Paul J. Gendron

An empirical bayes estimator of seismic events using wavelet packet bases

An empirical Bayes (EB) estimator is constructed to denoise a time series containing quarry blasts in New England. This estimator is portable and can be used more generally to denoise seismic events. The EB estimator uses adaptive wavelet packet analysis (WPA) for transformation selection via an EB approximation to the standard entropy functional. We compare this basis selection method to the discrete wavelet transform (DWT) and best basis selection via Stein’s unbiased risk estimator (SURE). The relation of sparsity of representation to quality of estimation over a range of signal-to-noiserations (SNR) for synthetic quarry blast events is demonstrated. For functions with sparse representations, we have found that, at moderate SNR, WPA significantly out performs DWT. The EB best basis performs similarly to SURE best basis, thereby lending credence to the EB method. Finally, we compare DWT and WPA. methods for denoising quarry blast events recorded in New England.

An empirical Bayes estimator for in-scale adaptive filtering

A scale-adaptive filtering scheme is developed for underspread channels based on a model of the linear time-varying channel operator as a process in scale. Recursions serve the purpose of adding detail to the filter estimate until a suitable measure of fidelity and complexity is met. Resolution of the channel impulse response associated with its coherence time is naturally modeled over the observation time via a Gaussian mixture assignment on wavelet coefficients. Maximum likelihood, approximate maximum a posteriori (MAP) and posterior mean estimators, as well as associated variances, are derived. Doppler spread estimation associated with the coherence time of the filter is synonymous with model order selection and a MAP estimate is presented and compared with Laplaces approximation and the popular AIC. The algorithm is implemented with conjugate-gradient iterations at each scale, and as the coherence time is recursively decreased, the lower scale estimate serves as a starting point for successive reduced-coherence time estimates. The algorithm is applied to a set of simulated sparse multipath Doppler spread channels, demonstrating the superior MSE performance of the posterior mean filter estimator and the superiority of the MAP Doppler spread stopping rule.

Modeling heavy-tailed correlated noise with wavelet packet basis functions

Empirical Bayes (EB) methods are used to model correlated and heavy-tailed time series background noise. Background noise is modeled as a multiband Students t process and estimates of the degree of freedom parameters and scaling parameters at each subband are used to characterize the background clutter. We compare this model with a multiband Gaussian model to demonstrate its robustness and accuracy with both underwater acoustic and seismic recordings. We demonstrate the usefulness of this model as a means of parameter estimation for wavelet packet denoising by applying the model to ocean acoustic recordings of whale calls and ground motion measurements of quarry blast explosions.

Environmental and Motion Effects on Orthogonal Frequency Division Multiplexed On‐Off Keying

Orthogonal frequency division multiplexing with on‐off keying (OFDM‐OOK) offers a means to near BPSK signaling rates with the simplicity of non‐coherent processing. At high frequencies source receiver acceleration induces time varying signal dilations that adversely effect both frequency alignment and multicarrier orthogonality. Dilation process estimation is coupled with a decision directed frequency domain channel magnitude response estimator for non‐coherent equalization of OFDM‐OOK. Joint co‐channel estimation is presented for near optimal decisions under loss of orthogonality due to Doppler spreading. Data from a moving source experiment at ranges from .8 km to 2.0 km, conducted in the shallow water off the coast of Elba Italy were used to test the feasibility of OFDM‐OOK at 18kHz center frequency with 4 kHz bandwidth. The effects of source receiver relative motion, frequency selectivity, and Doppler spreading on bit error rates were assessed. Mollification of frequency selective fading by diversity ...

Shallow water acoustic response and platform motion modeling via a hierarchical Gaussian mixture model

A hierarchical Gaussian mixture model is proposed to characterize shallow water acoustic response functions that are time-varying and sparse. The mixture model is based on the assumption that acoustic paths can be partitioned into two sets. The first is a relatively coherent set of arrivals that on average exhibit Doppler spreading about a mean Doppler and the remaining set is of multiple surface scattered paths that exhibit a spectrally flat Doppler. The hierarchy establishes constraints on the parameters of each of these Gaussian models such that coherent components of the response are both sparse and in the ensemble obey the Doppler spread profile. This is accomplished with a Bernoulli model that indicates the ensonification state of each element in the bi-frequency representation of the acoustic response function. Estimators of the time-varying acoustic response for the full duration of a broadband transmission are developed and employed to compensate for the shared time-varying dilation process among the coherent arrivals. The approach ameliorates response coherence degradation and can be employed to enhance coherent multi-path combining and is a useful alternative to time recursive estimation. The model is tested with acoustic communication recordings taken in shallow water at low signal-to-noise ratios.

A comparative study of differential and noncoherent direct sequence spread spectrum over underwater acoustic channels with multiuser interference

Spread spectrum communication provides a robust solution for underwater acoustic communication over noisy or otherwise unfavorable channels while allowing multiple users to occupy the same bandwidth at the same time. In this study we compare two variants, differential and noncoherent, of direct sequence code division multiple access (DS-CDMA) side-by-side on their performance over a range of channel conditions. Analysis of experimental data collected from the UNET06 experiment in St. Margarets Bay, Nova Scotia, Canada, reveals a tradeoff in performance between these two methods when the interference level and data rates change. Through further simulations we develop a good picture of the range of channel conditions for which one method will outperform the other. These results depend largely on the channel coherence value and the interference level: specifically, the differential scheme is better suited to coherent channels with low interference levels while the noncoherent scheme achieves better performance in high-interference scenarios and as the channel coherence decreases. Further, we observe that the noncoherent scheme is more robust relative to the differential alternative when the rate increases from 1 bit to 2 bits per symbol transmission.

High Frequency Coherent Acoustic Communications for the Networked Autonomous Littoral Surveillance System

The Networked autonomous littoral surveillance (NetALS) system is a wireless distributed bottom mounted sensor network being developed at DRDC Atlantic. NetALS will consist of a chain of bottom mounted sensor clusters that rely on ultrasonic communications in both synchronous time division and asynchronous frequency division schemes to transfer detection statistics from relativley cheap sensor nodes to more capable cluster heads where data fusion and decision making take place. A channel estimation based decision directed (CE-DD) algorithm for phase coherent demodulation of sensor data packets has been developed. This multi-channel CE-DD receiver relies on a time recursive use of conjugate gradient iterations to support computationally reduced channel estimation and is coupled to a Levin-son recursion for composite channel adaptive equalization. The algorithm was tested on shallow water data with source depth and bandwidth contraints as well as receiver ranges and apertures being consistent with a bottom mounted sensor network. Computational reductions beyond that of Levin-sons O(M 2) for adaptive filter construction lead to a slight performance degradation. Error rates for communication at 2 and 4 bps/Hz are reported at ranges from 300 m to 800 m with receive phone signal to noise ratios between 8 and 22 dB. The effect of limited aperture on the acoustic communication link is demonstrated.

Underwater acoustic communication experimentation: The acoustic communications and data storage (ACDS) system

The Naval Research laboratory has developed a sea‐going system, currently consisting of three acoustic communications and data storage (ACDS) buoys. The buoys can be deployed in the water column, moored to the ocean floor, or towed behind a ship to emulate an autonomous underwater vehicle (AUV). The system is intended for semi‐real‐time acoustic communications in situ and continuous recording of the raw acoustic data in the water for postexperiment analysis. The purpose is to study environmental issues affecting high data rate point‐to‐point acoustic communications as well as multiple‐in‐multiple‐out acoustic networking. Each ACDS has an acoustic projector and an array of eight hydrophones. It is designed for two frequency bands: 2–5 kHz and 15–25 kHz. The system has been deployed in several oceans. Modulation signals used include binary and quadrature phase‐shifted keying (BPSK/QPSK), frequency‐hopped frequency‐shifted keying (FH FSK), orthogonal frequency division multiplexing (OFDM) and code division m...

Acoustics education opportunities at UMass Dartmouth

The University of Massachusetts Dartmouth has a long tradition of research and course offerings in Acoustics and Signal Processing within the Department of Electrical and Computer Engineering dating back to the 1960s. The department has four full-time faculty with funded research programs in acoustics related areas as well as unique research/calibration facilities including a large underwater acoustic test facility and three fully autonomous underwater vehicles. UMass Dartmouth offers B.S., M.S., and Ph.D. degrees in Electrical Engineering with research opportunities and course offerings in fundamentals of acoustics, underwater acoustics, electro-acoustic transducers, medical ultrasonics, signal processing, speech processing, communications, and detection theory. The department works closely with the Center for Innovation and Entrepreneurship (CIE) and many local companies and government research centers. The poster will highlight course offerings and research opportunities. http://www.umassd.edu/engineer...

Tracking time varying multipath phase at very low signal to noise ratios

Diverse acoustic environments support multipath propagation. Estimating the arrival gains allows receiver structures to coherently combine acoustic energy for improved reception. In the case of mobile acoustic sources and receivers or dynamic boundaries, the amplitudes and phases of those arrivals are time varying such that estimation is made more difficult and typically entails some kind of phase tracking loop. This can be challenging as trackers are often formed as recursions in time employing previous observations to predict the phase at present, updating each phase estimate with the most recent observation. At extremely low SNR, recursive tracking can suffer loss of lock. Since a great deal of information about the instantaneous phase is contained in observations before and after it is judicious to seek estimators that exploit all of the observations in the signalling interval to infer the time varying response phase. Presented here is a scheme for simultaneous time varying phase estimation from the r...