Dr. Walter Kuklinski Profile

Dr. Walter Kuklinski

Associate Professor at MITRE Corp

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Publications (6)

Proceedings Article | 17 April 2008 Paper

An initial investigation into incorporating human reports into a road-constrained random set tracker

David Winters, James Witkoskie, Walter Kuklinski

Proceedings Volume 6968, 69680Q (2008) https://doi.org/10.1117/12.777142

KEYWORDS: Roads, Sensors, Radar, Target detection, Detection and tracking algorithms, Filtering (signal processing), Motion models, Acoustics, Nonlinear filtering, Time metrology

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Proceedings Article | 14 April 2008 Paper

Target recognition using HRR profile-based incoherent SAR (InSAR) image formation

Nicholas O'Donoughue, Walter Kuklinski, Constantine Arabadjis

Proceedings Volume 6967, 69670F (2008) https://doi.org/10.1117/12.776977

KEYWORDS: Target recognition, Detection and tracking algorithms, Radar, Target detection, Synthetic aperture radar, Interferometric synthetic aperture radar, Image acquisition, Reflectivity, Algorithm development, Kinematics

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Feature-aided target verification is a challenging field of research, with the potential to yield significant increases in the confidence of re-established target tracks after kinematic confusion events. Using appropriate control algorithms airborne multi-mode radars can acquire a library of HRR (High Range Resolution) profiles for targets as they are tracked. When a kinematic confusion event occurs, such as a vehicle dropping below MDV (Minimum Detectable Velocity) for some period of time, or two target tracks crossing, it is necessary to utilize feature-aided tracking methods to correctly associate post-confusion tracks with pre-confusion tracks. Many current HRR profile target recognition methods focus on statistical characteristics of either individual profiles or sets of profiles taken over limited viewing angles. These methods have not proven to be very effective when the pre- and post- confusion libraries do not overlap in azimuth angle. To address this issue we propose a new approach to target recognition from HRR profiles. We present an algorithm that generates 2-D imagery of targets from the pre- and post-confusion libraries. These images are subsequently used as the input to a target recognition/classifier process. Since, center-aligned HRR Profiles, while ideal for processing, are not easily computed in field systems, as they require the airborne platform's center of rotation to line up with the geometric center of the moving target (this is impossible when multiple targets are being tracked), our algorithm is designed to work with HRR profiles that are aligned to the leading edge (the first detection above a threshold, commonly referred to as Edge-Aligned HRR profiles). Our simulated results demonstrate the effectiveness of this method for classifying target vehicles based on simulations using both overlapping and non-overlapping HRR profile sets. The algorithm was tested on several test cases using an input set of .28 m resolution XPATCH generated HRR profiles of 20 test vehicles (civilian and military) at various elevation angles.

Proceedings Article | 7 May 2007 Paper

Random set tracking and entropy based control applied to distributed sensor networks

David Stein, James Witkoskie, Stephen Theophanis, Walter Kuklinski

Proceedings Volume 6567, 656709 (2007) https://doi.org/10.1117/12.719294

KEYWORDS: Sensors, Roads, Detection and tracking algorithms, Target detection, Radar, Acoustics, Sensor networks, Motion models, Sensor fusion, Filtering (signal processing)

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Proceedings Article | 2 September 2004 Paper

3D SAR imaging using a hybrid decomposition superresolution technique

Walter Kuklinski, Andrea Kraay

Proceedings Volume 5427, (2004) https://doi.org/10.1117/12.548353

KEYWORDS: Synthetic aperture radar, Data modeling, 3D modeling, 3D image processing, Image processing, Image resolution, Statistical analysis, Super resolution, Data centers, Computer aided design

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Proceedings Article | 27 July 1999 Paper

Helicopter detection and classification using hidden Markov models

Walter Kuklinski, Sean O'Neil, Laurens Tromp

Proceedings Volume 3720, (1999) https://doi.org/10.1117/12.357152

KEYWORDS: Radar, Detection and tracking algorithms, Data modeling, Fourier transforms, Algorithm development, Databases, Expectation maximization algorithms, Doppler effect, Target detection, Process control

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Proceedings Article | 1 June 1992 Paper

Adaptive textural segmentation of medical images

Walter Kuklinski, Gordon Frost, Thomas MacLaughlin

Proceedings Volume 1652, (1992) https://doi.org/10.1117/12.59409

KEYWORDS: Image segmentation, Fractal analysis, Medical imaging, Image processing algorithms and systems, Bone, Algorithms, Detection and tracking algorithms, Image processing, Teeth, Fourier transforms

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Showing 5 of 6 publications

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