Automatic Target Recognition Device (atrd). PDF Download
Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Automatic Target Recognition Device (atrd). PDF full book. Access full book title Automatic Target Recognition Device (atrd). by J. W. Gerdes. Download full books in PDF and EPUB format.
Author: J. W. Gerdes
Publisher:
ISBN:
Category :
Languages : en
Pages : 262
Get Book Here
Book Description
Military targets imaged on reconnaissance aerial photography were automatically identified by parametric pattern recognition techniques implemented in an Automatic Target Recognition Device. Successful performance of this equipment over a 16-class strategic and tactical target recognition requirement has significant implications to the field of military photo interpretation. Target characteristics are represented in statistical form by operating on the video waveform representation of a target area. Clue extraction, machine learning, and target recognition are accomplished under computer control; target decisions and reliabilities appear as a typed output. A comprehensive test and evaluation phase involving 350 frames of aerial photography yield classification error rates from 0.05 to 0.25. (Author).
Author: J. W. Gerdes
Publisher:
ISBN:
Category :
Languages : en
Pages : 262
Get Book Here
Book Description
Military targets imaged on reconnaissance aerial photography were automatically identified by parametric pattern recognition techniques implemented in an Automatic Target Recognition Device. Successful performance of this equipment over a 16-class strategic and tactical target recognition requirement has significant implications to the field of military photo interpretation. Target characteristics are represented in statistical form by operating on the video waveform representation of a target area. Clue extraction, machine learning, and target recognition are accomplished under computer control; target decisions and reliabilities appear as a typed output. A comprehensive test and evaluation phase involving 350 frames of aerial photography yield classification error rates from 0.05 to 0.25. (Author).
Author: J W. Gerdes
Publisher:
ISBN:
Category : Pattern recognition systems
Languages : en
Pages : 244
Get Book Here
Book Description
Author: Bruce Jay Schachter
Publisher:
ISBN: 9781510618565
Category : Algorithms
Languages : en
Pages : 0
Get Book Here
Book Description
"This third edition of Automatic Target Recognition provides a roadmap for breakthrough ATR designs with increased intelligence, performance, and autonomy. Clear distinctions are made between military problems and comparable commercial Deep Learning problems. These considerations need to be understood by ATR engineers working in the defense industry as well as by their government customers. A reference design is provided for a next-generation ATR that can continuously learn from and adapt to its environment. The convergence of diverse forms of data on a single platform supports new capabilities and improved performance. This third edition broadens the notion of ATR to multisensor fusion. Radical continuous-learning ATR architectures, better integration of data sources, well-packaged sensors, and low-power teraflop chips will enable transformative military designs"--
Author:
Publisher:
ISBN:
Category : Image processing
Languages : en
Pages : 438
Get Book Here
Book Description
Author: Firooz Sadjadi
Publisher: Springer Science & Business Media
ISBN: 0387369430
Category : Science
Languages : en
Pages : 269
Get Book Here
Book Description
This book examines the roles of sensors, physics–based attributes, classification methods, and performance evaluation in automatic target recognition. It details target classification from small mine–like objects to large tactical vehicles. Also explored in the book are invariants of sensor and transmission transformations, which are crucial in the development of low latency and computationally manageable automatic target recognition systems.
Author: Bruce Jay Schachter
Publisher:
ISBN: 9781510631199
Category : Algorithms
Languages : en
Pages :
Get Book Here
Book Description
"From an engineer designing Automatic Target Recognition (ATR) systems for 40 years, comes this step-by-step guide to producing state-of-the-art ATR systems. The full spectrum of ATR designs are covered, from systems that just suggest targets to the warfighter to ATRs that could serve as the "brains" of lethal autonomous robots. Unfortunately, when it comes to ATR, some practitioners claim that their off-the-shelf canned algorithms magically leap from academic research to deployment with scant domain knowledge or system engineering. Deep learning is marketed more than deep understanding, deep explainability or deep fusion of on-platform resources. Naïve practitioners twist a few algorithmic knobs, and test on data of uncertain virtue, until performance seems superb. Unfortunately, with the enemy and ever changing environment conspiring to defeat detection and recognition, naively designed ATRs can fail in unexpected and spectacular ways. Trustworthy ATRs need to fuse multiple data and metadata sources, continuously learn from and adapt to their environment, interact with humans in natural language, and deal with in-library and out-of-library targets and confusor objects. This book provides a blueprint for smarter, more autonomous, more sophisticated ATR designs"--
Author: Wade Swoboda
Publisher:
ISBN:
Category :
Languages : en
Pages : 130
Get Book Here
Book Description
The Automatic Target Recognition Device (ATRD) demonstrated the feasibility of parametric pattern recognition techniques when applied to automatic recognition of military targets on aerial photography. Recent modifications, known as the Background Effects Study, provided a variable aperture capability which allows the ATRD to vary the size of its raster scan. The Variable Aperture Target Recognition Study is concerned with the development of techniques to utilize this variable aperture capability more effectively. The algorithms developed to utilize this capability in performing target isolation include the Aperture Control Algorithm (APCONAL) and the Associative Recognition Algorithm (ASRAL). APCONAL was designed to automatically set the aperture to the optimum size based upon certain preliminary parameter measurements. Performance tests using this algorithm revealed deteriorated recognition with a variable aperture capability. ASRAL was designed to improve the decision-making procedure of the ATRD. Through application of a hierarchial decision procedure, this algorithm was able to significantly improve the recognition performance of the ATRD. (Author).
Author: Fouad Sabry
Publisher: One Billion Knowledgeable
ISBN:
Category : Computers
Languages : en
Pages : 188
Get Book Here
Book Description
What Is Automatic Target Recognition The capacity of an algorithm or device to detect targets or other objects based on data acquired from sensors is referred to as automatic target recognition, abbreviated as ATR. How You Will Benefit (I) Insights, and validations about the following topics: Chapter 1: Automatic target recognition Chapter 2: Computer vision Chapter 3: Radar Chapter 4: Synthetic-aperture radar Chapter 5: Beamforming Chapter 6: Pulse-Doppler radar Chapter 7: Inverse synthetic-aperture radar Chapter 8: Radar signal characteristics Chapter 9: Time delay neural network Chapter 10: Track algorithm (II) Answering the public top questions about automatic target recognition. (III) Real world examples for the usage of automatic target recognition in many fields. (IV) 17 appendices to explain, briefly, 266 emerging technologies in each industry to have 360-degree full understanding of automatic target recognition' technologies. Who This Book Is For Professionals, undergraduate and graduate students, enthusiasts, hobbyists, and those who want to go beyond basic knowledge or information for any kind of automatic target recognition.
Author:
Publisher:
ISBN:
Category : Optical pattern recognition
Languages : en
Pages : 38
Get Book Here
Book Description
The operation and evaluation of a laboratory automatic target recognition (ATR) system is described. The ATR system was evaluated against its ability to acquire and track a specific target in the presence of a false targets and background clutter. A ten second air-to-sea image sequence that contained the infrared signatures of three ship targets and sea clutter was used as the test sequence. The evaluation involved assessing the system performance with default values for various system parameters. These were then varied and the effect on system performance measured. The ability to acquire and track the true target over a limited range of target orientations and the presence of low clutter and false targets was demonstrated. Furthermore, it was found that acquisition was easier if the target was somewhat broadside rather than end-on to the sensor. A shortcoming of the system was that it was not robust to minimal target obscuration. in addition, its ability to discriminate between the true and false targets was somewhat limited, and resulted in the acquisition and tracking of false targets. The evaluation showed that the system discrimination was improved by optimisation of a number or parameters, however, this also resulted in a reduction of its ability to acquire and track the true target. In addition, those parameters that were most important in terms of their effect on the system performance were determined., this greate.
Author: Nicholas Wager
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
Get Book Here
Book Description
This research investigated signal processing of two dimensional signals for the detection of targets in noise, particularly in complex background pattern noise. The researchers hypothesized that this type of noise was vulnerable to non-linear processing. They investigated whether the human eye/brain acting as a surrogate for a non-linear processor could outperform an optimum linear processor in a quantitative sense. The researchers did this by conducting computer experiments to determine the ability of an operator and an optimum linear filter to determine a known pattern's presence or absence in a noisy image. The performance of both the operator and optimum linear filter are recorded as probability of detection, probability of false alarm pairs, which the researchers use to determine effective signal-to-noise ratio. The performance of man versus machine (optimum linear filter) is compared quantitatively using the effective signal-to-noise ratio. Operator and machine/filter are tested against circular targets in Random White Gaussian noise and in satellite images. The researchers report that the machine filter outperforms the man when the details of both target and background are known in advance, but the man outperforms the machine/filter when the details are known only in a statistical sense.
