Detecting and Classifying Bio-Inspired Artificial Landmarks Using In-Air 3D Sonar

Various autonomous applications rely on recognizing specific known landmarks in their environment. For example, Simultaneous Localization And Mapping (SLAM) is an important technique that lays the foundation for many common tasks, such as navigation and long-term object tracking. This entails building a map on the go based on sensory inputs which are prone to accumulating errors. Recognizing landmarks in the environment plays a vital role in correcting these errors and further improving the accuracy of SLAM. The most popular choice of sensors for conducting SLAM today is optical sensors such as cameras or LiDAR sensors. These can use landmarks such as QR codes as a prerequisite. However, such sensors become unreliable in certain conditions, e.g., foggy, dusty, reflective, or glass-rich environments. Sonar has proven to be a viable alternative to manage such situations better. However, acoustic sensors also require a different type of landmark. In this paper, we put forward a method to detect the presence of bio-mimetic acoustic landmarks using support vector machines trained on the frequency bands of the reflecting acoustic echoes using an embedded real-time imaging sonar.Comment: Presented at 2023 IEEE Sensors Conference, Vienna, Austri

A pipeline structure for the block QR update in digital signal processing

[EN] There exist problems in the field of digital signal processing, such as filtering of acoustic signals that require processing a large amount of data in real time. The beamforming algorithm, for instance, is a process that can be modeled by a rectangular matrix built on the input signals of an acoustic system and, thus, changes in real time. To obtain the output signals, it is required to compute its QR factorization. In this paper, we propose to organize the concurrent computational resources of a given multicore computer in a pipeline structure to perform this factorization as fast as possible. The pipeline has been implemented using both the application programming interface OpenMP and GrPPI, a library interface to design parallel applications based on parallel patterns. We tackle not only the performance challenge but also the programmability of our idea using parallel programming frameworks.This work was supported by the Spanish Ministry of Economy and Competitiveness under MINECO and FEDER projects TIN2014-53495-R and TEC2015-67387-C4-1-R.Dolz, MF.; Alventosa, FJ.; Alonso-Jordá, P.; Vidal Maciá, AM. (2019). A pipeline structure for the block QR update in digital signal processing. The Journal of Supercomputing. 75(3):1470-1482. https://doi.org/10.1007/s11227-018-2666-1S14701482753Huang Y, Benesty J, Chen J (2006) Acoustic MIMO signal processing (signals and communication technology). Springer, BerlinRamiro C, Vidal AM, González A (2015) MIMOPack: a high performance computing library for MIMO communication systems. J Supercomput 71:751–760Alventosa FJ, Alonso P, Piñero G, Vidal AM (2016) Implementation of the Beamformer algorithm for the NVIDIA Jetson. In: Actas de la Conferencia, Granada, Spain, pp 201–211. ISBN 978-3-319-49955-0Alventosa FJ, Alonso P, Vidal AM, Piñero G, Quintana-Ortí ES (2018) Fast block QR update in digital signal processing. J Supercomput. https://doi.org/10.1007/s11227-018-2298-5del Rio D, Dolz MF, Fernández J, García JD (2017) A generic parallel pattern interface for stream and data processing. Concurr Comput Pract Exp 29(24):e4175Benesty J, Chen J, Huang Y, Dmochowski J (2007) On microphone-array Beamforming from a MIMO acoustic signal processing perspective. IEEE Trans Audio Speech Lang Process 15(3):1053–1065Lorente J, Piñero G, Vidal AM, Belloch JA, González A (2011) Parallel implementations of Beamforming design and filtering for microphone array applications. In: 19th European Signal Processing Conference (EUSIPCO), Barcelona, Spain, pp 501–505Belloch JA, Ferrer M, González A, Martínez-Zaldívar FJ, Vidal AM (2013) Headphone-based virtual spatialization of sound with a GPU accelerator. J Audio Eng Soc 61:546–561Belloch JA, González A, Martínez-Zaldívar FJ, Vidal AM (2011) Real-time massive convolution for audio applications on GPU. J Supercomput 58(3):449–457Golub GH, Van Loan CF (2013) Matrix computations. Johns Hopkins studies in the mathematical sciences. Johns Hopkins University Press, BaltimoreGunter BC, van de Geijn RA (2005) Parallel out-of-core computation and updating the QR factorization. ACM Trans Math Softw 31(1):60–78Buttari A, Langou J, Kurzak J, Dongarra J (2009) A class of parallel tiled linear algebra algorithms for multicore architectures. Parallel Comput 35(1):38–53Dolz MF, Alventosa FJ, Alonso-Jordá P, Vidal AM (2018) A pipeline for the QR update in digital signal processing. In: Proceedings of the 18th International Conference on Computational and Mathematical Methods in Science and Engineering (CMMSE 2018), Rota, Cádiz, Spain, pp 1–5Quintana-Ortí G, Quintana-Ortí ES, Van De Geijn RA, Van Zee FG, Chan E (2009) Programming matrix algorithms-by-blocks for thread-level parallelism. ACM Trans Math Softw 36(3):14:1–14:2

Raking echoes in the time domain

The geometry of room acoustics is such that the reverberant signal can be seen as the same waveform emitted from multiple locations. In analogy with the rake receiver from wireless communications, we propose several beamforming strategies that exploit, rather than suppress, this additional spatio-temporal diversity. Unlike earlier work in the frequency domain, time domain designs allow to shape the impulse response of the beamformer. In particular, we can control perceptually relevant parameters, such as the amount of early echoes or the length of the beamformer response. Relying on the knowledge of the image sources positions, we derive different optimal beamformers. Leveraging perceptual cues, we show how to improve interference and noise reduction without degrading the perceptual quality. The designs are validated through simulation. Using early echoes is shown to strictly improve the signal to interference and noise ratio. Code and speech samples are available online at http://lcav.epfl.ch/Robin_Scheibler

Optimización en procesadores ARM de la descomposición matricial QR para Beamforming

[ES] Los procesadores de propósito general y bajo consumo ARM que se montan en una amplía gama de dispositivos móviles y sistemas embebidos están revolucionando el mundo de la tecnología, que hoy en día implica casi cualquier sector imaginable. Las series ARMv7 y posteriores, tienen en su diseño la inclusión de unidades de cómputo avanzadas SIMD (Simple Instruction Multiple Data), proporcionando un recurso brillante para el procesamiento paralelo de datos. El campo del procesamiento digital de audio es el contexto de este trabajo y es donde aprovechamos las citadas capacidades en un proceso inherentemente de tiempo real. Dicho proceso consiste en la adecuada selección y descarte de señales acústicas en base a un cómputo iterativo en la actualización de las mismas. El modelo se simula y está implementado de manera eficiente mediante el uso del lenguaje de programación C, el uso de librerías de altas prestaciones como BLAS/LAPACK optimizado (ATLAS), y a la herramienta de computación paralela OpenMP. Todo ello bajo un entorno de aprovechamiento máximo del rendimiento respecto del consumo (Flop/Watt), que haga factible su uso en plataformas portátiles.[EN] ARM's general purpose and low-power consumption processors, which are assembled in a wide range of mobile devices and embedded systems are revolutionizing the world of technology, which nowadays involves almost any sector imaginable. The ARMv7 and later series, have in their design the inclusion of advanced SIMD (Simple Instruction Multiple Data) units, providing a brilliant feature for parallel data processing. The field of digital audio processing is the context of this work and it is where we take advantage of the aforementioned capabilities in an inherently real-time process. This process consists in the proper acoustic signals selection and discard, based on an iterative compute in this updating signals. The model is simulated and it is implemented by using the C programming language, the optimized BLAS/LAPACK (ATLAS) high performance library and the OpenMP framework. All this under an environment of maximum profit of the performance against the consumption (Flop/Watt), doing feasible its use in mobile platforms.Ruiz Andrés, E. (2017). Optimización en procesadores ARM de la descomposición matricial QR para Beamforming. http://hdl.handle.net/10251/88852.TFG

Novel Complex Adaptive Signal Processing Techniques Employing Optimally Derived Time-varying Convergence Factors With Applicatio

In digital signal processing in general, and wireless communications in particular, the increased usage of complex signal representations, and spectrally efficient complex modulation schemes such as QPSK and QAM has necessitated the need for efficient and fast-converging complex digital signal processing techniques. In this research, novel complex adaptive digital signal processing techniques are presented, which derive optimal convergence factors or step sizes for adjusting the adaptive system coefficients at each iteration. In addition, the real and imaginary components of the complex signal and complex adaptive filter coefficients are treated as separate entities, and are independently updated. As a result, the developed methods efficiently utilize the degrees of freedom of the adaptive system, thereby exhibiting improved convergence characteristics, even in dynamic environments. In wireless communications, acceptable co-channel, adjacent channel, and image interference rejection is often one of the most critical requirements for a receiver. In this regard, the fixed-point complex Independent Component Analysis (ICA) algorithm, called Complex FastICA, has been previously applied to realize digital blind interference suppression in stationary or slow fading environments. However, under dynamic flat fading channel conditions frequently encountered in practice, the performance of the Complex FastICA is significantly degraded. In this dissertation, novel complex block adaptive ICA algorithms employing optimal convergence factors are presented, which exhibit superior convergence speed and accuracy in time-varying flat fading channels, as compared to the Complex FastICA algorithm. The proposed algorithms are called Complex IA-ICA, Complex OBA-ICA, and Complex CBC-ICA. For adaptive filtering applications, the Complex Least Mean Square algorithm (Complex LMS) has been widely used in both block and sequential form, due to its computational simplicity. However, the main drawback of the Complex LMS algorithm is its slow convergence and dependence on the choice of the convergence factor. In this research, novel block and sequential based algorithms for complex adaptive digital filtering are presented, which overcome the inherent limitations of the existing Complex LMS. The block adaptive algorithms are called Complex OBA-LMS and Complex OBAI-LMS, and their sequential versions are named Complex HA-LMS and Complex IA-LMS, respectively. The performance of the developed techniques is tested in various adaptive filtering applications, such as channel estimation, and adaptive beamforming. The combination of Orthogonal Frequency Division Multiplexing (OFDM) and the Multiple-Input-Multiple-Output (MIMO) technique is being increasingly employed for broadband wireless systems operating in frequency selective channels. However, MIMO-OFDM systems are extremely sensitive to Intercarrier Interference (ICI), caused by Carrier Frequency Offset (CFO) between local oscillators in the transmitter and the receiver. This results in crosstalk between the various OFDM subcarriers resulting in severe deterioration in performance. In order to mitigate this problem, the previously proposed Complex OBA-ICA algorithm is employed to recover user signals in the presence of ICI and channel induced mixing. The effectiveness of the Complex OBA-ICA method in performing ICI mitigation and signal separation is tested for various values of CFO, rate of channel variation, and Signal to Noise Ratio (SNR)

A binaural sound sources localisation application for smart phones

The ability to estimate positions of sound sources is one that gives animals a 360° awareness of their acoustic environment. This helps compliment the visual scene which is restricted to 180° in humans. Unfortunately, deaf people are left out on this ability. Smart phones are rapidly becoming a common tool amongst mobile users in developed and emerging markets. Their processing ability has more than doubled since their introduction to mass consumer markets by Apple in 2007. Top-end smart phones such as the Samsung Galaxy Series; 3, 4, and 5 models, have two microphones with which one can acquire stereo recordings. The purpose of this research project was to establish a feasible Sound source localization algorithm for current top-end smart phones, and to recommend hardware improvements for future smart phones, to pave way for the use of smart phones as advanced auditory sensory devices capable of acting as avatars for intelligent remote systems to learn about different acoustic scenes with help of human users. The GCC-PHAT algorithm was chosen as the underlying core DOA algorithm due to its suitability for pair-wise localization as highlighted in literature. A stochastic power accumulation algorithm was designed and implemented to improve estimation outcomes by GCC-PHAT. This algorithm was based on inspiration from W-disjoint orthogonality assumption in literature and was extended to perform sound source counting and time domain source separation. The system yielded satisfactory azimuth estimates of sound source directions in real time with pin-point DOA estimation accuracy rates of 64%, and 90.67% accuracy rate when a tolerance of ± 1 correlation sample is considered. An effort to resolve front back ambiguity using phone orientation data from the MEMs sensors yielded un-satisfactory results prompting a recommendation that an extra microphone would be needed to achieve 360° localization in a more user friendly way. The dissertation concludes with plans for further work on the topic and provision of a further refined API and optimised libraries to facilitate development of customised solutions using this system

Desarrollo de una aplicación de audio multicanal utilizando el paralelismo de las GPU

En este trabajo se han analizado las prestaciones que ofrece una GPU ante una aplicación de audio multicanal, aplicando dicho análisis a la implementación un Cancelador Crosstalk que funciona en tiempo real y cuyo código es ejecutado sobre una GPU de un computador personal portatil.Belloch Rodríguez, JA. (2010). Desarrollo de una aplicación de audio multicanal utilizando el paralelismo de las GPU. http://hdl.handle.net/10251/13644Archivo delegad