20072018 52nd Asilomar Conference on Signals, Systems, and ComputersRequires access

Lower Bound on Time-Delay Estimation Error of UWB Signals

Hicham Anouar, Aawatif Menouni Hayar, Raymond Knopp, Christian Bonnet

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Abstract

In this work, we study fundamental limitation to the performance of time-delay estimation schemes of IR-UWB signals. We are specially interested in deriving lower bound on the mean square error (MSE). As UWB systems are expected to operate at low signal-to-noise ratio (SNR) (80211.15.4 low-power low rate standard), the improved Ziv-Zakai lower bound (IZZLB) [1] is then more suited to characterize the lower bound on the MSE, than the Cramer-Rao lower bound (CRLB). We express then the lower bound on MSE of maximum likelihood estimator based on perfect knowledge of the 2nd order statistics of the received signal by mean of the IZZLB.

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What this paper is about

In this work, we study fundamental limitation to the performance of time-delay estimation schemes of IR-UWB signals. We are specially interested in deriving lower bound on the mean square error (MSE). As UWB systems are expected to operate at low signal-to-noise ratio (SNR) (80211.15.4 low-power low rate standard), the improved Ziv-Zakai lower bound (IZZLB) [1] is then more suited to characterize the lower bound on the MSE, than the Cramer-Rao lower bound (CRLB). We express then the lower bound on MSE of maximum likelihood estimator based on perfect knowledge of the 2nd order statistics of the received signal by mean of the IZZLB.

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Available abstract

In this work, we study fundamental limitation to the performance of time-delay estimation schemes of IR-UWB signals. We are specially interested in deriving lower bound on the mean square error (MSE). As UWB systems are expected to operate at low signal-to-noise ratio (SNR) (80211.15.4 low-power low rate standard), the improved Ziv-Zakai lower bound (IZZLB) [1] is then more suited to characterize the lower bound on the MSE, than the Cramer-Rao lower bound (CRLB). We express then the lower bound on MSE of maximum likelihood estimator based on perfect knowledge of the 2nd order statistics of the received signal by mean of the IZZLB.

Key concepts: Upper and lower bounds, Cramér–Rao bound, Estimator, Mean squared error, Signal-to-noise ratio (imaging), Algorithm, Computer science, Maximum likelihood

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