Performance Of Time Delay Estimation Research Articles

Exploring super-gaussianity toward robust information-theoretical time delay estimation

Time delay estimation (TDE) is a fundamental component of speaker localization and tracking algorithms. Most of the existing systems are based on the generalized cross-correlation method assuming gaussianity of the source. It has been shown that the distribution of speech, captured with far-field microphones, is highly varying, depending on the noise and reverberation conditions. Thus the performance of TDE is expected to fluctuate depending on the underlying assumption for the speech distribution, being also subject to multi-path reflections and competitive background noise. This paper investigates the effect upon TDE when modeling the source signal with different speech-based distributions. An information theoretical TDE method indirectly encapsulating higher order statistics (HOS) formed the basis of this work. The underlying assumption of Gaussian distributed source has been replaced by that of generalized Gaussian distribution that allows evaluating the problem under a larger set of speech-shaped distributions, ranging from Gaussian to Laplacian and Gamma. Closed forms of the univariate and multivariate entropy expressions of the generalized Gaussian distribution are derived to evaluate the TDE. The results indicate that TDE based on the specific criterion is independent of the underlying assumption for the distribution of the source, for the same covariance matrix.

Performance Optimization of Time Delay Estimation Based on Chirp Spread Spectrum Using ESPRIT

In this letter, we analyze the effect of the size of observed data on the performance of time delay estimation (TDE) in the chirp spread spectrum (CSS) system. By adjusting the size of observed data, we reduce the effect of DC offsets, which would otherwise degrade the performance of TDE based on CSS, and we optimize the performance of TDE in CSS system. Finally, we derive the optimal size of observed data of TDE in CSS system.

음성 신호를 이용한 시간지연 추정에 미치는 영향들에 관한 연구

Since it needs the light computational load and small database, sound source localization method using time delay of arrival(TDOA method) is applied at many research fields such as a robot auditory system, teleconferencing and so on. Researches for time delay estimation, which is the most important thing of TDOA method, had been studied broadly. However studies about factors for time delay estimation are insufficient, especially in case of real environment application. In 1997, Brandstein and Silverman announced that performance of time delay estimation deteriorates as reverberant time of room increases. Even though reverberant time of room is same, performance of estimation is different as the specific part of signals. In order to know that reason, we studied and analyzed the factors for time delay estimation using speech signal and room impulse response. In result, we can know that performance of time delay estimation is changed by different R/D ratio and signal characteristics in spite of same reverberant time. Also, we define the performance index(PI) to show a similar tendency to R/D ratio, and propose the method to improve the performance of time delay estimation with PI.

Transform-Domain Adaptive Constrained Normalized-LMS Filtering Scheme for Time Delay Estimation

The convergence speed of the conventional adaptive LMS algorithms for time delay estimation (TDE) is highly dependent on the spectral distribution of the desired random source signals of interest, thus the performance of TDE might be degraded, dramatically. To solve this problem, in this letter, a DCT-transform domain constrained adaptive normalized-LMS filtering scheme, referred to as the adaptive constrained DCT-LMS algorithm, is devised for TDE. Computer simulation results verify that the proposed scheme can be used to achieve desired performance, for input random signals with different spectral distributions; it outperforms the unconstrained DCT-LMS and time-domain constrained adaptive LMS algorithms.

Source Localization With Distributed Sensor Arrays and Partial Spatial Coherence

Multiple sensor arrays provide the means for highly accurate localization of the (x,y) position of a source. In some applications, such as microphone arrays receiving aeroacoustic signals from ground vehicles, random fluctuations in the air lead to frequency-selective coherence losses in the signals that arrive at widely separated sensors. We present performance analysis for localization of a wideband source using multiple, distributed sensor arrays. The wavefronts are modeled with perfect spatial coherence over individual arrays and frequency-selective coherence between distinct arrays, and the sensor signals are modeled as wideband, Gaussian random processes. Analysis of the Cramer-Rao bound (CRB) on source localization accuracy reveals that a distributed processing scheme involving bearing estimation at the individual arrays and time-delay estimation (TDE) between sensors on different arrays performs nearly as well as the optimum scheme while requiring less communication bandwidth with a central processing node. We develop Ziv-Zakai bounds for TDE with partially coherent signals in order to study the achievability of the CRB. This analysis shows that a threshold value of coherence is required in order to achieve accurate time-delay estimates, and the threshold coherence value depends on the source signal bandwidth, the additive noise level, and the observation time. Results are included based on processing measured aeroacoustic data from ground vehicles to illustrate the frequency-dependent signal coherence and the TDE performance.

Alpha-stable modeling of noise and robust time-delay estimation in the presence of impulsive noise

A new representation of audio noise signals is proposed, based on symmetric /spl alpha/-stable (S/spl alpha/S) distributions in order to better model the outliers that exist in real signals. This representation addresses a shortcoming of the Gaussian model, namely, the fact that it is not well suited for describing signals with impulsive behavior. The /spl alpha/-stable and Gaussian methods are used to model measured noise signals. It is demonstrated that the /spl alpha/-stable distribution, which has heavier tails than the Gaussian distribution, gives a much better approximation to real-world audio signals. The significance of these results is shown by considering the time delay estimation (TDE) problem for source localization in teleimmersion applications. In order to achieve robust sound source localization, a novel time delay estimation approach is proposed. It is based on fractional lower order statistics (FLOS), which mitigate the effects of heavy-tailed noise. An improvement in TDE performance is demonstrated using FLOS that is up to a factor of four better than what can be achieved with second-order statistics.

A new cepstral prefiltering technique for estimating time delay under reverberant conditions

A microphone array can be used for hands-free acquisition of speech under reverberant conditions. This requires knowledge about the desired talker location, which can be obtained by estimating the time delays between the signals received by one or more pairs of spatially separated microphones. However, in a typical audio-conference room, strong reverberation is usually present and can have disastrous effects on the performance of conventional time delay estimation (TDE) methods. In this article, we present and evaluate a new cepstral prefiltering technique which can be applied on the received signals before the actual TDE in order to obtain a more accurate estimate of the delay in a typical reverberant environment. The technique is based on the estimation and the subtraction of the minimum-phase component (MPC) of the channel cepstrum from the total cepstrum of each microphone signal. So, in the same way that it is necessary in certain TDE methods to estimate the power spectral densities of the signals of interest from the received data, the new method requires the estimation of the channel MPC in the cepstral domain. The performances of a TDE system with and without cepstral prefiltering are compared via Monte-Carlo simulations for fixed random and speech sources as well as for a moving random source. The results clearly demonstrate the beneficial effects of the new cepstral prefiltering technique on TDE performance when the source is fixed or slowly moving.

Performance of time-delay estimation in the presence of room reverberation

Synthetic microphone signals generated with the image model technique are used to study the effects of room reverberation on the performance of the maximum likelihood (ML) estimator of the time delay, in which the estimate is obtained by maximizing the cross correlation between filtered versions of the microphone signals. The results underscore the adverse effects of reverberation on the bias, variance and probability of anomaly of the ML estimator. Explanations of these effects are provided.

Theoretical signal‐to‐noise gain formulas for energy signal bicorrelation and tricorrelation detection

In the past the authors have examined energy signal detection and time delay estimation performance of ordinary and higher‐order correlations using Monte Carlo simulations and hypothesis testing [for example, Pflug et al., J. Acoust. Soc. Am. 91, 2763 (1992)]. For some circumstances higher‐order detector performance and SNR gains can be predicted theoretically based on third‐ and fourth‐order moments. SNR gain formulas for higher‐order detectors have been derived for a probability of detection of 0.5 and are discussed in this paper. Comparisons of these theoretical results are made to simulations with a model signal whose moments can be varied. Validity of the theoretical results is confirmed with eight diverse test signals which have been used in previous simulation studies. The formulas make possible the calculation of minimum third, and fourth‐order moment values needed for the bicorrelation and tricorrelation detectors, respectively, to outperform the cross‐correlation detector. [Research supported by Office of Naval Research, Program Element 61153N, with technical management provided by NRLSSC.]

Time delay estimation using the cross bispectrum

The cross bispectrum phase can be effectively used to estimate the time required for a nonGaussian signal to propagate between a pair of spatially separated sensors in the presence of highly correlated Gaussian noise. The authors present a consistent estimator of the phase of the cross bispectrum, derive the exact distribution of the phase of a complex Gaussian sample bispectrum, and show that in most cases the exact distribution can be approximated by a Gaussian distribution. Using this Gaussian approximation, the authors derive the variance of the time delay estimate computed from the sample cross bispectrum of a signal in additive correlated noise. These results allow the performance of time delay estimators based on the cross bispectrum phase to be quantified as a function of the sample size, the skewness of the signal, the signal-to-noise ratio (SNR), and the noise correlation.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

Time-delay estimation performance in a scattering medium

The effects of a scattering medium on the performance of time-delay estimation are considered. The medium is assumed to exhibit angular scattering, causing angular (as well as delay) dispersion and hence loss of signal coherence across the array aperture. Both the variance (via the Cramer-Rao bound) and the bias introduced in the time-delay estimates are studied. The results have been converted to bearing and range error standard deviation and bias. It is shown that there is an optimum range of values for the separation distance between the sensors in the design of an array for time-delay estimation, for range and bearing measurements.

Time Delay Estimation Performance in a Scattering Medium

The effects of a scattering medium on the performance of time delay estimation are considered. The medium is assumed to exhibit angular scattering, causing angular (as well as delay) dispersion and hence loss of signal coherence across the array aperture. Both the variance (via the Cramer-Rao bound) and the bias introduced in the time-delay estimates are studied. The results have been converted to bearing and range error standard deviation and bias. It is found from these studies that there is an optimum range of values for the separation distance between the sensors in the design of an array for time delay estimation, for range and bearing measurements.