Keonwook Kim

PARALLEL ALGORITHMS FOR ROBUST BROADBAND MVDR BEAMFORMING

Rapid advancements in adaptive sonar beamforming algorithms have greatly increased the computation and communication demands on beamforming arrays, particularly for applications that require in-array autonomous operation. By coupling each transducer node in a distributed array with a microprocessor, and networking them together, embedded parallel processing for adaptive beamformers can significantly reduce execution time, power consumption and cost, and increase scalability and dependability. In this paper, the basic narrowband Minimum Variance Distortionless Response (MVDR) beamformer is enhanced by incorporating broadband processing, a technique to enhance the robustness of the algorithm, and speedup of the matrix inversion task using sequential regression. Using this Robust Broadband MVDR (RB-MVDR) algorithm as a sequential baseline, two novel parallel algorithms are developed and analyzed. Performance results are included, among them execution time, scaled speedup, parallel efficiency, result latency and memory utilization. The testbed used is a distributed system comprised of a cluster of personal computers connected by a conventional network.

DISTRIBUTED PARALLEL PROCESSING TECHNIQUES FOR ADAPTIVE SONAR BEAMFORMING

Quiet submarine threats and high clutter in the littoral environment increase computation and communication demands on beamforming arrays, particularly for applications that require in-array autonomous operation. By coupling each transducer node in a distributed array with a microprocessor, and networking them together, embedded parallel processing for adaptive beamformers can glean advantages in execution speed, fault tolerance, scalability, power, and cost. In this paper, a novel set of techniques for the parallelization of adaptive beamforming algorithms is introduced for in-array sonar signal processing. A narrowband, unconstrained, Minimum Variance Distortionless Response (MVDR) beamformer is used as a baseline to investigate the efficiency and effectiveness of this method in an experimental fashion. Performance results are also included, among them execution times, parallel efficiencies, and memory requirements, using a distributed system testbed comprised of a cluster of workstations connected by a conventional network.

PARALLEL ALGORITHMS FOR SPLIT-APERTURE CONVENTIONAL BEAMFORMING

Quiet submarine threats and high clutter in the littoral undersea environment increase the processing demands on beamforming arrays, particularly for applications which require in-array autonomous operation. Whereas traditional single-aperture beamforming approaches may falter, the Split-Aperture Conventional Beamforming (SA-CBF) algorithm can be used to meet stringent requirements for more precise bearing estimation. Moreover, by coupling each transducer node with a microprocessor, parallel processing of the split-aperture beamformer on a distributed system can glean advantages in execution speed, fault tolerance, scalability, and cost. In this paper, parallel algorithms for SA-CBF are introduced using coarse-grained and medium-grained forms of decomposition. Performance results from parallel and sequential algorithms are presented using a distributed system testbed comprised of a cluster of workstations connected by a high-speed network. The execution times, parallel efficiencies, and memory requirements of each parallel algorithm are presented and analyzed. The results of these analyses demonstrate that parallel in-array processing holds the potential to meet the needs of future advanced sonar beamforming algorithms in a scalable fashion.

Design and Analysis of Experimental Anechoic Chamber for Localization

The anechoic chamber is essential tool to measure the various acoustic parameters with high precision. The chamber provides the climate controlled indoor environments but requires the dedicated room at a great cost in order to isolate and absorb sound field. Provided the purpose of the chamber is specific to the experiments of sound localization, the performance requirements excluding free field can be alleviated for cost effective solution. This paper designs low cost and profile anechoic chamber based on acoustic pyramids and evaluates the performance specified by the Annex of ISO 3745. Data analysis is employed to measure the free and hemi-free field performance over five straight paths for working areas and four paths for non-working areas. The identical two measurement campaigns were conducted for free and hemi-free field chamber which is easily interchangeable by simple labor in this chamber design. In the working area with conventional speaker, the results of these analyses demonstrate that lab-designed anechoic chamber is in conformance with ISO 3745 for 250 Hz - 16 kHz one-third octave band at free field chamber and for 1 kHz - 16 kHz one-third octave band at hemi-free field chamber.

Monaural Sound Localization Based on Structure-Induced Acoustic Resonance

A physical structure such as a cylindrical pipe controls the propagated sound spectrum in a predictable way that can be used to localize the sound source. This paper designs a monaural sound localization system based on multiple pyramidal horns around a single microphone. The acoustic resonance within the horn provides a periodicity in the spectral domain known as the fundamental frequency which is inversely proportional to the radial horn length. Once the system accurately estimates the fundamental frequency, the horn length and corresponding angle can be derived by the relationship. The modified Cepstrum algorithm is employed to evaluate the fundamental frequency. In an anechoic chamber, localization experiments over azimuthal configuration show that up to 61% of the proper signal is recognized correctly with 30% misfire. With a speculated detection threshold, the system estimates direction 52% in positive-to-positive and 34% in negative-to-positive decision rate, on average.

Binaural Sound Localizer for Azimuthal Movement Detection Based on Diffraction

Sound localization can be realized by utilizing the physics of acoustics in various methods. This paper investigates a novel detection architecture for the azimuthal movement of sound source based on the interaural level difference (ILD) between two receivers. One of the microphones in the system is surrounded by barriers of various heights in order to cast the direction dependent diffraction of the incoming signal. The gradient analysis of the ILD between the structured and unstructured microphone demonstrates the rotation directions as clockwise, counter clockwise, and no rotation of the sound source. Acoustic experiments with different types of sound source over a wide range of target movements show that the average true positive and false positive rates are 67% and 16%, respectively. Spectral analysis demonstrates that the low frequency delivers decreased true and false positive rates and the high frequency presents increases of both rates, overall.

PARALLEL ALGORITHMS FOR ADAPTIVE MATCHED-FIELD PROCESSING ON DISTRIBUTED ARRAY SYSTEMS

Matched-field processing (MFP) localizes sources more accurately than plane-wave beamforming by employing full-wave acoustic propagation models for the cluttered ocean environment. The minimum variance distortionless response MFP (MVDR-MFP) algorithm incorporates the MVDR technique into the MFP algorithm to enhance beamforming performance. Such an adaptive MFP algorithm involves intensive computational and memory requirements due to its complex acoustic model and environmental adaptation. The real-time implementation of adaptive MFP algorithms for large surveillance areas presents a serious computational challenge where high-performance embedded computing and parallel processing may be required to meet real-time constraints. In this paper, three parallel algorithms based on domain decomposition techniques are presented for the MVDR-MFP algorithm on distributed array systems. The parallel performance factors in terms of execution times, communication times, parallel efficiencies, and memory capacities are examined on three potential distributed systems including two types of digital signal processor arrays and a cluster of personal computers. The performance results demonstrate that these parallel algorithms provide a feasible solution for real-time, scalable, and cost-effective adaptive beamforming on embedded, distributed array systems.

Near-Field Sound Localization Based on the Small Profile Monaural Structure

The acoustic wave around a sound source in the near-field area presents unconventional properties in the temporal, spectral, and spatial domains due to the propagation mechanism. This paper investigates a near-field sound localizer in a small profile structure with a single microphone. The asymmetric structure around the microphone provides a distinctive spectral variation that can be recognized by the dedicated algorithm for directional localization. The physical structure consists of ten pipes of different lengths in a vertical fashion and rectangular wings positioned between the pipes in radial directions. The sound from an individual direction travels through the nearest open pipe, which generates the particular fundamental frequency according to the acoustic resonance. The Cepstral parameter is modified to evaluate the fundamental frequency. Once the system estimates the fundamental frequency of the received signal, the length of arrival and angle of arrival (AoA) are derived by the designed model. From an azimuthal distance of 3–15 cm from the outer body of the pipes, the extensive acoustic experiments with a 3D-printed structure show that the direct and side directions deliver average hit rates of 89% and 73%, respectively. The closer positions to the system demonstrate higher accuracy, and the overall hit rate performance is 78% up to 15 cm away from the structure body.

Lightweight Filter Architecture for Energy Efficient Mobile Vehicle Localization Based on a Distributed Acoustic Sensor Network

The generic properties of an acoustic signal provide numerous benefits for localization by applying energy-based methods over a deployed wireless sensor network (WSN). However, the signal generated by a stationary target utilizes a significant amount of bandwidth and power in the system without providing further position information. For vehicle localization, this paper proposes a novel proximity velocity vector estimator (PVVE) node architecture in order to capture the energy from a moving vehicle and reject the signal from motionless automobiles around the WSN node. A cascade structure between analog envelope detector and digital exponential smoothing filter presents the velocity vector-sensitive output with low analog circuit and digital computation complexity. The optimal parameters in the exponential smoothing filter are obtained by analytical and mathematical methods for maximum variation over the vehicle speed. For stationary targets, the derived simulation based on the acoustic field parameters demonstrates that the system significantly reduces the communication requirements with low complexity and can be expected to extend the operation time considerably.

Monaural Sound Localization Based on Reflective Structure and Homomorphic Deconvolution

The asymmetric structure around the receiver provides a particular time delay for the specific incoming propagation. This paper designs a monaural sound localization system based on the reflective structure around the microphone. The reflective plates are placed to present the direction-wise time delay, which is naturally processed by convolutional operation with a sound source. The received signal is separated for estimating the dominant time delay by using homomorphic deconvolution, which utilizes the real cepstrum and inverse cepstrum sequentially to derive the propagation response’s autocorrelation. Once the localization system accurately estimates the information, the time delay model computes the corresponding reflection for localization. Because of the structure limitation, two stages of the localization process perform the estimation procedure as range and angle. The software toolchain from propagation physics and algorithm simulation realizes the optimal 3D-printed structure. The acoustic experiments in the anechoic chamber denote that 79.0% of the study range data from the isotropic signal is properly detected by the response value, and 87.5% of the specific direction data from the study range signal is properly estimated by the response time. The product of both rates shows the overall hit rate to be 69.1%.