James H. McClellan

A unified approach to the design of optimum FIR linear-phase digital filters

A method for designing finite-duration impulse-response (FIR) linear-phase digital filters is presented in which the four possible cases for such filters are treated in a unified approach. It is shown how to reduce each case to the proper form so that the Remez exchange algorithm can be used to compute the best approximation to the desired frequency response. The result is that a very flexible and fast technique is available for FIR linear-phase filter design.

Multidimensional spectral estimation

Methods of multidimensional power spectral estimation are reviewed. Seven types of estimators are discussed: Fourier, separable, data extension, MLM, MEM, AR, and Pisarenko estimators. Particular emphasis is given to MEM where current research is quite active. Theoretical developments are reviewed and computational algorithms are discussed.

The discrete rotational Fourier transform

We define a discrete version of the angular Fourier transform and present the properties of the transform that show it to be a rotation in time-frequency space, this new transform is a generalization of the DFT. Efficient algorithms for its computation can then be based on the FFT and the eigenstructure of the DFT.

Estimating slowness dispersion from arrays of sonic logging waveforms

Acoustic wave propagation in a fluid‐filled borehole is affected by the type of rock which surrounds the hole. More specifically, the slowness dispersion of the various body‐wave and borehole modes depends to some extent on the properties of the rock. We have developed a technique for estimating the dispersion relations from data acquired by full‐waveform digital sonic array well‐logging tools. The technique is an extension of earlier work and is based on a variation of the well‐known Prony method of exponential modeling to estimate the spatial wavenumbers at each temporal frequency. This variation, known as the forward‐backward method of linear prediction, models the spatial propagation by purely real‐valued wavenumbers. The Prony exponential model is derived from the physics of borehole acoustics under the assumption that the formation does not vary in the axial or azimuthal dimensions across the aperture of the receiver array, but can vary arbitrarily in the radial dimension. The exponential model fits...

Target Tracking Using a Joint Acoustic Video System

In this paper, a multitarget tracking system for collocated video and acoustic sensors is presented. We formulate the tracking problem using a particle filter based on a state-space approach. We first discuss the acoustic state-space formulation whose observations use a sliding window of direction-of-arrival estimates. We then present the video state space that tracks a targets position on the image plane based on online adaptive appearance models. For the joint operation of the filter, we combine the state vectors of the individual modalities and also introduce a time-delay variable to handle the acoustic-video data synchronization issue, caused by acoustic propagation delays. A novel particle filter proposal strategy for joint state-space tracking is introduced, which places the random support of the joint filter where the final posterior is likely to lie. By using the Kullback-Leibler divergence measure, it is shown that the joint operation of the filter decreases the worst case divergence of the individual modalities. The resulting joint tracking filter is quite robust against video and acoustic occlusions due to our proposal strategy. Computer simulations are presented with synthetic and field data to demonstrate the filters performance

A simple proof of stability for all-pole linear prediction models

A simple method of proof is presented for the minimum-phase property of the all-pole model obtained in the autocorrelation method of linear prediction. The proof does not require knowledge of Levinsons recursion and extends easily to some special cases of the covariance method of linear prediction.

Experiences in teaching DSP first in the ECE curriculum

In this paper we describe experiences gained from teaching an introductory electrical engineering course based on digital signal processing rather than the traditional first course in analog circuit theory. We discuss our motivation for teaching DSP first, before covering analog circuits and systems. We describe the style of the course and point out difficulties, as well as advantages, in the organization of basic material. At Georgia Tech and Rose-Hulman, this beginning course has been required of all computer engineering majors. Finally, we make some comments about extending this approach to encompass a wider range of students from other disciplines.

Using multimedia and the Web to teach the theory of digital multimedia signals

The paper is about using multimedia via the World Wide Web in a course that teaches the theory behind digital audio and video. New course materials accessible via the Web are now used by students to explore demos that were presented in class. At Georgia Tech (and soon Rose-Hulman) a relatively new course that teaches the fundamentals of discrete signal processing (DSP) to sophomores is now required of computer engineering majors. Because DSP is involved in every aspect of multimedia information signals (coding, transmission, storage, playback etc.) the numerous in-class demos and all of the labs relate to the creation or analysis of sounds or images via computer. The course is structured so that the classroom time is used to explain theory, which is then implemented in lab to explore a given concept (e.g., sampling rates) or carry out a small design (e.g., write a MATLAB program to produce a sequence of sinusoidal waveforms that when sent to a speaker will play a song such as Ramblin Wreck). Traditionally, reading and homework assignments provide a link between lectures and labs. In this course the lecture/lab gap is closed via follow-up demos that are run by the students via the Web. Labs are assigned that require the students to run demos that illustrate and reinforce concepts introduced in the lecture. The homework assignments are designed to help the students to make the transition from the overview/demo mode to the implementation/lab mode. This leads them to implement something via MATLAB to test their answer.

Evaluation of partially adaptive STAP algorithms on the Mountain Top data set

In this paper we introduce a common framework for evaluating the performance of multiple weight, partially adaptive space-time adaptive processing (STAP) algorithms in terms of composite weight vectors. We then evaluate the performance of these STAP algorithms using synthetic and Mountain Top (MT) data (for airborne early warning radar) and address some limitations of high dimensional STAP algorithms in a nonstationary clutter environment. As part of the evaluation, we also familiarize the reader with the MT database and address important issues in processing the data.

An acoustic multiple target tracker

We propose a particle filter acoustic tracker to track multiple maneuvering targets using a state space formulation with a locally linear motion model. The observations are a batch of direction-of-arrival (DOA) estimates at various frequencies. The data likelihood incorporates the possibility of missing data as well as spurious DOA observations. By imposing smoothness constraints on the target motion, the particle filter is able to avoid data association problems. To make the filter computationally efficient, a proposal strategy based on approximating the full posterior with Newtons method is employed. Computer simulations show the algorithms performance