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

Statistical Mechanics and Visual Signal Processing

The nervous system solves a wide variety of problems in signal processing. In many cases the performance of the nervous system is so good that it apporaches fundamental physical limits, such as the limits imposed by diffraction and photon shot noise in vision. In this paper we show how to use the language of statistical field theory to address and solve problems in signal processing, that is problems in which one must estimate some aspect of the environment from the data in an array of sensors. In the field theory formulation the optimal estimator can be written as an expectation value in an ensemble where the input data act as external field. Problems at low signal-to-noise ratio can be solved in perturbation theory, while high signal-to-noise ratios are treated with a saddle-point approximation. These ideas are illustrated in detail by an example of visual motion estimation which is chosen to model a problem solved by the fly's brain. In this problem the optimal estimator has a rich structure, adapting to various parameters of the environment such as the mean-square contrast and the correlation time of contrast fluctuations. This structure is in qualitative accord with existing measurements on motion sensitive neurons in the fly's brain, and we argue that the adaptive properties of the optimal estimator may help resolve conlficts among different interpretations of these data. Finally we propose some crucial direct tests of the adaptive behavior.Comment: 34pp, LaTeX, PUPT-143

Rotating single-shot acquisition (RoSA) with composite reconstruction for fast high-resolution diffusion imaging

PURPOSE: To accelerate high-resolution diffusion imaging, rotating single-shot acquisition (RoSA) with composite reconstruction is proposed. Acceleration was achieved by acquiring only one rotating single-shot blade per diffusion direction, and high-resolution diffusion-weighted (DW) images were reconstructed by using similarities of neighboring DW images. A parallel imaging technique was implemented in RoSA to further improve the image quality and acquisition speed. RoSA performance was evaluated by simulation and human experiments. METHODS: A brain tensor phantom was developed to determine an optimal blade size and rotation angle by considering similarity in DW images, off-resonance effects, and k-space coverage. With the optimal parameters, RoSA MR pulse sequence and reconstruction algorithm were developed to acquire human brain data. For comparison, multishot echo planar imaging (EPI) and conventional single-shot EPI sequences were performed with matched scan time, resolution, field of view, and diffusion directions. RESULTS: The simulation indicated an optimal blade size of 48 × 256 and a 30 ° rotation angle. For 1 × 1 mm2 in-plane resolution, RoSA was 12 times faster than the multishot acquisition with comparable image quality. With the same acquisition time as SS-EPI, RoSA provided superior image quality and minimum geometric distortion. CONCLUSION: RoSA offers fast, high-quality, high-resolution diffusion images. The composite image reconstruction is model-free and compatible with various diffusion computation approaches including parametric and nonparametric analyses. Magn Reson Med 79:264-275, 2018. © 2017 International Society for Magnetic Resonance in Medicine

Geosynchronous synthetic aperture radar for Earth continuous observation missions

This thesis belongs to the field of remote sensing, particularly Synthetic Aperture Radar (SAR) systems from the space. These systems acquire the signals along the orbital track of one or more satellites where the transmitter and receiver are mounted, and coherently process the echoes in order to form the synthetic aperture. So, high resolution images can be obtained without using large arrays of antennas. The study presented in this thesis is centred in a novel concept in SAR, which is known as Geosynchronous SAR or GEOSAR, where the transmitter and/or receiver are placed in a platform in a geostationary orbit. In this case, the small relative motions between the satellite and the Earth surface are taken to get the necessary motion to form the synthetic aperture and focus the image. The main advantage of these systems with respect to the current technology (where LEO satellites with lower height are considered) is the possibility of permanently acquire images from the same region thanks to the small motion of the platform. Therefore, the different possibilities in the orbital design that offer this novel technology as well as the geometric resolutions obtained in the final image have been firstly studied. However, the use of geosynchronous satellites as illuminators results in slant ranges between 35.000-38.000 Km, which are much higher than the typical values obtained in LEOSAR, under 1.000 Km. Fortunately, the slow motion of the satellite makes possible large integration of pulses during minutes or even hours, reaching Signal-to-Noise Ratio (SNR) levels in the order of LEO acquisitions without using high transmitted power or large antennas. Moreover, such large integration times, increases the length of the synthetic aperture to get the desired geometric resolutions of the image (in the order of a few meters or kilometres depending on the application). On the other hand, the use of long integration time presents some drawbacks such as the scene targets decorrelation, atmospheric artefacts due to the refraction index variations in the tropospheric layer, transmitter and receiver clock jitter, clutter decorrelation or orbital positioning errors; which will affect the correct focusing of the image. For this reason, a detailed theoretical study is presented in the thesis in order to characterize and model these artefacts. Several simulations have been performed in order to see their effects on the final images. Some techniques and algorithms to track and remove these errors from the focused image are presented and the improvement of the final focused image is analysed. Additionally, the real data from a GB-SAR (Ground-Based SAR) have been reused to simulate a long integration time acquisition and see the effects in the image focusing as well as to check the performance of compensation algorithms in the final image. Finally, a ground receiver to reuse signals of opportunity from a broadcasting satellite have been designed and manufactured. This hardware is expected to be an important tool for experimental testing in future GEOSAR analysis.Aquesta tesi s'emmarca dins de l'àmbit de la teledetecció, en particular, en els sistemes coneguts com a radar d'obertura sintètica (SAR en anglès) des de l'espai. Aquests sistemes adquireixen senyal al llarg de l'òrbita d'un o més satèl·lits on estan situats el transmissor i el receptor, i processa els ecos de forma coherent per a formar l'obertura sintètica. D'aquesta manera es poden aconseguir imatge d'alta resolució sense la necessitat d'emprar un array d'antenes molt gran. El treball realitzat en aquest estudi es centra en un nou concepte dins del món SAR que consisteix en l'ús de satèl·lits en òrbita geostacionària per a l'adquisició d'imatges, sistemes coneguts com a Geosynchronous SAR o GEOSAR. En aquest cas, els petits moviments relatius dels satèl·lits respecte de la superfície terrestre s'empren per a aconseguir el desplaçament necessari per a formar l'obertura sintètica i així obtenir la imatge. El principal avantatge d'aquests sistemes respecte a la tecnologia actual (on s'utilitzen satèl·lits en orbites més baixes LEO) és la possibilitat d'adquirir imatges d'una mateixa zona de forma permanent gràcies als petits desplaçaments del satèl·lit. Així doncs, en aquesta tesi s'estudien les diferents possibilitats en el disseny orbital que ofereixen aquests sistemes així com les resolucions d'imatge que s'obtindrien. Tot i així, l'ús de satèl·lits en òrbita geoestacionària, resulta en una distància entre el transmissor/receptor i l'escena entre 35000-38000 Km, molt més gran que les distàncies típiques en els sistemes LEO per sota dels 1000 Km. Tot i així, el moviment lent de les plataformes geostacionàries fa possible la integració de polsos durant minuts o hores, arribant a nivells acceptables de relació senyal a soroll (SNR) sense necessitat d'utilitzar potències transmeses i antenes massa grans. A més a més, aquesta llarga integració també permet assolir unes longituds d'obertura sintètica adients per a arribar a resolucions d'imatge desitjades (de l'ordre de pocs metres o kilòmetres segons l'aplicació). Malgrat això, l'ús de temps d'integració llargs té una sèrie d'inconvenients com poden ser la decorrelació dels blancs de l'escena, l'aparició d'artefactes atmosfèrics deguts als canvis d'índex de refracció en la troposfera, derives dels rellotges del transmissor i receptor, decorrelació del clutter o errors en el posicionament orbital, que poden afectar la correcta focalització de la imatge. Així doncs, en la tesi s'ha fet un detallat estudi teòric d'aquests problemes per tal de modelitzar-los i posteriorment s'han realitzat diverses simulacions per veure els seus efectes en una imatge. Diverses tècniques per a compensar aquests errors i millorar la qualitat de la imatge també s'han estudiat al llarg de la tesi. Per altra banda, dades reals d'un GB-SAR (SAR en una base terrestre) s'han reutilitzat per adaptar-les a una possible adquisició de llarga durada i veure així de forma experimental com afecta la llarga integració en les imatges i com millora l'enfocament després d'aplicar els algoritmes de compensació. Per últim, en la tesi es presenta un sistema receptor terrestre per a poder realitzar un anàlisi experimental del cas GEOSAR utilitzant un il·luminador d'oportunitat. Els primers passos en el disseny i la fabricació del hardware també es presenten en aquesta tes

Partial Update Algorithms and Echo Delay Estimation

In this paper, we introduce methods for extracting an echo delay between speech signals using adaptive filtering algorithms. Time delay estimation is an initial step for many speech processing applications. Conventional techniques that estimate a time difference of arrival between two signals are based on the peak determination of the generalized cross-correlation between the signals. To achieve a good precision and stability in estimation, the input sequences have to be multiplied by an appropriate weighting function. Regularly, the weighting functions are dependent on the signals power spectra. The spectra are generally unknown and have to be estimated in advance. An implementation of the time delay estimation via the adaptive least mean squares is analogous to estimating the Roth generalized cross-correlation weighting function. The estimated parameters using the adaptive filter have a smaller variance, because it avoids the need for the spectrum estimation. In the following, we discuss proportionate and partial-update adaptive techniques and consider their performance in term of delay estimation