James H. McClellan - Storming Media

Node Selection for Unattended Ground Sensor Networks While Interrogating Multiple Targets

DEC 2004

9 pages

Authors: Qiang Le; Lance M. Kaplan; James H. McClellan; CLARK ATLANTA UNIV GA DEPT OF ENGINEERING

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This work investigates the performance of a multiple target tracker that exploits bearings-only measurements from a network of unattended ground sensors (UGS). To conserve energy while interrogating multiple maneuvering targets, the tracker integrates node resource management with the multiple-mode probabilistic data association (PDA) or joint probabilistic data ASSOCIATION(JPDA) filter. Experiments show that for sufficiently separated targets, the global node selection leads to better geolocation performance than the closest selection approach ...

Vehicle Tracking using Acoustic and Video Sensors

04 OCT 2004

9 pages

Authors: Aswin C. Sankaranayanan; Qinfen Zheng; Rama Chellappa; Volkan Cevher; James H. McClellan; Gang Qian; MARYLAND UNIV COLLEGE PARK

In target tracking, fusing multi-modal sensor data under a power- performance trade-o is becoming increasingly important. Proper fusion of multiple modalities can help in achieving better tracking performance while decreasing the total power consumption. In this paper, we present a framework for tracking a target given joint acoustic and video observations from a co- located acoustic array and a video camera. We demonstrate on eld data that tracking of the ...

Duality for Multidimensional MEM (Maximum-Entropy Method) Spectral Analysis

15 JUL 1982

Authors: James H. McClellan; Stephen W. Lang; MASSACHUSETTS INST OF TECH CAMBRIDGE

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Spectral Estimation for Sensor Arrays

25 JAN 1982

Authors: Stephen W. Lang; James H. McClellan; MASSACHUSETTS INST OF TECH CAMBRIDGE

Multidimensional Spectral Estimation

07 JAN 1982

Authors: James H. McClellan; MASSACHUSETTS INST OF TECH CAMBRIDGE RESEARCH LAB OF ELECTRONICS

Multi-Dimensional MEM Spectral Estimation

1982

Authors: James H. McClellan; Stephen W. Lang; MASSACHUSETTS INST OF TECH CAMBRIDGE

Convergence of Iterative Nonexpansive Signal Reconstruction Algorithms.

01 AUG 1980

Authors: Victor T. Tom; Thomas F. Quatieri; Monson H. Hayes; James H. McClellan; MASSACHUSETTS INST OF TECH LEXINGTON LINCOLN LAB

A convergence proof of a special class of iterative signal reconstruction problems is presented. The proof relies on the concept of nonexpansive mappings which impose partial knowledge of the unknown signal in both the time and frequency domains. Two examples studied in detail are time limited extrapolation and phase-only reconstruction. The proof of convergence for the phase-only iteration is a new result. The generality of the approach allows the incorporation ...

Homomorphic Speech Analysis-Synthesis.

JAN 1978

5 pages

Authors: Alan V. Oppenheim; Arthur B. Baggeroer; James H. McClellan; MASSACHUSETTS INST OF TECH CAMBRIDGE RESEARCH LAB OF ELECTRONICS

This work is summarized in the following projects: homomorphic speech analysis-synthesis, enhancement of degraded speech, time-varying linear predictive coding of speech signals, and digital seismic signal processing.

Vector Radix Fast Fourier Transform,

1977

Authors: David B. Harris; James H. McClellan; David S. K. Chan; Hans W. Schuessler; MASSACHUSETTS INST OF TECH CAMBRIDGE RESEARCH LAB OF ELECTRONICS

A new radix-2 two-dimensional direct FFT is generalized in this paper to include arbitrary radices and non-square arrays. It is shown that the radix-4 version of this algorithm may require significantly fewer computations than conventional row-column transform methods. Also, the new algorithm eliminates the matrix transpose operation normally required when the array must reside on a bulk storage device. It requires the same number of passes over the array on ...

Hardware for the Fermat Number Transform.

01 APR 1975

Authors: James H. McClellan; MASSACHUSETTS INST OF TECH LEXINGTON LINCOLN LAB

The design and implementation of a hardware Fermat Number Transform (FNT) is described. The arithmetic logic design is treated in detail and a new data representation for integers modulo a Fermat number is derived. Some results of filter implementation with the FNT are shown to illustrate the use of the hardware. Finally, the FNT is compared with the Fast Fourier Transform (FFT) on the basis of hardware required for a ...