Time delay estimation algoritms for echo cancellation

The following case study describes how to eliminate echo in a VoIP network using delay estimation algorithms. It is known that echo with long transmission delays becomes more noticeable to users. Thus, time delay estimation, as a part of echo cancellation, is an important topic during transmission of voice signals over packetswitching telecommunication systems. An echo delay problem associated with IP-based transport networks is discussed in the following text. The paper introduces the comparative study of time delay estimation algorithm, used for estimation of the true time delay between two speech signals. Experimental results of MATLab simulations that describe the performance of several methods based on cross-correlation, normalized crosscorrelation and generalized cross-correlation are also presented in the paper

Adaptive phase transform processors for time delay estimation

Journal ArticleThis paper introduces two recursive realizations of the phase transform (PHAT) processor for time-delay estimation (TDE), using a simple one-pole low-pass filter and the least-mean-square (LMS) adaptive filter, respectively. It is shown that these adaptive methods are capable of tracking time-varying delay functions which correspond to moving sources or receivers, and are very effective in reducing the effect of interfering tonals which must be generated by the target as jamming signals to mask its movement. The performances of these methods are compared with those of other existing adaptive TDE algorithma via computer simulations

Temperature reconstruction and acoustic time of flight determination for boiler furnace exit temperature measurement

The furnace exit gas temperature (FEGT) is one of the fundamental parameters necessary to determine the energy balance of the boiler in a coal-fired power plant, and is thus beneficial to the production of reliable thermo-fluid models of its operation and the operation of the systems down and upstream. The continuous measurement of the FEGT would also be a useful indicator to predict, prevent and diagnose faults, optimize boiler operation and aid the design of heat transfer surfaces. Acoustic pyrometry, a technique that measures temperature based on the travel time of an acoustic wave in a gas, is investigated as a viable solution for continuous direct measurement of the FEGT. This study focuses specifically on using acoustic pyrometry to reconstruct the temperature profile at the furnace exit including methods for accurately determining the time of flight (TOF) of acoustic waves. An improved reconstruction technique using radial basis functions (RBF) for interpolation and a least squares algorithm is simulated and its performance was compared to cubic spline interpolation, regression and Lagrange interpolation by evaluating its reconstruction accuracy in terms of mean and root-mean-squared (RMS) error when reconstructing set temperature profiles. Various parameters including transceiver positions, grid divisions and time of flight error, are investigated in terms of how they inform acoustic pyrometry implementation. The improved RBF interpolation function managed to reconstruct complex temperature profiles and had a greater reconstruction accuracy than compared interpolation methods, improving on the accuracy of previous work done. Random acoustic path error was found to not be additive with reconstruction error however repeating acoustic TOF readings improved reconstruction accuracy to mitigate this effect. In general, it was also found that symmetrical transmitter/receiver positions produced more accurate reconstructions as well as positioning receivers/transceivers and grid lines closer to the furnace walls, where the greatest temperature change occurs. In addition to testing reconstruction methods, a low-cost experimental set-up was constructed to measure the time of flight. The focus of this study was on using various signal processing methods to determine the time of flight and evaluating their accuracy in the presence of noise. Methods such as threshold detection with bandpass filtering, cross correlation, generalized cross-correlation (GCC) and a new method developed employing variable notch filters with locations and widths based on repetitive frequencies identified in the noise with cross correlation. The performance of methods was experimentally tested under varying signal to noise ratios (SNR) and noise conditions. These SNR tests showed that cross-correlation methods produced more reliable TOF readings under lower SNRs than threshold detection methods. Under white noise the smooth coherent transform (SCOT) GCC variation proved to produce the most accurate results producing an average TOF error of 0.84 % up until a SNR of 1.4 before reducing in accuracy. In coloured noise (generated based on previous boiler recordings) the variable notch filter method with crosscorrelation was able to identify repetitive noise frequencies filter them out and ultimately produced results with an average TOF error of 1.99 % up until a SNR of 0.67, where the noise level exceeds that of the signal

ARTIFICIAL NEURAL NETWORK APPLICATION FOR THE TEMPORAL PROPERTIES OF ACOUSTIC PERCEPTION

Though acoustic perception is well established in literature, it seems to be insufficiently implemented in practice. Experimental results are excellent but a lot of issues arise when it comes to the application in real conditions. Using artificial neural networks makes acoustic signal processing very comfortable from the mathematical point of view. However, a great job has to be done in order to make it possible. The procedure includes data acquisition, filtering, feature extraction and selection. These techniques require much more resources than mere artificial neural networks and this represents a limiting factor for the implementation. The paper investigates the complete procedure of acoustic perception, in terms of time, in order to identify limitations

EXPERIMENTAL EVALUATION OF MODIFIED PHASE TRANSFORM FOR SOUND SOURCE DETECTION

The detection of sound sources with microphone arrays can be enhanced through processing individual microphone signals prior to the delay and sum operation. One method in particular, the Phase Transform (PHAT) has demonstrated improvement in sound source location images, especially in reverberant and noisy environments. Recent work proposed a modification to the PHAT transform that allows varying degrees of spectral whitening through a single parameter, andamp;acirc;, which has shown positive improvement in target detection in simulation results. This work focuses on experimental evaluation of the modified SRP-PHAT algorithm. Performance results are computed from actual experimental setup of an 8-element perimeter array with a receiver operating characteristic (ROC) analysis for detecting sound sources. The results verified simulation results of PHAT- andamp;acirc; in improving target detection probabilities. The ROC analysis demonstrated the relationships between various target types (narrowband and broadband), room reverberation levels (high and low) and noise levels (different SNR) with respect to optimal andamp;acirc;. Results from experiment strongly agree with those of simulations on the effect of PHAT in significantly improving detection performance for narrowband and broadband signals especially at low SNR and in the presence of high levels of reverberation

Acoustic transient TDOA estimation and discrimination

This thesis examines acoustic transient discrimination and Time Difference Of Arrival (TDOA) estimation for the purposes of estimating the position of a submarine in a sonobuoy field. Transient discrimination, for this thesis, is the process of telling different transients apart. Two algorithms are evaluated. One method is based on higher order statistics while the other is based on signal subspace techniques. Extensive simulations using synthetic transients were conducted to establish the performance of each algorithm in terms of discrimination and TDOA estimation. It was found that the bispectral algorithm gave better TDOA estimation at low SNRs while the subspace algorithm gave better TDOA estimation at high SNRs. For discrimination, it was found that the sub space algorithm gave consistent false alarm rates at all SNRs while the false alarm rate for the bispectral algorithm grew with increasing SNR.http://www.archive.org/details/acoustictransien00bennLieutenant Commander, South African NavyApproved for public release; distribution is unlimited

Spatial Error Concealment in Ad-hoc Audio Conferencing Systems

In this work we consider an ad-hoc audio conferensing system based on VoIP services in which the participants connect to the conference using mobile communication devices with wireless connectivity. To overcome possible quality problems in the wireless link, we propose improvements to the existing conferencing systems. Some networking modifications are suggested to increase the channel capacity and robustness from the conference server to multiple clients. On the other hand, for the improvement of the uplink quality, we suggest a new spatial error concealment method, where a backup device captures and sends the audio signals to the server together with the primary device. In the server the lost frames from the primary channel are estimated based on the backup signal. Several methods for estimating the primary signal based on the backup signal are studied. The results of the methods are evaluated by a psychoacoustic error metric based on Zwicker’s loudness model. An informal subjective test is also performed to compare the results of these methods in order to chose one for implementing on the real- time conferencing setup. Both objective and subjective tests show consistent results and confirm that usage of spatial error concealment improves significantly the audio quality in the primary signal