Interference cancellation in respiratory sounds via a multiresolution joint time-delay and signal-estimation scheme

Includes bibliographical references.This paper is concerned with the problem of cancellation of heart sounds from the acquired respiratory sounds using a new joint time-delay and signal-estimation (JTDSE) procedure. Multiresolution discrete wavelet transform (DWT) is first applied to decompose the signals into several subbands. To accurately separate the heart sounds from the acquired respiratory sounds, time-delay estimation (TDE) is performed iteratively in each subband using two adaptation mechanisms that minimize the sum of squared errors between these signals. The time delay is updated using a nonlinear adaptation, namely the Levenberg-Marquardt (LM) algorithm, while the function of the other adaptive system-which uses the block fast transversal filter (BFTF)—is to minimize the mean squared error between the outputs of the delay estimator and the adaptive filter. The proposed methodology possesses a number of key benefits such as the incorporation of multiple complementary information at different subbands, robustness in presence of noise, and accuracy in TDE. The scheme is applied to several cases of simulated and actual respiratory sounds under different conditions and the results are compared with those of the standard adaptive filtering. The results showed the promise of the scheme for the TDE and subsequent interference cancellation

Indoor source localization via direction finding technique

The location of an indoor transmitter such as a mobile phone in a building can be determined by measuring power or relative timing of the transmitted signal from simultaneous receivers located in the vicinity of the transmitter. A radio location finding system, consisting of two or more equivalent direction finders (DF), is placed outside of the building to pinpoint a transmitter located inside the building. Once the bearing angle is obtained from each DF system, the position of the transmitter is simply the intersection of the bearings from the direction finders. In our experiments, we mostly concentrated on the performance of suggested DF system for both indoor and outdoor applications. We implemented a one-coordinate direction finder to determine only the azimuthal angle of arrival (AOA) of the transmitted signal. Each DF system is composed of two dipole antenna array, receivers, and a laptop computer. A 4-channel sampling oscilloscope with a maximum sampling frequency of 4 Gs/s is used to receive and digitize the received signals. The digitized signals are then transferred to a laptop computer over a General Purpose Interface Board (GPIB) interface for further analysis to extract AOA information. Extraction of AOA information is based on time delay measurement technique. An electromagnetic wave impinging on two antennas separated by a distance of d experiences a time delay. The time difference of arrival between the received signals at the antenna terminals can easily be found by cross-correlating the signals. The delay is estimated as the time lag value where the peak of the cross correlation of two antenna signals occurs. Many experiments are realized in different environments such as anechoic chamber, an indoor RF laboratory and open air sites to measure the performance of direction finder. Using the data we have collected, we modeled a location finding system consisting of three equivalent DF systems located around a building. The simulation results show that the proposed simple DF system will work reasonably well for the location of a tranmitter inside a building. The proposed DF system is a trade-off between a highly sophisticated, but not easily deployable system such as a phased array DF and a simple amplitude comparison DF system. Accuracy of the system will be higher compared to that of an amplitude only system, and also will have an ease of implementation compared to that of a phased array system

Sequential bayesian filtering for spatial arrival time estimation

Locating and tracking a source in an ocean environment as well as estimating environmental parameters of a sound propagation medium is of utmost importance in underwater acoustics. Matched field processing is often the method of choice for the estimation of such parameters. This approach, based on full field calculations, is computationally intensive and sensitive to assumptions on the structure of the environment. As an alternative, methods that use only select features of the acoustic field for source localization and environmental inversion have been proposed. The focus here is on inversion using arrival times of identified paths within recorded time-series. After a short study of a linearization techniques employing such features and numerical issues on their implementation, we turn our attention to the need for accurate extraction of arrival times for accurate estimation. We develop a particle filtering approach that treats arrival times as targets , dynamically modeling their location at arrays of spatially separated receivers. Using Monte Carlo simulations, we perform an evaluation of our method and compare it to conventional Maximum Likelihood (ML) estimation. The comparison demonstrates an advantage in using the proposed approach, which can be employed as a pre-inversion tool for minimization and quantification of uncertainty in arrival time estimation

A study on the error minimization of underwater source localization using sub-array

Passive sonar listens to the sound radiated by any underwater target using a sensor system, and detects its signals against a background noise of the sea and the self noise of the sonar platform. The system can be made directional with time difference of arrival, therefore the horizontal bearing of a signal is known. In addition to measure the bearings with direction of arrival of a signal from sub-array well separated, the direct passive range is known. Underwater source localization based on time difference of arrival measurements has some problems due to the sub-array location uncertainty, partial sensor failures and sound speed mismatch from real underwater environments and system. Therefore the source localization error using TDOA measurements with these problems is investigated. Many algorithms for robust underwater source localization have been developed using TDOA measurements in recent years. One classic algorithm is the linear least squares method. Through pre-processing of TDOA measurements, a set of linear forward closed-form equations can be obtained without considering the relationship between the measurements and references by equations. To incorporate the constraint on the relationship, the localization problem by linear least squares formula can not be convex in accordance with the measurements. In this dissertation, research shows the robust method to minimize the underwater source localization errors with non-linear method, Levenberg-Marquardt. This algorithm is an iterative operation that locates the minimum of a multi-variated function that is expressed as the sum of squares of non-linear real-value. The real critical values for the research of robust underwater source localization are considered the sub-array location uncertainty, partial sensor failures and sound speed mismatch. The proposed algorithm is evaluated as root mean squared errors in terms of the each and mixed value error ranges through the Monte-Carlo simulation. It significantly shows that root mean squared errors of the proposed method based on time difference of arrival are lower than the result of the previous linear least squares method in many cases.|수동 소나는 수중의 소음원이 방사하는 음파를 탐지하여 소음원의 방위, 거리를 추정하는 시스템이다. 음파의 효과적인 탐지를 위하여 음파 탐지 센서를 여러 개의 부배열로 구성하여 각 센서에 입사되는 신호의 도래 시간차를 이용하여 도래각과 거리를 추정한다. 본 연구는 신호원의 도래각 및 도래 시간차 산출에 오차를 유발시키는 변수들을 도출하고 오차를 포함한 변수들로 인해 발생하는 거리 추정 오차를 분석하였다. 오차를 유발하는 변수들은 부배열의 위치 오차, 해양환경의 음파 전달 속도와 시스템에 적용하는 음파전달속도의 부정합, 수신 센서의 작동 유무를 표현하는 센서의 고장 상태를 고려하였다. 이를 기반으로 분산된 부배열로 입사되는 신호원의 도래 시간차를 이용하여 위치 추정 성능을 향상시키기 위한 방안을 연구하였다. 수중 소음원의 위치 추정 최적화 기법에는 오차를 포함한 측정 데이터를 기반으로 이론적으로 예측한 기대값과의 편차를 줄임으로서 오차를 최소화하는 기법으로 선형 최소자승법(LS)이 있다. 선형 최소자승법은 관측 데이터의 특성에 따라 발산 또는 국소 위치(Local Minimum)를 추정하는 Forward Closed Form으로 알려져 있다. 선형 최소자승법과는 달리 비선형 최소자승법은 Backward Recursive Form 으로 매 시간 수신한 데이터를 기반으로 반복 연산을 통하여 목적 함수 내에 포함된 변수의 오차를 최소화하는 과정이다. 비선형 최소자승법은 오차를 최소화하기 위한 감폭 계수(Damping Coefficient)를 어떻게 정의하느냐에 따라 Gauss Newton, Gradient Descent 방법으로 구분한다. 본 논문에서는 이러한 두 개의 비선형 최적화 기법을 결합한 형태인 LM(Levenberg-Marquardt) 알고리즘을 적용하여 수중 소음원의 위치 추정 오차를 최소화하는 기법을 제안하였다. 제안한 기법은 선형 최소자승법에 비하여 안정적인 해를 가지는 장점이 있다. 수중 소음원의 방위, 거리 추정 오차를 유발하는 3개의 주요 변수(음파전달속도의 부정합, 부배열 간의 위치 오차, 센서의 고장 상태)에 오차를 포함한 모의한 데이터를 비선형 최소자승법인 LM 알고리즘에 적용하여 모의 시뮬레이션을 수행하였다. 통계적인 특성을 도출하기 위하여 시뮬레이션 입력 조건에 따라 500회의 몬테카를로 시뮬레이션을 수행하여 통상적인 오차 분석 기법 가운데 하나인 평균제곱근오차(RMSE, Root Mean Squared Errors) 값을 구하여 분석하였다. 시뮬레이션 결과로부터 비선형 최소자승 알고리즘 기반의 제안 기법이 선형 최소자승법에 비해 대부분의 조건에서 5~50% 범위로 성능이 향상되는 것을 확인하였으며, 부배열의 위치 오차와 같은 일부 변수의 성능 제안 범위도 확인하였다.표 차례 iii 그림 차례 iv Abbreviations vi 요 약 문 vii Abatract ix 제 1 장 서론 1 1.1 연구 배경 1 1.2 연구 목적 3 1.3 논문 구성 13 제 2 장 수중 표적의 위치 추정 기법 14 제 3 장 표적 위치 추정 오차 성능 분석 28 3.1 센서 고장에 따른 오차 성능 분석 28 3.2 센서 위치 오차에 따른 오차 성능 분석 36 3.3 음속 오차에 따른 오차 성능 분석 40 3.4 복합 오차에 따른 오차 성능 분석 46 제 4 장 비선형 최소자승법 기반의 거리 추정 오차 최소화 52 4.1 기존의 기법 52 4.2 비선형 최소자승법 기반의 거리 추정 방법 59 제 5 장 시뮬레이션 결과 및 고찰 63 5.1 모의실험 환경 65 5.2 개별 오차에 따른 TDOA 추정 성능 분석 67 5.3 복합 오차에 따른 TDOA 추정 성능 분석 73 5.4 시뮬레이션 결과 종합 80 제 6 장 결론 81 참 고 문 헌 83Docto

Iterative maximum likelihood time delay and Doppler estimation using stationary signals

Includes bibliographical references (p. 155-156).Supported by the USA AMCCOM and ARDEC. Supported by the U.S. Army Research Office managed by Battelle. DAAL03-86-D-0001 Supported in part by the Advanced Research Projects Agency monitored by ONR. N00014-85-K-0272Bruce R. Musicus and Ehud Weinstein

Spontaneous and explicit estimation of time delays in the absence/presence of multipath propagation.

by Hing-cheung So.Thesis (Ph.D.)--Chinese University of Hong Kong, 1995.Includes bibliographical references (leaves 133-141).Chapter 1 --- Introduction --- p.1Chapter 1.1 --- Time Delay Estimation (TDE) and its Applications --- p.1Chapter 1.2 --- Goal of the Work --- p.6Chapter 1.3 --- Thesis Outline --- p.9Chapter 2 --- Adaptive Methods for TDE --- p.10Chapter 2.1 --- Problem Description --- p.11Chapter 2.2 --- The Least Mean Square Time Delay Estimator (LMSTDE) --- p.11Chapter 2.2.1 --- Bias and Variance --- p.14Chapter 2.2.2 --- Probability of Occurrence of False Peak Weight --- p.16Chapter 2.2.3 --- Some Modifications of the LMSTDE --- p.17Chapter 2.3 --- The Adaptive Digital Delay-Lock Discriminator (ADDLD) --- p.18Chapter 2.4 --- Summary --- p.20Chapter 3 --- The Explicit Time Delay Estimator (ETDE) --- p.22Chapter 3.1 --- Derivation and Analysis of the ETDE --- p.23Chapter 3.1.1 --- The ETDE system --- p.23Chapter 3.1.2 --- Performance Surface --- p.26Chapter 3.1.3 --- Static Behaviour --- p.28Chapter 3.1.4 --- Dynamic Behaviour --- p.30Chapter 3.2 --- Performance Comparisons --- p.32Chapter 3.2.1 --- With the LMSTDE --- p.32Chapter 3.2.2 --- With the CATDE --- p.34Chapter 3.2.3 --- With the CRLB --- p.35Chapter 3.3 --- Simulation Results --- p.38Chapter 3.3.1 --- Corroboration of the ETDE Performance --- p.38Chapter 3.3.2 --- Comparative Studies --- p.44Chapter 3.4 --- Summary --- p.48Chapter 4 --- An Improvement to the ETDE --- p.49Chapter 4.1 --- Delay Modeling Error of the ETDE --- p.49Chapter 4.2 --- The Explicit Time Delay and Gain Estimator (ETDGE) --- p.52Chapter 4.3 --- Performance Analysis --- p.55Chapter 4.4 --- Simulation Results --- p.57Chapter 4.5 --- Summary --- p.61Chapter 5 --- TDE in the Presence of Multipath Propagation --- p.62Chapter 5.1 --- The Multipath TDE problem --- p.63Chapter 5.2 --- TDE with Multipath Cancellation (MCTDE) --- p.64Chapter 5.2.1 --- Structure and Algorithm --- p.64Chapter 5.2.2 --- Convergence Dynamics --- p.67Chapter 5.2.3 --- The Generalized Multipath Cancellator --- p.70Chapter 5.2.4 --- Effects of Additive Noises --- p.73Chapter 5.2.5 --- Simulation Results --- p.74Chapter 5.3 --- TDE with Multipath Equalization (METDE) --- p.86Chapter 5.3.1 --- The Two-Step Algorithm --- p.86Chapter 5.3.2 --- Performance of the METDE --- p.89Chapter 5.3.3 --- Simulation Results --- p.93Chapter 5.4 --- Summary --- p.101Chapter 6 --- Conclusions and Suggestions for Future Research --- p.102Chapter 6.1 --- Conclusions --- p.102Chapter 6.2 --- Suggestions for Future Research --- p.104Appendices --- p.106Chapter A --- Derivation of (3.20) --- p.106Chapter B --- Derivation of (3.29) --- p.110Chapter C --- Derivation of (4.14) --- p.111Chapter D --- Derivation of (4.15) --- p.113Chapter E --- Derivation of (5.21) --- p.115Chapter F --- Proof of unstablity of A°(z) --- p.116Chapter G --- Derivation of (5.34)-(5.35) --- p.118Chapter H --- Derivation of variance of αs11(k) and Δs11(k) --- p.120Chapter I --- Derivation of (5.40) --- p.123Chapter J --- Derivation of time constant of αΔ11(k) --- p.124Chapter K --- Derivation of (5.63)-(5.66) --- p.125Chapter L --- Derivation of (5.68)-(5.72) --- p.129References --- p.13

Esquema para la cancelación de interferencias mediante un análisis de multiresolución

En general, en el análisis y procesamiento de señales biomédicas es inevitable la presencia de señales de interferencia, que se traslapar temporal y espectralmente con la señal deseada, y los sonidos respiratorios no son la excepción. La auscultación pulmonar surge como una técnica clínica primordial en la evaluación y seguimiento de enfermedades pulmonares. Actualmente, entre los profesionales de la medicina, el inter& en el análisis de los sonidos respiratorios mediante la técnica de auscultación permanece vigente debido a la información que los sonidos contienen acerca de la condición pulmonar y su característica no invasiva. En el análisis de los sonidos respiratorios, los' ruidos cardiacos representan una fuente de ruido ineludible que modifica, en algunas ocasiones severamente, la información referente al estado pulmonar. Estudios relacionados con la cancelación de interferencias, en diversos campos de la ingeniería, indican que el desempeño de los esquemas de cancelación radica fuertemente en la estimación adecuada del retraso temporal entre la señal de referencia y la señal primaria. En consecuencia, el objetivo de la presente investigación es desarrollar un esquema que permita la cancelación de señales de interferencia (ruidos cardiacos) presentes en la adquisición de los sonidos respiratorios. Para minimizar los efectos de las señales de interferencia, el esquema propuesto para la estimación conjunta de la señal de interferencia y su posición temporal, denominado ‘‘joint time delay and signal estimation (JTDSE)”, utiliza un análisis de multiresolución como marco de referencia. En una primera etapa, el esquema estima la ubicación temporal, “time delay estimation (TDE)”, de la señal de interferencia cardíaca y posteriormente, realiza el filtrado de la señal de interferencia mediante técnicas no convencionales. El análisis de multiresolución de las señales de referencia cardíaca y de sonido respiratorio adquirido se efectúa mediante la transformada discreta de ondillas, “discrete wavelet transform (DWT)”, utilizando varios niveles de descomposición.Como consecuencia del análisis de multiresolución, la metodología propuesta posee importantes beneficios tales como la incorporación de información complementaria en múltiples subbandas, robustez en presencia de ruido, y disponibilidad de un procedimiento de validacibn para los retrasos estimados. El esquema en subbandas JTDSE emplea diferentes mecanismos de adaptación para el retraso temporal y para el proceso de filtrado de la señal de interferencia. La adaptación del retraso se lleva a cabo mediante el algoritmo del gradiente descendente (GD) G mediante el algoritmo de Levenberg-Marquardt (LM), mientras que el proceso de filtrado se basa en el filtro transversal rápido a bloques, “block fast transversal filter (BFTF)”. El desempeño del esquema JTDSE, en sd fase de estimación de la ubicación temporal de interferencias cardiacas, se evalúa utilizando señales sintetizadas que simulan la morfología de la señal respiratoria y la presencia de señales de interferencia con múltiples ruidos cardiacos. La robustez del esquema propuesto se evalúa involucrando diferentes condiciones de la relación señal a interferencia. Señales respiratoriz; adquiridas de sujetos sanos y pacientes asmáticos muestran que el esquema JTDSE representa una alternativa en el análisis de sonidos respiratorios. Además, los resultados del esquema JTDSE se comparan con los resultados obtenidos mediante un esquema de cancelación propuesto previamente, esquema basado en el filtro de Kalman de orden reducido “reduced order Kalman filter (ROKF)”. La utilidad del esquema propuesto no se limita al campo biomédico. En la detección submarina de objetos, “underwater targ target detection (UTD)”, con el propósito de analizar la informacibn relevante relacionada con el objeto bajo estudio, es importante ubicar temporalmente y eliminar la presencia de información no deseada en la señal acústica reflejada. En la evaluación del desempeño del esquema JTDSE, en el campo de la detección submarina de objetos, se emplearon señales sintetizadas simulando la presencia de múltiples componentes no deseados y señales adquiridas de objetos bajo el agua. Los resultados incluidos en eí presente documento se obtuvieron utilizando la versión programada del esquema JTDSE, en la plataforma proporcionada por “Matlab”. La aplicación clínica del esquema propuesto posiblemente requiera la versión en circuitería que en su diseño considere las bondades del procesamiento en paralelo de varias subbandas, inherente a la descomposición por multiresolución