

Abdelouahab Boudjellal

doi:10.1016/j.sigpro.2017.05.003

2017-11-01

PRE

Abdelouahab Boudjellal *

Karim Abed‐Meraim

Adel Belouchrani

Ph. Ravier

DOI：10.1016/j.sigpro.2017.05.003

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摘要

En 中文

This paper addresses the thresholding problem which is an important issue in detection theory. A new thresholding methodology is proposed, namely the Minimum Error Rate (MER), related to the minimization of the error probability instead of minimizing only the miss probability for a Constant False Alarm Rate (CFAR). In an adaptive detection scheme, the proposed thresholding technique is combined with Cell Averaging (CA) and Order-Statistics OS estimation methods giving birth to the (CA-MER) and (OS-MER) detectors. Their performance statistics are analyzed for both homogeneous and heterogeneous environments. Moreover, a simplified approximate threshold expression is proposed and its effect on the whole detection process is studied. Theoretical and numerical results show that the MER-based detectors operate better than the classical CFAR-based ones. In particular, the proposed method is shown to be robust w.r.t. estimation errors on the different parameters (priors). Comparative study of MER versus CFAR-based detectors used for the delay detection in multipath context show that OS-MER detector outperforms the OS-CFAR which induces more accurate mobile positioning. (C) 2017 Elsevier B.V. All rights reserved.

Keyword:

Bayesian MER detector

Cell-averaging

Order-statistics

Chi-2 targets

Interfering targets

Delay estimation