Moving target detection and characterization with circular SAR
Leonid Perlovsky,Roman Ilin,Ross Deming,Robert Linnehan,Freeman C. Lin +4 more
- pp 661-666
TLDR
This work examines ground target detection and characterization from radar data, which incorporates a modelbased optimization method called dynamic logic (DL) and applies it to a prototype airborne radar platform called Gotcha, developed by the Air Force Research Laboratory/Sensors Directorate/Automatic Target recognition Division in recent years.Abstract:
In this work, we examine ground target detection and characterization from radar data, which incorporates a modelbased optimization method called dynamic logic (DL). We apply our methodology to a prototype airborne radar platform called Gotcha, developed by the Air Force Research Laboratory/Sensors Directorate/Automatic Target Recognition Division in recent years. The aircraft traces out a circular path around an area of interest, and the onboard, side-looking radar transmits and receives energy at a constant pulse repetition frequency, while the main beam direction is maintained at a fixed aim point on the ground. Data collected during any appropriate length arc of the flight path can be used to create synthetic aperture radar (SAR) images of the ground. The data can also be used for ground moving target indication (GMTI) and provide Doppler/Range imagery of the same ground area. Our approach combines the computation of Range-Doppler surfaces and a variable target velocity backprojection SAR method. Potential targets are detected using multiple backprojection images and features are extracted using adaptive mixture models. We demonstrate the feasibility of our approach using target truth information provided with the Gotcha dataset. We outline the steps toward implementing a comprehensive automatic target tracking solution based on presented methodology.read more
Citations
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Journal ArticleDOI
Ground Moving Target Trajectory Reconstruction in Single-Channel Circular SAR
TL;DR: This paper analyzes the performances of a method that reconstructs the real target trajectory given the apparent positions of the moving target measured on SAR images acquired along a circular trajectory.
Phase history decomposition for efficient scatterer classification in SAR imagery
TL;DR: In this paper, a new theory and algorithm for scatterer classification in SAR imagery is presented, which analyzes local peaks in the subimages to determine locations and geometric shapes of scatterers in the scene.
Journal Article
Synthetic aperture radar and moving target indication
TL;DR: In this article, the problems about the detection of moving objects and observation by the synthetic aperture radars (SAR) are described, and the authors also explain the moving target indication (MTI) SAR approach using the reflectivity displacement method, the MTI SAR aproach using the multilook image displacement method.
Dissertation
Reconstruction de trajectoires de cibles mobiles en imagerie RSO aéroportée
TL;DR: L’imagerie RSO circulaire aeroportee permet d’obtenir de nombreuses informations sur les zones imagees et sur les cibles mobiles, notamment de vitesse et d”acceleration.
Dissertation
Reconstruction de trajectoires de cibles mobiles en imagerie RSO circulaire aéroportée
TL;DR: In this article, a methode de reconstruction de trajectoire de cibles mobiles en imagerie RSO circulaire monovoie is proposed, and the methode is evaluated on two jeux de donnees reelles acquises par le capteur SETHI et RAMSES NG.
References
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Book
Fundamentals of Radar Signal Processing
TL;DR: This revised edition of Fundamentals of Radar Signal Processing provides in-depth coverage of radar digital signal processing fundamentals and applications and has been updated to include coverage of measurement accuracy and target tracking.
Book
Neural Networks and Intellect: Using Model-Based Concepts
TL;DR: The inner workings of the human mind, consciousness, language-mind relationships, learning, and emotions are explored mathematically in amazing details in Neural Networks and Intellect: Using Model-Based Concepts.
Proceedings ArticleDOI
A challenge problem for 2D/3D imaging of targets from a volumetric data set in an urban environment
Curtis H. Casteel,LeRoy A. Gorham,Michael J. Minardi,Steven Scarborough,Kiranmai D. Naidu,Uttam Majumder +5 more
TL;DR: The Gotcha Volumetric SAR Data Set as discussed by the authors provides the community with X-band Synthetic Aperture Radar (SAR) data that supports the development of new algorithms for high-resolution 2D/3D imaging.
Journal ArticleDOI
Neural Networks for Improved Tracking
Leonid Perlovsky,R.W. Deming +1 more
TL;DR: The neural tracker overcomes combinatorial complexity of tracking in highly cluttered scenarios and results in about 20-dB (two orders of magnitude) improvement in signal-to-clutter ratio.
Journal ArticleDOI
Multi-Target/Multi-Sensor Tracking using Only Range and Doppler Measurements
TL;DR: A new approach is described for combining range and Doppler data from multiple radar platforms to perform multi-target detection and tracking, with promising results that demonstrate robustness in the presence of nonhomogeneous clutter.