Each year, General Dynamics distributes Medal Paper Awards to employees whose technical reports, journals, symposia presentations or other written materials significantly contributed during the year to their technical discipline, the nation, customers and General Dynamics. 

Winning papers are also available from 2004 and 2003.

2005 Medal Paper Award winners

A Cluster-Based Approach for Detecting Man-Made Objects and Changes in Imagery
Mark J. Carlotto

Summary: A new unified approach to object and change detection is presented that involves clustering and analyzing the distribution of pixel values within clusters over one or more images. Cluster-based anomaly detection (CBAD) can detect man-made objects that are: 1) present in a single multiband image; 2) appear or disappear between two images acquired at different times; or 3) manifest themselves as spectral differences between two sets of bands acquired at the same time.

An Improved Version of the Circular Near Field-to-Far Field Transformation (CNFFFT)
Ivan J. LaHaie, Christopher M. Coleman, Scott A. Rice

Summary: For many years now, GDAIS has described the development, characterization, and performance of an imagebased circular near field-to-far field transformation (CNFFFT) for predicting far-field radar cross-section (RCS) from near-field measurements collected on a circular path around the target. In this paper, we present an improved version of the algorithm that avoids a stationary phase approximation inherent in earlier versions of the technique. The improvement is realized by modifying the range-domain weighting used to implement the frequency derivative in the existing method. A similar modification was presented in the context of linear near-field measurements in an earlier AMTA paper. Numerical simulations are presented that demonstrate the improvement afforded by the technique in predicting far-field RCS patterns from near-field data collected using typical bandwidths and standoff distances. An additional benefit of the revised algorithm is that it readily admits a formulation that includes antenna pattern compensation, as described in a companion paper.

Limiting Performance Analysis of Biomechanical Systems for Optimal Injury Control -- Part 2: Applications
Zhiqing Cheng

Summary:  Applications of the limiting performance analysis of biomechanical systems for optimal injury control are presented. A brief review of applications based on lumped-parameter injury models is given, which includes the problems of helmets with head injuries, seat belts with thoracic injurieshelicopter seat cushions with spinal injuries, toepan padding with lower limb injuries, and child seat sled test corridors with best and worst responses. Then, the problem of ejection seat cushions for the optimal control of spinal injuries is investigated. A rigid multi-body model is developed to describe the biodynamics of the entire system including the occupant. Peak lumbar load in the vertical direction is used as the safety performance index for ejection seat cushions and is minimized. Parametric optimization is performed on a particular cushion to find its optimal performance.

Minimizing Average Network Delay for Ultra-Wideband Wireless Networks
Christopher Taggart

Summary:  Ultra-wideband wireless (UWB) may provide the physical layer for high capacity personal area networks in the
future. Certain characteristics of the wireless links possible using this technology give rise to properties not seen with other wireless
technologies. Two such properties are long synchronization times for link establishment and the ability to change individual link
capacities by choosing PN codes of different lengths. This paper formulates a novel routing problem in UWB; in particular we investigate the impact of UWB physical layer characteristics on average network transit delay for a UWB network with a ring topology. The paper derives an expression of average network
transit delay as a function of the capacity between each pair of nodes in the network.

Modeling of Autoregressive Moving Average Models to Non-Gaussian Processes Encountering Noise with Impulses
Preston D. Frazier

Summary: In statistical signal processing, parametric modeling of non-Gaussian processes experiencing noise interference is a very important research topic. Particularly challenging to some researchers is how to estimate signals encountering stochastic noise process exhibiting sharp spikes. The authors propose the use of systems with impulse effect along with the classic autoregressive moving average model as a novel parametric modeling tool to successfully estimate these specific processes. The proficiency of this original system is illustrated in a performance table and compared to well-known parametric estimation technique.

Multitarget Tracking using the Joint Multitarget Probability Density
Dr. Chris Kreucher, Dr. Keith Kastella

Summary: This paper addresses the problem of tracking multiple moving targets by recursively estimating the joint multitarget probability density (JMPD). Estimation of the JMPD is done in a Bayesian framework and provides a method for tracking multiple targets which allows nonlinear target motion and measurement to state coupling as well as non-Gaussian target state densities. The JMPD technique simultaneously estimates both the target states and the number of targets in the surveillance region based on the set of measurements made. In this paper, we give an implementation of the JMPD method based on particle filtering techniques and provide an adaptive sampling scheme which explicitly models the multitarget nature of the problem. We show that this implementation of the JMPD technique provides a natural way to track a collection of targets, is computationally tractable, and performs well under difficult conditions such as target crossing, convoy movement, and low measurement SNR.

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