Subband adaptive filtering for acoustic echo control using allpass polyphase IIR filterbanks

Published versio

Fast and Robust Real-Time Estimation of Respiratory Rate from Photoplethysmography

Respiratory rate (RR) is a useful vital sign that can not only provide auxiliary information on physiological changes within the human body, but also indicate early symptoms of various diseases. Recently, methods for the estimation of RR from photoplethysmography (PPG) have attracted increased interest, because PPG can be readily recorded using wearable sensors such as smart watches and smart bands. In the present study, we propose a new method for the fast and robust real-time estimation of RR using an adaptive infinite impulse response (IIR) notch filter, which has not yet been applied to the PPG-based estimation of RR. In our offline simulation study, the performance of the proposed method was compared to that of recently developed RR estimation methods called an adaptive lattice-type RR estimator and a Smart Fusion. The results of the simulation study show that the proposed method could not only estimate RR more quickly and more accurately than the conventional methods, but also is most suitable for online RR monitoring systems, as it does not use any overlapping moving windows that require increased computational costs. In order to demonstrate the practical applicability of the proposed method, an online RR estimation system was implemented.This research was supported by the National Research Foundation of Korea (NRF) grants funded by the Ministry of Science, ICT & Future Planning (MSIP) (NRF-2015M3C7A1065052 and 2015R1A2A1A15054662)

Residual echo signal in critically sampled subband acoustic echo cancellers based on IIR and FIR filter banks

Published versio

Digital signal processing algorithms and structures for adaptive line enhancing

Imperial Users onl

Adaptive notch filtering for tracking multiple complex sinusoid signals

This thesis is related to the field of digital signal processing; where the aim of this research is to develop features of an infinite impulse response adaptive notch filter capable of tracking multiple complex sinusoid signals. Adaptive notch filters are commonly used in: Radar, Sonar, and Communication systems, and have the ability to track the frequencies of real or complex sinusoid signals; thus removing noise from an estimate, and enhancing the performance of a system. This research programme began by implementing four currently proposed adaptive notch structures. These structures were simulated and compared: for tracking between two and four signals; however, in their current form they are only capable of tracking real sinusoid signals. Next, one of these structures is developed further, to facilitate the ability to track complex sinusoid signals. This original structure gives superior performance over Regalia's comparable structure under certain conditions, which has been proven by simulations and results. Complex adaptive notch filter structures generally contain two parameters: the first tracks a target frequency, then the second controls the adaptive notch filter's bandwidth. This thesis develops the notch filter, so that the bandwidth parameter can be adapted via a method of steepest ascent; and also investigates tracking complex-valued chirp signals. Lastly, stochastic search methods are considered; and particle swarm optimisation has been applied to reinitialise an adaptive notch filter, when tracking two signals; thus more quickly locating an unknown frequency, after the frequency of the complex sinusoid signal jumps

Adaptive Interference Mitigation in GPS Receivers

Satellite navigation systems (GNSS) are among the most complex radio-navigation systems, providing positioning, navigation, and timing (PNT) information. A growing number of public sector and commercial applications rely on the GNSS PNT service to support business growth, technical development, and the day-to-day operation of technology and socioeconomic systems. As GNSS signals have inherent limitations, they are highly vulnerable to intentional and unintentional interference. GNSS signals have spectral power densities far below ambient thermal noise. Consequently, GNSS receivers must meet high standards of reliability and integrity to be used within a broad spectrum of applications. GNSS receivers must employ effective interference mitigation techniques to ensure robust, accurate, and reliable PNT service. This research aims to evaluate the effectiveness of the Adaptive Notch Filter (ANF), a precorrelation mitigation technique that can be used to excise Continuous Wave Interference (CWI), hop-frequency and chirp-type interferences from GPS L1 signals. To mitigate unwanted interference, state-of-the-art ANFs typically adjust a single parameter, the notch centre frequency, and zeros are constrained extremely close to unity. Because of this, the notch centre frequency converges slowly to the target frequency. During this slow converge period, interference leaks into the acquisition block, thus sabotaging the operation of the acquisition block. Furthermore, if the CWI continuously hops within the GPS L1 in-band region, the subsequent interference frequency is locked onto after a delay, which means constant interference occurs in the receiver throughout the delay period. This research contributes to the field of interference mitigation at GNSS's receiver end using adaptive signal processing, predominately for GPS. This research can be divided into three stages. I first designed, modelled and developed a Simulink-based GPS L1 signal simulator, providing a homogenous test signal for existing and proposed interference mitigation algorithms. Simulink-based GPS L1 signal simulator provided great flexibility to change various parameters to generate GPS L1 signal under different conditions, e.g. Doppler Shift, code phase delay and amount of propagation degradation. Furthermore, I modelled three acquisition schemes for GPS signals and tested GPS L1 signals acquisition via coherent and non-coherent integration methods. As a next step, I modelled different types of interference signals precisely and implemented and evaluated existing adaptive notch filters in MATLAB in terms of Carrier to Noise Density (\u1d436/\u1d4410), Signal to Noise Ratio (SNR), Peak Degradation Metric, and Mean Square Error (MSE) at the output of the acquisition module in order to create benchmarks. Finally, I designed, developed and implemented a novel algorithm that simultaneously adapts both coefficients in lattice-based ANF. Mathematically, I derived the full-gradient term for the notch's bandwidth parameter adaptation and developed a framework for simultaneously adapting both coefficients of a lattice-based adaptive notch filter. I evaluated the performance of existing and proposed interference mitigation techniques under different types of interference signals. Moreover, I critically analysed different internal signals within the ANF structure in order to develop a new threshold parameter that resets the notch bandwidth at the start of each subsequent interference frequency. As a result, I further reduce the complexity of the structural implementation of lattice-based ANF, allowing for efficient hardware realisation and lower computational costs. It is concluded from extensive simulation results that the proposed fully adaptive lattice-based provides better interference mitigation performance and superior convergence properties to target frequency compared to traditional ANF algorithms. It is demonstrated that by employing the proposed algorithm, a receiver is able to operate with a higher dynamic range of JNR than is possible with existing methods. This research also presents the design and MATLAB implementation of a parameterisable Complex Adaptive Notch Filer (CANF). Present analysis on higher order CANF for detecting and mitigating various types of interference for complex baseband GPS L1 signals. In the end, further research was conducted to suppress interference in the GPS L1 signal by exploiting autocorrelation properties and discarding some portion of the main lobe of the GPS L1 signal. It is shown that by removing 30% spectrum of the main lobe, either from left, right, or centre, the GPS L1 signal is still acquirable

Adaptive Notch Filter for Single and Multiple Narrow-Band Interference

In this project, the adaptive notch filter for single and Multiple narrow-band interference is implemented using simplified LMS algorithm. Performances of the LMS adaptive algorithms is evaluated and analysed through simulation on the computer using Matlab. The algorithm are then written in C programme and implemented using Texas Instrument Tool which consist of TMS320C54x EMV board and Code Composer Studio

IIR modeling of interpositional transfer functions with a genetic algorithm aided by an adaptive filter for the purpose of altering free-field sound localization

The psychoacoustic process of sound localization is a system of complex analysis. Scientists have found evidence that both binaural and monaural cues are responsible for determining the angles of elevation and azimuth which represent a sound source. Engineers have successfully used these cues to build mathematical localization systems. Research has indicated that spectral cues play an important role in 3-d localization. Therefore, it seems conceivable to design a filtering system which can alter the localization of a sound source, either for correctional purposes or listener preference. Such filters, known as Interpositional Transfer Functions, can be formed from division in the z-domain of Head-related Transfer Functions. HRTF’s represent the free-field response of the human body to sound processed by the ears. In filtering applications, the use of IIR filters is often favored over that of FIR filters due to their preservation of resolution while minimizing the number of required coefficients. Several methods exist for creating IIR filters from their representative FIR counterparts. For complicated filters, genetic algorithms (GAs) have proven effective. The research summarized in this thesis combines the past efforts of researchers in the fields of sound localization, genetic algorithms, and adaptive filtering. It represents the initial stage in the development of a practical system for future hardware implementation which uses a genetic algorithm as a driving engine. Under ideal conditions, an IIR filter design system has been demonstrated to successfully model several IPTF pairs which alter sound localization when applied to non-minimum phase HRTF’s obtained from free-field measurement

Doctor of Philosophy

dissertationHearing aids suffer from the problem of acoustic feedback that limits the gain provided by hearing aids. Moreover, the output sound quality of hearing aids may be compromised in the presence of background acoustic noise. Digital hearing aids use advanced signal processing to reduce acoustic feedback and background noise to improve the output sound quality. However, it is known that the output sound quality of digital hearing aids deteriorates as the hearing aid gain is increased. Furthermore, popular subband or transform domain digital signal processing in modern hearing aids introduces analysis-synthesis delays in the forward path. Long forward-path delays are not desirable because the processed sound combines with the unprocessed sound that arrives at the cochlea through the vent and changes the sound quality. In this dissertation, we employ a variable, frequency-dependent gain function that is lower at frequencies of the incoming signal where the information is perceptually insignificant. In addition, the method of this dissertation automatically identifies and suppresses residual acoustical feedback components at frequencies that have the potential to drive the system to instability. The suppressed frequency components are monitored and the suppression is removed when such frequencies no longer pose a threat to drive the hearing aid system into instability. Together, the method of this dissertation provides more stable gain over traditional methods by reducing acoustical coupling between the microphone and the loudspeaker of a hearing aid. In addition, the method of this dissertation performs necessary hearing aid signal processing with low-delay characteristics. The central idea for the low-delay hearing aid signal processing is a spectral gain shaping method (SGSM) that employs parallel parametric equalization (EQ) filters. Parameters of the parametric EQ filters and associated gain values are selected using a least-squares approach to obtain the desired spectral response. Finally, the method of this dissertation switches to a least-squares adaptation scheme with linear complexity at the onset of howling. The method adapts to the altered feedback path quickly and allows the patient to not lose perceivable information. The complexity of the least-squares estimate is reduced by reformulating the least-squares estimate into a Toeplitz system and solving it with a direct Toeplitz solver. The increase in stable gain over traditional methods and the output sound quality were evaluated with psychoacoustic experiments on normal-hearing listeners with speech and music signals. The results indicate that the method of this dissertation provides 8 to 12 dB more hearing aid gain than feedback cancelers with traditional fixed gain functions. Furthermore, experimental results obtained with real world hearing aid gain profiles indicate that the method of this dissertation provides less distortion in the output sound quality than classical feedback cancelers, enabling the use of more comfortable style hearing aids for patients with moderate to profound hearing loss. Extensive MATLAB simulations and subjective evaluations of the results indicate that the method of this dissertation exhibits much smaller forward-path delays with superior howling suppression capability