Compressive sensing based Bayesian sparse channel estimation for OFDM communication systems: high performance and low complexity

In orthogonal frequency division modulation (OFDM) communication systems, channel state information (CSI) is required at receiver due to the fact that frequency-selective fading channel leads to disgusting inter-symbol interference (ISI) over data transmission. Broadband channel model is often described by very few dominant channel taps and they can be probed by compressive sensing based sparse channel estimation (SCE) methods, e.g., orthogonal matching pursuit algorithm, which can take the advantage of sparse structure effectively in the channel as for prior information. However, these developed methods are vulnerable to both noise interference and column coherence of training signal matrix. In other words, the primary objective of these conventional methods is to catch the dominant channel taps without a report of posterior channel uncertainty. To improve the estimation performance, we proposed a compressive sensing based Bayesian sparse channel estimation (BSCE) method which can not only exploit the channel sparsity but also mitigate the unexpected channel uncertainty without scarifying any computational complexity. The propose method can reveal potential ambiguity among multiple channel estimators that are ambiguous due to observation noise or correlation interference among columns in the training matrix. Computer simulations show that propose method can improve the estimation performance when comparing with conventional SCE methods.Comment: 24 pages,16 figures, submitted for a journa

Recent Langley helicopter acoustics contributions

The helicopter acoustics program at NASA Langley has included technology for elements of noise control ranging from sources of noise to receivers of noise. The scope of Langley contributions for about the last decade is discussed. Specifically, the resolution of two certification noise quantification issues by subjective acoustics research, the development status of the helicopter system noise prediction program ROTONET are reviewed and the highlights from research on blade rotational, broadband, and blade vortex interaction noise sources are presented. Finally, research contributions on helicopter cabin (or interior) noise control are presented. A bibliography of publications from the Langley helicopter acoustics program for the past 10 years is included

Acoustical Ranging Techniques in Embedded Wireless Sensor Networked Devices

Location sensing provides endless opportunities for a wide range of applications in GPS-obstructed environments; where, typically, there is a need for higher degree of accuracy. In this article, we focus on robust range estimation, an important prerequisite for fine-grained localization. Motivated by the promise of acoustic in delivering high ranging accuracy, we present the design, implementation and evaluation of acoustic (both ultrasound and audible) ranging systems.We distill the limitations of acoustic ranging; and present efficient signal designs and detection algorithms to overcome the challenges of coverage, range, accuracy/resolution, tolerance to Doppler’s effect, and audible intensity. We evaluate our proposed techniques experimentally on TWEET, a low-power platform purpose-built for acoustic ranging applications. Our experiments demonstrate an operational range of 20 m (outdoor) and an average accuracy 2 cm in the ultrasound domain. Finally, we present the design of an audible-range acoustic tracking service that encompasses the benefits of a near-inaudible acoustic broadband chirp and approximately two times increase in Doppler tolerance to achieve better performance

Sound Source Localization in a Multipath Environment Using Convolutional Neural Networks

The propagation of sound in a shallow water environment is characterized by boundary reflections from the sea surface and sea floor. These reflections result in multiple (indirect) sound propagation paths, which can degrade the performance of passive sound source localization methods. This paper proposes the use of convolutional neural networks (CNNs) for the localization of sources of broadband acoustic radiated noise (such as motor vessels) in shallow water multipath environments. It is shown that CNNs operating on cepstrogram and generalized cross-correlogram inputs are able to more reliably estimate the instantaneous range and bearing of transiting motor vessels when the source localization performance of conventional passive ranging methods is degraded. The ensuing improvement in source localization performance is demonstrated using real data collected during an at-sea experiment.Comment: 5 pages, 5 figures, Final draft of paper submitted to 2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) 15-20 April 2018 in Calgary, Alberta, Canada. arXiv admin note: text overlap with arXiv:1612.0350

The estimation of geoacoustic properties from broadband acoustic data, focusing on instantaneous frequency techniques

The compressional wave velocity and attenuation of marine sediments are fundamental to marine science. In order to obtain reliable estimates of these parameters it is necessary to examine in situ acoustic data, which is generally broadband. A variety of techniques for estimating the compressional wave velocity and attenuation from broadband acoustic data are reviewed. The application of Instantaneous Frequency (IF) techniques to data collected from a normal-incidence chirp profiler is examined. For the datasets examined the best estimates of IF are obtained by dividing the chirp profile into a series of sections, estimating the IF of each trace in the section using the first moments of the Wigner Ville distribution, and stacking the resulting IF to obtain a composite IF for the section. As the datasets examined cover both gassy and saturated sediments, this is likely to be the optimum technique for chirp datasets collected from all sediment environments

Implementing and Characterizing Real-time Broadband RFI Excision for the GMRT Wideband Backend

The Giant Metrewave Radio Telescope (GMRT) is being upgraded to increase the receiver sensitivity. This makes the receiver more susceptible to man-made Radio Frequency Interference (RFI). To improve the receiver performance in presence of RFI, real-time RFI excision (filtering) is incorporated in the GMRT wideband backend (GWB). The RFI filtering system is implemented on FPGA and CPU-GPU platforms to detect and remove broadband and narrowband RFI. The RFI is detected using a threshold-based technique where the threshold is computed using Median Absolute Deviation (MAD) estimator. The filtering is carried out by replacing the RFI samples by either noise samples or constant value or threshold. This paper describes the status of the real-time broadband RFI excision system in the wideband receiver chain of the upgraded GMRT (uGMRT). The test methodology for carrying out various tests to demonstrate the performance of broadband RFI excision at the system level and on radio astronomical imaging experiments are also described.Comment: 7 pages, 7 figure

Bandwidth extension of narrowband speech

Recently, 4G mobile phone systems have been designed to process wideband speech signals whose sampling frequency is 16 kHz. However, most part of mobile and classical phone network, and current 3G mobile phones, still process narrowband speech signals whose sampling frequency is 8 kHz. During next future, all these systems must be living together. Therefore, sometimes a wideband speech signal (with a bandwidth up to 7,2 kHz) should be estimated from an available narrowband one (whose frequency band is 300-3400 Hz). In this work, different techniques of audio bandwidth extension have been implemented and evaluated. First, a simple non-model-based algorithm (interpolation algorithm) has been implemented. Second, a model-based algorithm (linear mapping) have been designed and evaluated in comparison to previous one. Several CMOS (Comparison Mean Opinion Score) [6] listening tests show that performance of Linear Mapping algorithm clearly overcomes the other one. Results of these tests are very close to those corresponding to original wideband speech signal.Postprint (published version

Experimental and Numerical Investigation of Near-field Rotor Aeroacoustics

This work presents comparisons between experimental and numerical estimates of near-field rotor aeroacoustics in hover. The experiments took place at the Kazan National Research Technical University named after A. N. Tupolev (Kazan Aviation Institute). A set of rotor blades with NACA-0012 aerofoil sections was used to obtain the sound pressure distribution using a linear array of microphones. It is shown that CFD and experimental results are in good agreement suggesting that the obtained test data can be useful as a validation case for development of CFD tools