ICASSP99 Array Processing Applications II

Array Processing Applications II
Home Full List of Titles 1: Speech Processing CELP Coding Large Vocabulary Recognition Speech Analysis and Enhancement Acoustic Modeling I ASR Systems and Applications Topics in Speech Coding Speech Analysis Low Bit Rate Speech Coding I Robust Speech Recognition in Noisy Environments Speaker Recognition Acoustic Modeling II Speech Production and Synthesis Feature Extraction Robust Speech Recognition and Adaptation Low Bit Rate Speech Coding II Speech Understanding Language Modeling I 2: Speech Processing, Audio and Electroacoustics, and Neural Networks Acoustic Modeling III Lexical Issues/Search Speech Understanding and Systems Speech Analysis and Quantization Utterance Verification/Acoustic Modeling Language Modeling II Adaptation /Normalization Speech Enhancement Topics in Speaker and Language Recognition Echo Cancellation and Noise Control Coding Auditory Modeling, Hearing Aids and Applications of Signal Processing to Audio and Acoustics Spatial Audio Music Applications Application - Pattern Recognition & Speech Processing Theory & Neural Architecture Signal Separation Application - Image & Nonlinear Signal Processing 3: Signal Processing Theory & Methods I Filter Design and Structures Detection Wavelets Adaptive Filtering: Applications and Implementation Nonlinear Signals and Systems Time/Frequency and Time/Scale Analysis Signal Modeling and Representation Filterbank and Wavelet Applications Source and Signal Separation Filterbanks Emerging Applications and Fast Algorithms Frequency and Phase Estimation Spectral Analysis and Higher Order Statistics Signal Reconstruction Adaptive Filter Analysis Transforms and Statistical Estimation Markov and Bayesian Estimation and Classification 4: Signal Processing Theory & Methods II, Design and Implementation of Signal Processing Systems, Special Sessions, and Industry Technology Tracks System Identification, Equalization, and Noise Suppression Parameter Estimation Adaptive Filters: Algorithms and Performance DSP Development Tools VLSI Building Blocks DSP Architectures DSP System Design Education Recent Advances in Sampling Theory and Applications Steganography: Information Embedding, Digital Watermarking, and Data Hiding Speech Under Stress Physics-Based Signal Processing DSP Chips, Architectures and Implementations DSP Tools and Rapid Prototyping Communication Technologies Image and Video Technologies Automotive Applications / Industrial Signal Processing Speech and Audio Technologies Defense and Security Applications Biomedical Applications Voice and Media Processing Adaptive Interference Cancellation 5: Communications, Sensor Array and Multichannel Source Coding and Compression Compression and Modulation Channel Estimation and Equalization Blind Multiuser Communications Signal Processing for Communications I CDMA and Space-Time Processing Time-Varying Channels and Self-Recovering Receivers Signal Processing for Communications II Blind CDMA and Multi-Channel Equalization Multicarrier Communications Detection, Classification, Localization, and Tracking Radar and Sonar Signal Processing Array Processing: Direction Finding Array Processing Applications I Blind Identification, Separation, and Equalization Antenna Arrays for Communications Array Processing Applications II 6: Multimedia Signal Processing, Image and Multidimensional Signal Processing, Digital Signal Processing Education Multimedia Analysis and Retrieval Audio and Video Processing for Multimedia Applications Advanced Techniques in Multimedia Video Compression and Processing Image Coding Transform Techniques Restoration and Estimation Image Analysis Object Identification and Tracking Motion Estimation Medical Imaging Image and Multidimensional Signal Processing Applications I Segmentation Image and Multidimensional Signal Processing Applications II Facial Recognition and Analysis Digital Signal Processing Education Author Index A B C D E F G H I J K L M N O P Q R S T U V W X Y Z	Modeling and Estimation of Mutual Coupling in a Uniform Linear Array of Dipoles Authors: Thomas Svantesson, Page (NA) Paper number 1614 Abstract: The mutual coupling in a uniform linear array (ULA) of dipoles is calculated using basic electromagnetic concepts. Since the coupling often is unknown and needs to be estimated, a simpler model is proposed based on the electromagnetic analysis. The parametrization of this model is shown to be locally unambiguous. A necessary condition for the joint solution of directions and coupling parameters to be unique is also derived. Finally, the directions and coupling parameters are estimated using a maximum likelihood method. It is found that the simpler coupling model with just a few parameters well describes the full electromagnetic model. IC991614.PDF (From Author) IC991614.PDF (Rasterized) TOP Theoretical Noise Reduction Limits of the Generalized Sidelobe Canceller (GSC) for Speech Enhancement Authors: Joerg Bitzer, Uwe Simmer, Karl-Dirk Kammeyer, Page (NA) Paper number 1099 Abstract: In this paper we present an analysis of the generalized sidelobe canceller (GSC). It can be shown that the theoretical limits of the noise reduction performance depend only on the auto- and cross-spectral densities of the input signals. Furthermore, we compute the limits of the noise reduction performance for the theoretically determined diffuse noise field, which is an approximation for reverberant rooms. Our results will show that the GSC cannot reduce noise further than 1dB. These results were verified by simulation of reverberant environments. Only in sound-proofed rooms with a reverberation time less than 100ms the GSC performs well. IC991099.PDF (From Author) IC991099.PDF (Rasterized) TOP Adaptive Subarray Design for Interference Cancellation Authors: Ho Yang, Mary Ann Ingram, Page (NA) Paper number 2019 Abstract: A method for designing near-optimal, tapered subarrays for adaptive interference cancellation is proposed. The limited aperture or limited element feature of these subarrays enables a low-complexity hardware implementation of a partially adaptive array. This approach optimizes canceller performance for a given number of beams and a given number of elements per beams. IC992019.PDF (From Author) IC992019.PDF (Rasterized) TOP Classification Using Dirichlet Priors When the Training Data are Mislabeled Authors: Robert S Lynch Jr., Peter K Willett, Page (NA) Paper number 2209 Abstract: The average probability of error is used to demonstrate performance of a Bayesian classification test (referred to as the Combined Bayes Test (CBT)) given the training data of each class are mislabeled. The CBT combines the information in discrete training and test data to infer symbol probabilities, where a uniform Dirichlet prior (i.e., a noninformative prior of complete ignorance) is assumed for all classes. Using this prior it is shown how classification performance degrades when mislabeling exists in the training data, and this occurs with a severity that depends on the value of the mislabeling probabilities. However, an increase in the mislabeling probabilities are also shown to cause an increase in M* (i.e., the best quantization fineness). Further, even when the actual mislabeling probabilities are known by the CBT, it is not possible to achieve the classification performance obtainable without mislabeling. IC992209.PDF (From Author) IC992209.PDF (Rasterized) TOP A Constrained Optimal Data Association for Multiple Target Tracking Authors: Hong Jeong, POSTECH, Republic of Korea (Korea) Jeong-Ho Park, Page (NA) Paper number 1277 Abstract: One of the major problems in multiple target tracking is to obtain an accurate association between targets and noisy measurements. We introduce a new scheme, called Constrained Optimal Data Association (CODA), that finds the optimal data association by a MAP estimation method and uses a new energy function. In this scheme, the natural constraints between targets and measurements are defined so that they may contain missed detection and false alarm errors. Most current algorithms involve many heuristic adjustments of the parameters. Instead, this paper suggests an adaptive mechanism for such parameter updation. In this manner, the system automatically adapts to the clutter environment as it continuously changes in time and space, resulting in better association. Experimental results, using PDA, NNF, and CODA, show that the new approach reduces position errors in crossing trajectories by 13.9% on average compared to NNF. IC991277.PDF (From Author) IC991277.PDF (Rasterized) TOP Analysis of the Adaptive Matched Filter Algorithm for Cases with Mismatched Clutter Statistics Authors: Yumin Zhang, Rick S Blum, Page (NA) Paper number 1974 Abstract: In practical radar applications of the adaptive matched filter algorithm, the covariance matrix for the clutter-plus-noise is typically estimated using data taken from range cells surrounding the cell under test. In a nonhomogeneous environment, this can lead to a mismatch between the mean of the estimated covariance matrix and the true covariance matrix for the range cell under test. Closed form expressions are provided, which give the performance for such cases. These equations are exact in some cases and provide useful approximate results in others. Performance depends on a small number of important parameters. These parameters describe which types of mismatches are important and which are not. Numerical examples illustrate how performance varies with each of the important parameters. Monte Carlo simulations are included which closely match the predictions of our equations. IC991974.PDF (From Author) IC991974.PDF (Rasterized) TOP Approximate Minimum-norm Subspace Projection of Least-squares Weights Without the SVD Authors: Mark J Smith, Defence Evaluation and Research Agency, UK (U.K.) Ian K Proudler, Defence Evaluation and Research Agency,UK (U.K.) Page (NA) Paper number 1256 Abstract: A QR based technique is presented for estimating the approximate numerical rank and corresponding signal subspace of a matrix together with the subspace projection of the least squares weights. Theoretical difficulties associated with conventional QR factorisation are overcome by applying the technique of Row-Zeroing QR to the covariance matrix. Thresholding is simplified compared with the use of the data matrix as the diagonal value spectrum is sharpened and the subspace estimate is improved. An approximation to the minimum norm solution for the projection of the least squares weight onto the signal subspace of the data is obtained simply, without performing an SVD. IC991256.PDF (From Author) IC991256.PDF (Rasterized) TOP A Broadband Application Of Memoryless Narrowband GSC/NLMS Adaptive Beamformers Authors: Douglas Peters, Page (NA) Paper number 1037 Abstract: In this article, the adaptive performance of the normalized least mean-squares algorithm in the context of the generalized sidelobe canceller beamformer is considered. The implications of both the convergence behaviour and the misadjustment on various beamforming applications are discussed. In particular, an important case is identified for which there is near-instantaneous convergence. A misadjustment limit for which coherent post-processing is viable is also derived. Finally, a novel approach to coherent broadband beamforming is introduced and then tested via simulation. IC991037.PDF (From Author) IC991037.PDF (Rasterized) TOP