Journal ArticleDOI
Fundamental limitations in passive time delay estimation--Part I: Narrow-band systems
Anthony J. Weiss,E. Weinstein +1 more
TLDR
A new method is presented to analyze the mean-square error performance of delay estimation schemes based on a modified (improved) version of the Ziv-Zakai lower bound (ZZLB) to yield the tightest results on the attainable system performance for a wide range of signal-to-noise ratio (SNR) conditions.Abstract:
Time delay estimation of a noise-like random signal observed at two or more spatially separated receivers is a problem of considerable practical interest in passive radar/sonar applications. A new method is presented to analyze the mean-square error performance of delay estimation schemes based on a modified (improved) version of the Ziv-Zakai lower bound (ZZLB). This technique is shown to yield the tightest results on the attainable system performance for a wide range of signal-to-noise ratio (SNR) conditions. For delay estimation using narrow-band (ambiguity-prone) signals, the fundamental result of this study is illustrated in Fig. 3. The entire domain of SNR is divided into several disjoint segments indicating several distinct modes of operation. If the available SNR does not exceed SNR 1 , signal observations from the receiver outputs are completely dominated by noise thus essentially useless for the delay estimation. As a result, the attainable mean-square error \bar{\epsilon}^{2} is bounded only by the a priori parameter domain. If SNR 1 2 , the modified ZZLB coincides with the Barankin bound. In this regime differential delay observations are subject to ambiguities. If SNR > SNR 3 the modified ZZLB coincides with the Cramer-Rao lower bound indicating that the ambiguity in the differential delay estimation can essentially be resolved. The transition from the ambiguity-dominated mode of operation to the ambiguity-free mode of operation starts at SNR 2 and ends at SNR 3 . This is the threshold phenomenon in time delay estimation. The various deflection points SNR i and the various segments of the bound (Fig. 3) are given as functions of such important system parameters as time-bandwidth product (WT), signal bandwidth to center frequency ratio (W/ω 0 ) and the number of half wavelengths of the signal center frequency contained in the spacing between receivers. With this information the composite bound illustrated in Fig. 3 provides the most complete characterization of the attainable system performance under any prespecified SNR conditions.read more
Citations
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Performance Evaluation of 3D-LOCUS Advanced Acoustic LPS
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Improved Lower Bounds on Time-of-Arrival Estimation Error in Realistic UWB Channels
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Target localisation techniques and tools for multiple-input multiple-output radar
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References
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Journal ArticleDOI
The generalized correlation method for estimation of time delay
TL;DR: In this paper, a maximum likelihood estimator is developed for determining time delay between signals received at two spatially separated sensors in the presence of uncorrelated noise, where the role of the prefilters is to accentuate the signal passed to the correlator at frequencies for which the signal-to-noise (S/N) ratio is highest and suppress the noise power.
Journal ArticleDOI
Time delay estimation for passive sonar signal processing
TL;DR: In this article, an overview of applied research in passive sonar signal processing estimation techniques for naval systems is presented, where the authors present a discussion of this problem in terms of estimating the position and velocity of a moving acoustic source.
Journal ArticleDOI
Optimum processing for delay-vector estimation in passive signal arrays
W. Hahn,Steven A. Tretter +1 more
TL;DR: The Cramer-Rao matrix bound for the vector delay estimate is derived, and used to show that either properly filtered beamformers or properly filtered systems of multiplier-correlators can be used to provide efficient estimates.
Journal ArticleDOI
Improved Lower Bounds on Signal Parameter Estimation
D. Chazan,Moshe Zakai,Jacob Ziv +2 more
TL;DR: An improved technique for bounding the mean-square error of signal parameter estimates is presented and the resulting bounds are independent of the bias and stronger than previously known bounds.
Journal ArticleDOI
Optimum signal processing for passive sonar range and bearing estimation
TL;DR: In this paper, the Cramer-Rao bound is used to determine an optimum signal processor for passive sonar target range and bearing estimation, where the sonar array consists of an M • element linear array of hydrophone point detectors.