Optimum estimation of time delay by a generalized correlator

Hassab, Joseph C.; Boucher, R.

doi:10.1109/tassp.1979.1163269

Cited by 119 publications

(33 citation statements)

References 13 publications

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“…0 n g, 2 = =f P N ;1 n=0 q 1 (n)e ;j! 0 n g, 3 = <f P N ;1 n=0 q 2 (n)e ;j! 0 n g and 4 = =f P N ;1 n=0 q 2 (n)e ;j!…”

Section: The Proposed Methodsmentioning

confidence: 99%

Time-delay estimation for sinusoidal signals

2001

IEE Proc., Radar Sonar Navig.

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The problem of estimating the di erence in arrival times of a sinusoid received at two spatially separated sensors is considered. Given the sinusoidal frequency, a simple delay estimator using the phase di erence of the discrete time Fourier transforms (DTFTs) of the received signals is devised. With the use of periodogram, the algorithm is extended to estimate the delay when the frequency is unknown. The minimum achievable delay v ariances for the cases of known/unknown frequencies and constant/rectangular envelopes are also derived. The e ectiveness of the method is demonstrated by comparing with the performance bounds for di erent frequencies, envelopes and noise conditions.

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“…0 n g, 2 = =f P N ;1 n=0 q 1 (n)e ;j! 0 n g, 3 = <f P N ;1 n=0 q 2 (n)e ;j! 0 n g and 4 = =f P N ;1 n=0 q 2 (n)e ;j!…”

Section: The Proposed Methodsmentioning

confidence: 99%

Time-delay estimation for sinusoidal signals

2001

IEE Proc., Radar Sonar Navig.

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“…This GFDC differs from the generalized cross correlator (GCC) that has been used for radar and sonar signal processing for delay estimation [15,16]. The GCC is closely related to the coherence, a complex quantity that is the cross-power spectral density between two random processes divided by the product of their auto power spectral densities.…”

Section: Generalized Frequency-domain Correlator (Gfdc)mentioning

confidence: 99%

Symmetric Phase-Only Matched Filter (SPOMF) for Frequency-Domain Software GPS Receivers

Yang¹,

Miller

Nguyen

2007

Navigation

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ABSTRACT:The symmetric phase-only matched filter (SPOMF) is studied in this paper for processing GPS signals. The use of phase-only information is equivalent to equalizing the magnitude spectrum in contrast to the original spectrum that tapers off according to a sinc-function. This tends to accentuate the high frequency components corresponding to edges or transitions in the signals. As such, the SPOMF produces a much sharper peak (ideally a Dirac delta function) that is more accurate in timing and less sensitive to multipath. In addition, the same operation is applicable to both a binary phase shift keying (BPSK) modulated signal such as the GPS C/A-code and P(Y)-code and a binary offset carrier (BOC) modulation such as the GPS M-code and Galileo codes. More importantly, it only produces a single matching peak regardless of which modulation code is used.

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“…GCC requires knowledge of the signal and noise spectra. Some of the commonly used prefilters include the Roth processor, the smoothed coherent transform, the phase transform, the Eckart filter, the Hannan-Thomson processor, the Hassab-Boucher processor and the Wiener processor [11][12][13]. The prefilters, in general, enhance the frequency bands where the signal is dominant and attenuate the frequency bands where noise is dominant [11].…”

Section: Introductionmentioning

confidence: 99%

Passive acoustic localisation using blind Gauss–Markov estimate with spectral estimation at each sensor

Choudhary

Bahl

Kumar

2013

IET Radar, Sonar & Navigation

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Time-delay estimation has essential applications in the field of radar, sonar and robotics. For a very distant source, timedelay vector estimation across an M-sensor array is realised using the generalised cross-correlation (GCC) function and the estimates combined with their covariance matrix, expressed in terms of a priori known signal and noise spectra, to yield a linear minimum variance unbiased estimator, known as the Gauss-Markov Estimate. In the absence of a priori information, spectral estimation has to be done at one of the sensors. For close range sources, the use of amplitude attenuation information across the array will improve this estimate further. This study presents a new amplitude information related Gauss-Markov estimate, which calculates the power spectral density (PSD) at all the sensors of the array and gives more accurate time delay estimates in terms of the mean-square error when compared to the earlier constant amplitude-based technique using the PSD at the closest sensor. The performance has been evaluated against signal-to-noise ratio for varying distance of a source from the receiving array. The results have been verified by simulations and experiments for a two-dimensional source localisation problem.

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Optimum estimation of time delay by a generalized correlator

Cited by 119 publications

References 13 publications

Time-delay estimation for sinusoidal signals

Time-delay estimation for sinusoidal signals

Symmetric Phase-Only Matched Filter (SPOMF) for Frequency-Domain Software GPS Receivers

Passive acoustic localisation using blind Gauss–Markov estimate with spectral estimation at each sensor

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