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

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

Modified Direct Adaptive Regulation Scheme Applied to a Benchmark Problem

International audienceA direct adaptive regulation scheme using a FIR Youla-Kučera Filter has been proposed for solving the EJC Benchmark [4] for rejection of multiple unknown and time-varying narrow-band disturbances. Despite the excellent results this approach requires a careful design of the central controller in terms of selection of some of the assigned closed-loop poles. A modified scheme is proposed in this paper which will incorporate a particular adaptive IIR Youla-Kučera Filter. Called ρ-notch structure (the denominator is a projection inside the unit circle) of the model of the disturbance which has roots on the unit circle. The adaptive scheme estimates separately the numerator and denominator parameters of the IIR Youla-Kučera Filter. Stability and convergence proofs are given along with simulation and real-time results. Comparison with results already obtained for the EJC Benchmark are provided. The use of this approach drastically simplify the design of the central controller and provide even better results than [4] with the advantage to use a single central controller independently of the number of narrow band disturbances

Advanced Electromyogram Signal Processing with an Emphasis on Simplified, Near-Optimal Whitening

Estimates of the time-varying standard deviation of the surface EMG signal (EMGσ) are extensively used in the field of EMG-torque estimation. The use of a whitening filter can substantially improve the accuracy of EMGσ estimation by removing the signal correlation and increasing the statistical bandwidth. However, a subject-specific whitening filter which is calibrated to each subject, is quite complex and inconvenient. To solve this problem, we first calibrated a 60th-order “Universal” FIR whitening filter by using the ensemble mean of the inverse of the square root of the power spectral density (PSD) of the noise-free EMG signal. Pre-existing data from elbow contraction of 64 subjects, providing 512 recording trials were used. The test error on an EMG-torque task based on the “Universal” FIR whitening filter had a mean error of 4.80% maximum voluntary contraction (MVC) with a standard deviation of 2.03% MVC. Meanwhile the subject-specific whitening filter had performance of 4.84±1.98% MVC (both have a whitening band limit at 600 Hz). These two methods had no statistical difference. Furthermore, a 2nd-order IIR whitening filter was designed based on the magnitude response of the “Universal” FIR whitening filter, via the differential evolution algorithm. The performance of this IIR whitening filter was very similar to the FIR filter, with a performance of 4.81±2.12% MVC. A statistical test showed that these two methods had no significant difference either. Additionally, a complete theory of EMG in additive measured noise contraction modeling is described. Results show that subtracting the variance of whitened noise by computing the root difference of the square (RDS) is the correct way to remove noise from the EMG signal

Optimal design of magnitude responses of rational infinite impulse response filters

This correspondence considers a design of magnitude responses of optimal rational infinite impulse response (IIR) filters. The design problem is formulated as an optimization problem in which a total weighted absolute error in the passband and stopband of the filters (the error function reflects a ripple square magnitude) is minimized subject to the specification on this weighted absolute error function defined in the corresponding passband and stopband, as well as the stability condition. Since the cost function is nonsmooth and nonconvex, while the constraints are continuous, this kind of optimization problem is a nonsmooth nonconvex continuous functional constrained problem. To address this issue, our previous proposed constraint transcription method is applied to transform the continuous functional constraints to equality constraints. Then the nonsmooth problem is approximated by a sequence of smooth problems and solved via a hybrid global optimization method. The solutions obtained from these smooth problems converge to the global optimal solution of the original optimization problem. Hence, small transition bandwidth filters can be obtained

Efficient Algorithms for Immersive Audio Rendering Enhancement

Il rendering audio immersivo è il processo di creazione di un’esperienza sonora coinvolgente e realistica nello spazio 3D. Nei sistemi audio immersivi, le funzioni di trasferimento relative alla testa (head-related transfer functions, HRTFs) vengono utilizzate per la sintesi binaurale in cuffia poiché esprimono il modo in cui gli esseri umani localizzano una sorgente sonora. Possono essere introdotti algoritmi di interpolazione delle HRTF per ridurre il numero di punti di misura e per creare un movimento del suono affidabile. La riproduzione binaurale può essere eseguita anche dagli altoparlanti. Tuttavia, il coinvolgimento di due o più gli altoparlanti causa il problema del crosstalk. In questo caso, algoritmi di cancellazione del crosstalk (CTC) sono necessari per eliminare i segnali di interferenza indesiderati. In questa tesi, partendo da un'analisi comparativa di metodi di misura delle HRTF, viene proposto un sistema di rendering binaurale basato sull'interpolazione delle HRTF per applicazioni in tempo reale. Il metodo proposto mostra buone prestazioni rispetto a una tecnica di riferimento. L'algoritmo di interpolazione è anche applicato al rendering audio immersivo tramite altoparlanti, aggiungendo un algoritmo di cancellazione del crosstalk fisso, che considera l'ascoltatore in una posizione fissa. Inoltre, un sistema di cancellazione crosstalk adattivo, che include il tracciamento della testa dell'ascoltatore, è analizzato e implementato in tempo reale. Il CTC adattivo implementa una struttura in sottobande e risultati sperimentali dimostrano che un maggiore numero di bande migliora le prestazioni in termini di errore totale e tasso di convergenza. Il sistema di riproduzione e le caratteristiche dell'ambiente di ascolto possono influenzare le prestazioni a causa della loro risposta in frequenza non ideale. L'equalizzazione viene utilizzata per livellare le varie parti dello spettro di frequenze che compongono un segnale audio al fine di ottenere le caratteristiche sonore desiderate. L'equalizzazione può essere manuale, come nel caso dell'equalizzazione grafica, dove il guadagno di ogni banda di frequenza può essere modificato dall'utente, o automatica, la curva di equalizzazione è calcolata automaticamente dopo la misurazione della risposta impulsiva della stanza. L'equalizzazione della risposta ambientale può essere applicata anche ai sistemi multicanale, che utilizzano due o più altoparlanti e la zona di equalizzazione può essere ampliata misurando le risposte impulsive in diversi punti della zona di ascolto. In questa tesi, GEQ efficienti e un sistema adattativo di equalizzazione d'ambiente. In particolare, sono proposti e approfonditi tre equalizzatori grafici a basso costo computazionale e a fase lineare e quasi lineare. Gli esperimenti confermano l'efficacia degli equalizzatori proposti in termini di accuratezza, complessità computazionale e latenza. Successivamente, una struttura adattativa in sottobande è introdotta per lo sviluppo di un sistema di equalizzazione d'ambiente multicanale. I risultati sperimentali verificano l'efficienza dell'approccio in sottobande rispetto al caso a banda singola. Infine, viene presentata una rete crossover a fase lineare per sistemi multicanale, mostrando ottimi risultati in termini di risposta in ampiezza, bande di transizione, risposta polare e risposta in fase. I sistemi di controllo attivo del rumore (ANC) possono essere progettati per ridurre gli effetti dell'inquinamento acustico e possono essere utilizzati contemporaneamente a un sistema audio immersivo. L'ANC funziona creando un'onda sonora in opposizione di fase rispetto all'onda sonora in arrivo. Il livello sonoro complessivo viene così ridotto grazie all'interferenza distruttiva. Infine, questa tesi presenta un sistema ANC utilizzato per la riduzione del rumore. L’approccio proposto implementa una stima online del percorso secondario e si basa su filtri adattativi in sottobande applicati alla stima del percorso primario che mirano a migliorare le prestazioni dell’intero sistema. La struttura proposta garantisce un tasso di convergenza migliore rispetto all'algoritmo di riferimento.Immersive audio rendering is the process of creating an engaging and realistic sound experience in 3D space. In immersive audio systems, the head-related transfer functions (HRTFs) are used for binaural synthesis over headphones since they express how humans localize a sound source. HRTF interpolation algorithms can be introduced for reducing the number of measurement points and creating a reliable sound movement. Binaural reproduction can be also performed by loudspeakers. However, the involvement of two or more loudspeakers causes the problem of crosstalk. In this case, crosstalk cancellation (CTC) algorithms are needed to delete unwanted interference signals. In this thesis, starting from a comparative analysis of HRTF measurement techniques, a binaural rendering system based on HRTF interpolation is proposed and evaluated for real-time applications. The proposed method shows good performance in comparison with a reference technique. The interpolation algorithm is also applied for immersive audio rendering over loudspeakers, by adding a fixed crosstalk cancellation algorithm, which assumes that the listener is in a fixed position. In addition, an adaptive crosstalk cancellation system, which includes the tracking of the listener's head, is analyzed and a real-time implementation is presented. The adaptive CTC implements a subband structure and experimental results prove that a higher number of bands improves the performance in terms of total error and convergence rate. The reproduction system and the characteristics of the listening room may affect the performance due to their non-ideal frequency response. Audio equalization is used to adjust the balance of different audio frequencies in order to achieve desired sound characteristics. The equalization can be manual, such as in the case of graphic equalization, where the gain of each frequency band can be modified by the user, or automatic, where the equalization curve is automatically calculated after the room impulse response measurement. The room response equalization can be also applied to multichannel systems, which employ two or more loudspeakers, and the equalization zone can be enlarged by measuring the impulse responses in different points of the listening zone. In this thesis, efficient graphic equalizers (GEQs), and an adaptive room response equalization system are presented. In particular, three low-complexity linear- and quasi-linear-phase graphic equalizers are proposed and deeply examined. Experiments confirm the effectiveness of the proposed GEQs in terms of accuracy, computational complexity, and latency. Successively, a subband adaptive structure is introduced for the development of a multichannel and multiple positions room response equalizer. Experimental results verify the effectiveness of the subband approach in comparison with the single-band case. Finally, a linear-phase crossover network is presented for multichannel systems, showing great results in terms of magnitude flatness, cutoff rates, polar diagram, and phase response. Active noise control (ANC) systems can be designed to reduce the effects of noise pollution and can be used simultaneously with an immersive audio system. The ANC works by creating a sound wave that has an opposite phase with respect to the sound wave of the unwanted noise. The additional sound wave creates destructive interference, which reduces the overall sound level. Finally, this thesis presents an ANC system used for noise reduction. The proposed approach implements an online secondary path estimation and is based on cross-update adaptive filters applied to the primary path estimation that aim at improving the performance of the whole system. The proposed structure allows for a better convergence rate in comparison with a reference algorithm