Flavio Lorenzelli

Stochastic Maximum-Likelihood DOA Estimation in the Presence of Unknown Nonuniform Noise

This correspondence investigates the direction-of-arrival (DOA) estimation of multiple narrowband sources in the presence of nonuniform white noise with an arbitrary diagonal covariance matrix. While both the deterministic and stochastic Cramer-Rao bound (CRB) and the deterministic maximum-likelihood (ML) DOA estimator under this model have been derived by Pesavento and Gershman, the stochastic ML DOA estimator under the same setting is still not available in the literature. In this correspondence, a new stochastic ML DOA estimator is derived. Its implementation is based on an iterative procedure which concentrates the log-likelihood function with respect to the signal and noise nuisance parameters in a stepwise fashion. A modified inverse iteration algorithm is also presented for the estimation of the noise parameters. Simulation results have shown that the proposed algorithm is able to provide significant performance improvement over the conventional uniform ML estimator in nonuniform noise environments and require only a few iterations to converge to the nonuniform stochastic CRB.

Maximum likelihood DOA estimation of multiple wideband sources in the presence of nonuniform sensor noise

We investigate the maximum likelihood (ML) direction-of-arrival (DOA) estimation of multiple wideband sources in the presence of unknown nonuniform sensor noise. New closed-form expression for the direction estimation Cramér-Rao-Bound (CRB) has been derived. The performance of the conventional wideband uniform ML estimator under nonuniform noise has been studied. In order to mitigate the performance degradation caused by the nonuniformity of the noise, a new deterministic wideband nonuniform ML DOA estimator is derived and two associated processing algorithms are proposed. The first algorithm is based on an iterative procedure which stepwise concentrates the log-likelihood function with respect to the DOAs and the noise nuisance parameters, while the second is a noniterative algorithm that maximizes the derived approximately concentrated log-likelihood function. The performance of the proposed algorithms is tested through extensive computer simulations. Simulation results show the stepwise-concentrated ML algorithm (SC-ML) requires only a few iterations to converge and both the SC-ML and the approximately-concentrated ML algorithm (AC-ML) attain a solution close to the derived CRB at high signal-to-noise ratio.

Distributed Gauss-Newton method for node loclaization in wireless sensor networks

We present distributed algorithms for sensor localization based on the Gauss-Newton method. Each sensor updates its estimated location by computing the Gauss-Newton step for a local cost function and choosing a proper step length. Then it transmits the updated estimate to all the neighboring sensors. The proposed algorithms provide non-increasing values of a global cost function. It is shown in the paper that the algorithms have computational complexity of O(n) per iteration and a reduced communication cost over centralized algorithms.

Detection and estimation for communication and radar systems

1. Introduction and motivation to detection and estimation 2. Review of probability and random processes 3. Statistical hypothesis testing theory 4. Detection of deterministic binary signals in Gaussian noises 5. M-ary detection and classification of deterministic signals 6. Non-coherent detection 7. Parameter estimation 8. Analytical and simulation methods for system performance analysis and design.

A high performance microphone array system for hearing aid applications

Microphone array technology has been proposed for various audio, teleconference, and hearing aid applications. By forming a focused beam toward the desired speech source, attenuating background noises and rejecting discrete spatial interferers, a microphone array can enhance the SNR/SIR in a noisy environment with significant improvement in speech intelligibility. An array can also perform real time source-localization or direction-of-arrival (DOA) estimation in various applications. We present a high performance prototype PC-based microphone array system for hearing aid applications. Algorithms for maximum energy criterion array weight design needed in the speech processing mode as well as modified broadband near-field MUSIC schemes in the search mode are discussed. Then a PC-based microphone array system using a TMS320C40 DSP is described. Preliminary study of equalizing non-uniform response microphones is also discussed. Finally, some array performance results in free-space and reverberant room conditions are presented.

A systolic implementation of the Chan/Foster RRQR algorithm

The rank revealing QR factorization is a useful tool in many signal processing applications; since it explicitly yields all the necessary information to solve rank deficient least-squares problems and subset selection problems, to compute signal and noise subspaces, etc. The authors present a systolic algorithm for computing a rank revealing QR factorization, and consider the performance of the algorithm. >

Subband processing for broadband microphone arrays

This paper considers array processing for wideband signals. The optimization techniques and associated performance results correspond to steerable but fixed beam microphone arrays, to be used in hearing aid applications, both in free-space and reverberant conditions. We first review the results on maximum energy (ME) broadband arrays. We subsequently formulate optimization criteria for array subband processing. The uniformly spaced subband and the non-uniformly spaced subband using quadrature mirror filter approaches are treated. Finally, various simulation results for free-space and reverberant conditions are presented to demonstrate the usefulness of this class of microphone arrays, as well as the feasibility of quadrature mirror filter-based subband processing.

Broadband array processing using subband techniques

In this paper, we consider array processing techniques for broadband signals. The optimisation techniques and associated performance results correspond to steerable but fixed beam microphone arrays, to be used in a variety of applications, both in free-space and in reverberant conditions. The proposed arrays maximize the energy concentration around the desired look directions, minimize reverberant disturbance, cancel individual interferers, and control the amount of signal distortion. Optimization criteria for array subband processing are also given. The uniformly spaced subband and the non-uniformly spaced subband using quadrature mirror filter approaches are treated. Finally, various simulation results for free-space and reverberant conditions are presented to demonstrate the usefulness of this class of microphone array, as well as the feasibility of quadrature mirror filter-based subband processing.

A systematic partitioning approach for LS and SVD problems to fixed size arrays with constraints

Design methodologies which incorporate partitioning in the projection of an algorithm onto a physical array of processors are of theoretical and practical interest in systolic/wavefront designs. A systematic partitioning technique utilizing the integral matrix approach for designing fixed-size arrays with desired user-imposed constraints is presented. These include I/O and interconnection constraints to obtain efficient communication link properties. Applications to the QR algorithm for eigenvalue decomposition and least square problems are given.<<ETX>>

Space-time beamforming for randomly distributed sensors

We briefly review the signal processing architecture of a wireless MEM sensor system for source detection, signal enhancement, localization, and identification. A blind beamformer using only the measured data of randomly distributed sensor to form a sample correlation matrix is proposed. The maximum power collection criterion is used to obtain array weights from the dominant eigenvector of the sample correlation matrix. An effective blind beamforming estimation of the time delays of the dominant source is demonstrated. Source localization based on a novel least-squares method for time delay estimation is also given. Array system performance based on analysis, simulation, and measured acoustical/seismic sensor data is presented. Applications of such a system to multimedia, intrusion detection, and surveillance are briefly discussed.