arXiv subjects

Andrew C. Singer

Publications and source records attributed to Andrew C. Singer.

At least 37 records · Page 2Linked to original sources

arXiv2023

Online Segmented Recursive Least-Squares for Multipath Doppler Tracking

Underwater communication signals typically suffer from distortion due to motion-induced Doppler. Especially in shallow water environments, recovering the signal is challenging due to the time-varying Doppler effects distorting each path differently. However, conventional Doppler estimation algorithms typically model uniform Doppler across all paths and often fail to provide robust Doppler tracking in multipath environments. In this paper, we propose a dynamic programming-inspired method, called online segmented recursive least-squares (OSRLS) to sequentially estimate the time-varying non-uniform Doppler across different multipath arrivals. By approximating the non-linear time distortion as a piece-wise-linear Markov model, we formulate the problem in a dynamic programming framework known as segmented least-squares (SLS). In order to circumvent an ill-conditioned formulation, perturbations are added to the Doppler model during the linearization process. The successful operation of the algorithm is demonstrated in a simulation on a synthetic channel with time-varying non-uniform Doppler.

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arXiv2023

Towards Robust Data-Driven Underwater Acoustic Localization: A Deep CNN Solution with Performance Guarantees for Model Mismatch

Key challenges in developing underwater acoustic localization methods are related to the combined effects of high reverberation in intricate environments. To address such challenges, recent studies have shown that with a properly designed architecture, neural networks can lead to unprecedented localization capabilities and enhanced accuracy. However, the robustness of such methods to environmental mismatch is typically hard to characterize, and is usually assessed only empirically. In this work, we consider the recently proposed data-driven method [19] based on a deep convolutional neural network, and demonstrate that it can learn to localize in complex and mismatched environments. To explain this robustness, we provide an upper bound on the localization mean squared error (MSE) in the ``true" environment, in terms of the MSE in a ``presumed" environment and an additional penalty term related to the environmental discrepancy. Our theoretical results are corroborated via simulation results in a rich, highly reverberant, and mismatch channel.

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arXiv2023

A Semi-Blind Method for Localization of Underwater Acoustic Sources

Underwater acoustic localization has traditionally been challenging due to the presence of unknown environmental structure and dynamic conditions. The problem is richer still when such structure includes occlusion, which causes the loss of line-of-sight (LOS) between the acoustic source and the receivers, on which many of the existing localization algorithms rely. We develop a semi-blind passive localization method capable of accurately estimating the source's position even in the possible absence of LOS between the source and all receivers. Based on typically-available prior knowledge of the water surface and bottom, we derive a closed-form expression for the optimal estimator under a multi-ray propagation model, which is suitable for shallow-water environments and high-frequency signals. By exploiting a computationally efficient form of this estimator, our methodology makes comparatively high-resolution localization feasible. We also derive the Cramér-Rao bound for this model, which can be used to guide the placement of collections of receivers so as to optimize localization accuracy. The method improves a balance of accuracy and robustness to environmental model mismatch, relative to existing localization methods that are useful in similar settings. The method is validated with simulations and water tank experiments.

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arXiv2022

Through Tissue Ultra-high-definition Video Transmission Using an Ultrasound Communication Channel

Wireless capsule endoscopy (WCE) has been widely adopted as complementary to traditional wired gastroendoscopy, especially for small bowel diseases which are beyond the latter's reach. However, both the video resolution and frame rates are limited in current WCE solutions due to the limited wireless data rate. The reasons behind this are that the electromagnetic (EM), radio frequency (RF) based communication scheme used by WCE has strict limits on useable bandwidth and power, and the high attenuation in the human body compared to air. Ultrasound communication could be a potential alternative solution as it has access to much higher bandwidths and transmitted power with much lower attenuation. In this paper, we propose an ultrasound communication scheme specially designed for high data rate through tissue data transmission and validate this communication scheme by successfully transmitting ultra-high-definition (UHD) video (3840*2160 pixels at 60 FPS) through 5 cm of pork belly. Over 8.3 Mbps error free payload data rate was achieved with the proposed communication scheme and our custom-built field programmable gate array (FPGA) based test platform.

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arXiv2021

Video-Streaming Biomedical Implants using Ultrasonic Waves for Communication

The use of wireless implanted medical devices (IMDs) is growing because they facilitate continuous monitoring of patients during normal activities, simplify medical procedures required for data retrieval and reduce the likelihood of infection associated with trailing wires. However, most of the state-of-the-art IMDs are passive and offline devices. One of the key obstacles to an active and online IMD is the infeasibility of real-time, high-quality video broadcast from the IMD. Such broadcast would help develop innovative devices such as a video-streaming capsule endoscopy (CE) pill with therapeutic intervention capabilities. State-of-the-art IMDs employ radio-frequency electromagnetic waves for information transmission. However, high attenuation of RF-EM waves in tissues and federal restrictions on the transmit power and operable bandwidth lead to fundamental performance constraints for IMDs employing RF links, and prevent achieving high data rates that could accomodate video broadcast. In this work, ultrasonic waves were used for video transmission and broadcast through biological tissues. The proposed proof-of-concept system was tested on a porcine intestine ex vivo and a rabbit in vivo. It was demonstrated that using a millimeter-sized, implanted biocompatible transducer operating at 1.1-1.2 MHz, it was possible to transmit endoscopic video with high resolution (1280 pixels by 720 pixels) through porcine intestine wrapped with bacon, and to broadcast standard definition (640 pixels by 480 pixels) video near real-time through rabbit abdomen in vivo. A media repository that includes experimental demonstrations and media files accompanies this paper. The accompanying media repository can be found at this link: https://bit.ly/3wuc7tk.

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arXiv2021

High Data Rate Near-Ultrasonic Communication with Consumer Devices

Automating device pairing and credential exchange in consumer devices reduce the time users spend with mundane tasks and improve the user experience. Acoustic communication is gaining traction as a practical alternative to Bluetooth or Wi-Fi because it can enable quick and localized information transfer between consumer devices with built-in hardware. However, achieving high data rates (>1 kbps) in such systems has been a challenge because the systems and methods chosen for communication were not tailored to the application. In this work, a high data rate, near-ultrasonic communication (NUSC) system is proposed to transfer personal identification numbers (PINs) to establish a connection between consumer laptops using built-in microphones and speakers. The similarities between indoor near-ultrasonic and underwater acoustic communication (UWAC) channels are identified, and appropriate UWAC techniques are tailored to the NUSC system. The proposed system uses the near-ultrasonic band at 18-20 kHz, and employs coherent modulation and phase-coherent adaptive equalization. The capability of the proposed system is explored in simulated and field experiments that span different device orientations and distances. The experiments demonstrate data rates of 4 kbps over distances of up to 5 meters, which is an order of magnitude higher than the data rates reported with similar systems in the literature.

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arXiv2021

Blind Exploration and Exploitation of Stochastic Experts

We present blind exploration and exploitation (BEE) algorithms for identifying the most reliable stochastic expert based on formulations that employ posterior sampling, upper-confidence bounds, empirical Kullback-Leibler divergence, and minmax methods for the stochastic multi-armed bandit problem. Joint sampling and consultation of experts whose opinions depend on the hidden and random state of the world becomes challenging in the unsupervised, or blind, framework as feedback from the true state is not available. We propose an empirically realizable measure of expert competence that can be inferred instantaneously using only the opinions of other experts. This measure preserves the ordering of true competences and thus enables joint sampling and consultation of stochastic experts based on their opinions on dynamically changing tasks. Statistics derived from the proposed measure is instantaneously available allowing both blind exploration-exploitation and unsupervised opinion aggregation. We discuss how the lack of supervision affects the asymptotic regret of BEE architectures that rely on UCB1, KL-UCB, MOSS, IMED, and Thompson sampling. We demonstrate the performance of different BEE algorithms empirically and compare them to their standard, or supervised, counterparts.

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arXiv2020

Modeling the effects of dynamic range compression on signals in noise

Hearing aids use dynamic range compression (DRC), a form of automatic gain control, to make quiet sounds louder and loud sounds quieter. Compression can improve listening comfort, but it can also cause distortion in noisy environments. It has been widely reported that DRC performs poorly in noise, but there has been little mathematical analysis of these distortion effects. This work introduces a mathematical model to study the behavior of DRC in noise. Using statistical assumptions about the signal envelopes, we define an effective compression function that models the compression applied to one signal in the presence of another. This framework is used to prove results about DRC that have been previously observed experimentally: that when DRC is applied to a mixture of signals, uncorrelated signal envelopes become negatively correlated; that the effective compression applied to each sound in a mixture is weaker than it would have been for the signal alone; and that compression can reduce the long-term signal-to-noise ratio in certain conditions. These theoretical results are supported by software experiments using recorded speech signals.

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arXiv2020

Real-time video streaming in vivo using ultrasound as the communication channel

The emergence of capsule endoscopy has provided a means of capturing video of the small intestines without having to resort to an invasive procedure involving intubation. However, real-time video streaming to a receiver outside the body remains challenging for capsule endoscopy. Traditional electromagnetic-based solutions are limited in their data rates and available power. Recently, ultrasound was investigated as a communication channel for through-tissue data transmission. To achieve real-time video streaming through tissue, data rates of ultrasound need to exceed 1 Mbps. In a previous study, we demonstrated ultrasound communications with data rates greater than 30 Mbps with two focused ultrasound transducers using a large footprint laboratory system through slabs of lossy tissues [1]. While the form factor of the transmitter is also crucial for capsule endoscopy, it is obvious that a large, focused transducer cannot fit within the size of a capsule. Several other challenges for achieving high-speed ultrasonic communication through tissue include strong reflections leading to multipath effects and attenuation. In this work, we demonstrate ultrasonic video communications using a mm-scale microcrystal transmitter with video streaming supplied by a camera connected to a Field Programmable Gate Array (FPGA). The signals were transmitted through a tissue-mimicking phantom and through the abdomen of a rabbit in vivo. The ultrasound signal was recorded by an array probe connected to a Verasonics Vantage system and decoded back to video. To improve the received signal quality, we combined the signal from multiple channels of the array probe. Orthogonal frequency division multiplexing (OFDM) modulation was used to reduce the receiver complexity under a strong multipath environment.

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arXiv2020

Acoustic effects of medical, cloth, and transparent face masks on speech signals

Face masks muffle speech and make communication more difficult, especially for people with hearing loss. This study examines the acoustic attenuation caused by different face masks, including medical, cloth, and transparent masks, using a head-shaped loudspeaker and a live human talker. The results suggest that all masks attenuate frequencies above 1 kHz, that attenuation is greatest in front of the talker, and that there is substantial variation between mask types, especially cloth masks with different materials and weaves. Transparent masks have poor acoustic performance compared to both medical and cloth masks. Most masks have little effect on lapel microphones, suggesting that existing sound reinforcement and assistive listening systems may be effective for verbal communication with masks.

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arXiv2020

Low-Complexity System and Algorithm for an Emergency Ventilator Sensor and Alarm

In response to the shortage of ventilators caused by the COVID-19 pandemic, many organizations have designed low-cost emergency ventilators. Many of these devices are pressure-cycled pneumatic ventilators, which are easy to produce but often do not include the sensing or alarm features found on commercial ventilators. This work reports a low-cost, easy-to-produce electronic sensor and alarm system for pressure-cycled ventilators that estimates clinically useful metrics such as pressure and respiratory rate and sounds an alarm when the ventilator malfunctions. A low-complexity signal processing algorithm uses a pair of nonlinear recursive envelope trackers to monitor the signal from an electronic pressure sensor connected to the patient airway. The algorithm, inspired by those used in hearing aids, requires little memory and performs only a few calculations on each sample so that it can run on nearly any microcontroller.

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arXiv2020

Binaural Audio Source Remixing with Microphone Array Listening Devices

Augmented listening devices, such as hearing aids and augmented reality headsets, enhance human perception by changing the sounds that we hear. Microphone arrays can improve the performance of listening systems in noisy environments, but most array-based listening systems are designed to isolate a single sound source from a mixture. This work considers a source-remixing filter that alters the relative level of each source independently. Remixing rather than separating sounds can help to improve perceptual transparency: it causes less distortion to the signal spectrum and especially to the interaural cues that humans use to localize sounds in space.

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arXiv2019

Cooperative Audio Source Separation and Enhancement Using Distributed Microphone Arrays and Wearable Devices

Augmented listening devices such as hearing aids often perform poorly in noisy and reverberant environments with many competing sound sources. Large distributed microphone arrays can improve performance, but data from remote microphones often cannot be used for delay-constrained real-time processing. We present a cooperative audio source separation and enhancement system that leverages wearable listening devices and other microphone arrays spread around a room. The full distributed array is used to separate sound sources and estimate their statistics. Each listening device uses these statistics to design real-time binaural audio enhancement filters using its own local microphones. The system is demonstrated experimentally using 10 speech sources and 160 microphones in a large, reverberant room.

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arXiv2019

Motion-Tolerant Beamforming with Deformable Microphone Arrays

Microphone arrays are usually assumed to have rigid geometries: the microphones may move with respect to the sound field but remain fixed relative to each other. However, many useful arrays, such as those in wearable devices, have sensors that can move relative to each other. We compare two approaches to beamforming with deformable microphone arrays: first, by explicitly tracking the geometry of the array as it changes over time, and second, by designing a time-invariant beamformer based on the second-order statistics of the moving array. The time-invariant approach is shown to be appropriate when the motion of the array is small relative to the acoustic wavelengths of interest. The performance of the proposed beamforming system is demonstrated using a wearable microphone array on a moving human listener in a cocktail-party scenario.

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arXiv2019

On the Reusability of Post-Experimental Field Data for Underwater Acoustic Communications R&D

Field data is often expensive to collect, time-consuming to prepare to collect, and even more time-consuming to process after the experiment has concluded. However, it is often the practice that such data are used for little after the funded research activity that was concomitant with the experiment is completed. Immutability of the original experimental configuration either results in re-gathering of expensive field-data, or in absence of such data, model-dependent analysis that partially captures the real-world dynamics. For underwater acoustic research and development, the standard communication pipeline might be modified to enable greater re-usability of experimental field data. This paper first characterizes the necessary modifications to the standard communication pipeline to prepare signals for transmission and subsequent recording such that research trades for different modulation and coding schemes may be undertaken post-experiment, without the need for re-transmission of additional waveforms. Then, using the modified mathematical framework, sufficient conditions for reliable post-experimental replay of the environment are recognized. Finally, techniques are discussed to collect sufficient environmental statistics such that subsequent research can be accomplished long after the experiment has been completed, and that results from a given experiment may be reasonably compared with those of another. Examples are provided using both synthetic and experimental data collected from at-sea field tests.

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arXiv2019

Acoustic Impulse Responses for Wearable Audio Devices

We present an open-access dataset of over 8000 acoustic impulse from 160 microphones spread across the body and affixed to wearable accessories. The data can be used to evaluate audio capture and array processing systems using wearable devices such as hearing aids, headphones, eyeglasses, jewelry, and clothing. We analyze the acoustic transfer functions of different parts of the body, measure the effects of clothing worn over microphones, compare measurements from a live human subject to those from a mannequin, and simulate the noise-reduction performance of several beamformers. The results suggest that arrays of microphones spread across the body are more effective than those confined to a single device.

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arXiv2018

Speech Separation Using Partially Asynchronous Microphone Arrays Without Resampling

We consider the problem of separating speech sources captured by multiple spatially separated devices, each of which has multiple microphones and samples its signals at a slightly different rate. Most asynchronous array processing methods rely on sample rate offset estimation and resampling, but these offsets can be difficult to estimate if the sources or microphones are moving. We propose a source separation method that does not require offset estimation or signal resampling. Instead, we divide the distributed array into several synchronous subarrays. All arrays are used jointly to estimate the time-varying signal statistics, and those statistics are used to design separate time-varying spatial filters in each array. We demonstrate the method for speech mixtures recorded on both stationary and moving microphone arrays.

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arXiv2018

Delay-Performance Tradeoffs in Causal Microphone Array Processing

In real-time listening enhancement applications, such as hearing aid signal processing, sounds must be processed with no more than a few milliseconds of delay to sound natural to the listener. Listening devices can achieve better performance with lower delay by using microphone arrays to filter acoustic signals in both space and time. Here, we analyze the tradeoff between delay and squared-error performance of causal multichannel Wiener filters for microphone array noise reduction. We compute exact expressions for the delay-error curves in two special cases and present experimental results from real-world microphone array recordings. We find that delay-performance characteristics are determined by both the spatial and temporal correlation structures of the signals.

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