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Author: Christer Persson Publisher: ISBN: 9781423500759 Category : Languages : en Pages : 148
Book Description
The characteristic of low probability of intercept (LPI) radar makes it difficult to intercept with conventional signal intelligence methods so new interception methods need to be developed. This thesis initially describes a simulation of a polytime phase-coded LPI signal. The thesis then introduces a method for classification of LPI radar signals. The method utilizes a parallel tree structure with three separate 'branches' to exploit the image representation formed by three separate detection methods. Each detection method output is pre-processed and features are extracted using image processing. After processing the images, they are each fed into three separate neural networks to be classified. The classification output of each neural network is then combined and fed into a fourth neural network performing the final classification. The outcome of testing shows only 53%, which might be the result of the image representation of the detection methods not being distinct enough, the pre - processing/feature extraction not being able to extract relevant information or the neural networks not being properly trained. The thesis concludes with a brief discussion about a suitable method for image processing to extract significant parameters from a LPI signal.
Author: Christer Persson Publisher: ISBN: 9781423500759 Category : Languages : en Pages : 148
Book Description
The characteristic of low probability of intercept (LPI) radar makes it difficult to intercept with conventional signal intelligence methods so new interception methods need to be developed. This thesis initially describes a simulation of a polytime phase-coded LPI signal. The thesis then introduces a method for classification of LPI radar signals. The method utilizes a parallel tree structure with three separate 'branches' to exploit the image representation formed by three separate detection methods. Each detection method output is pre-processed and features are extracted using image processing. After processing the images, they are each fed into three separate neural networks to be classified. The classification output of each neural network is then combined and fed into a fourth neural network performing the final classification. The outcome of testing shows only 53%, which might be the result of the image representation of the detection methods not being distinct enough, the pre - processing/feature extraction not being able to extract relevant information or the neural networks not being properly trained. The thesis concludes with a brief discussion about a suitable method for image processing to extract significant parameters from a LPI signal.
Author: Phillip E. Pace Publisher: Artech House ISBN: 9781580533225 Category : Technology & Engineering Languages : en Pages : 496
Book Description
Pace (Naval Postgraduate School) presents the principles of radar design that enable a low probability of intercept (LPI) by a noncooperative intercept receiver. The RF system uses complex pulse compression CW waveforms, low side lobe antennas, and power management techniques to render itself virtually undetectable. The second part of the textbook investigates three algorithms for providing the intercept receiver with a processing gain that is close to the radar's matched filter processing gain, and quantifies their performance with LPI waveforms. The CD-ROM contains MATLAB code for evaluating the complex LPI radar-receiver interactions. Annotation : 2004 Book News, Inc., Portland, OR (booknews.com).
Author: Fernando L. Taboada Publisher: ISBN: 9781423507079 Category : Languages : en Pages : 297
Book Description
Low probability of intercept (LPI) is that property of an emitter that because of its low power, wide bandwidth, frequency variability, or other design attributes, makes it difficult to be detected or identified by means of passive intercept devices such as radar warning, electronic support and electronic intelligence receivers, In order to detect LPI radar waveforms new signal processing techniques are required This thesis first develops a MATLAB toolbox to generate important types of LPI waveforms based on frequency and phase modulation The power spectral density and the periodic ambiguity function are examined for each waveforms These signals are then used to test a novel signal processing technique that detects the waveforms parameters and classifies the intercepted signal in various degrees of noise, The technique is based on the use of parallel filter (sub-band) arrays and higher order statistics (third- order cumulant estimator) Each sub-band signal is treated individually and is followed by the third-order estimator in order to suppress any symmetrical noise that might be present, The significance of this technique is that it separates the LPI waveforms in small frequency bands, providing a detailed time-frequency description of the unknown signal, Finally, the resulting output matrix is processed by a feature extraction routine to detect the waveforms parameters Identification of the signal is based on the modulation parameters detected,
Author: Antonio F. Lime, Jr. Publisher: ISBN: 9781423507642 Category : Languages : en Pages : 186
Book Description
LPI radar is a class of radar systems that possess certain performance characteristics that make them nearly undetectable by today's digital intercept receivers, This presents a significant tactical problem in the battle space To detect these types of radar, new digital receivers that use sophisticated signal processing techniques are required This thesis investigates the use of cyclostationary processing to extract the modulation parameters from a variety of continuous-wave (CW) low-probability-of- intercept (LPI) radar waveforms, The cyclostationary detection techniques described exploit the fact that digital signals vary in time with single or multiple periodicities, because they have spectral correlation, namely, non-zero correlation between certain frequency components, at certain frequency shifts, The use of cyclostationary signal processing in a non-cooperative intercept receiver can help identify the particular emitter and can help develop electronic attacks, LPI CW waveforms examined include Frank codes, polyphase codes (Pt through P4), Frequency Modulated CW (FMCW), Costas frequencies as well as several frequency-shift- keying/phase-shift-keying (FSK/PSK) waveforms It is shown that for signal-to- noise ratios of OdB and -6 dB, the cyclostationary signal processing can extract the modulation parameters necessary in order to distinguish among the various types of LPI modulations.
Author: Fulvio Gini Publisher: John Wiley & Sons ISBN: 0470283149 Category : Science Languages : en Pages : 287
Book Description
Discover the technology for the next generation of radar systems Here is the first book that brings together the key concepts essential for the application of Knowledge Based Systems (KBS) to radar detection, tracking, classification, and scheduling. The book highlights the latest advances in both KBS and radar signal and data processing, presenting a range of perspectives and innovative results that have set the stage for the next generation of adaptive radar systems. The book begins with a chapter introducing the concept of Knowledge Based (KB) radar. The remaining nine chapters focus on current developments and recent applications of KB concepts to specific radar functions. Among the key topics explored are: Fundamentals of relevant KB techniques KB solutions as they apply to the general radar problem KBS applications for the constant false-alarm rate processor KB control for space-time adaptive processing KB techniques applied to existing radar systems Integrated end-to-end radar signals Data processing with overarching KB control All chapters are self-contained, enabling readers to focus on those topics of greatest interest. Each one begins with introductory remarks, moves on to detailed discussions and analysis, and ends with a list of references. Throughout the presentation, the authors offer examples of how KBS works and how it can dramatically improve radar performance and capability. Moreover, the authors forecast the impact of KB technology on future systems, including important civilian, military, and homeland defense applications. With chapters contributed by leading international researchers and pioneers in the field, this text is recommended for both students and professionals in radar and sonar detection, tracking, and classification and radar resource management.
Author: Publisher: ISBN: Category : Languages : en Pages : 186
Book Description
LPI radar is a class of radar systems that possess certain performance characteristics that make them nearly undetectable by today's digital intercept receivers, This presents a significant tactical problem in the battle space To detect these types of radar, new digital receivers that use sophisticated signal processing techniques are required This thesis investigates the use of cyclostationary processing to extract the modulation parameters from a variety of continuous-wave (CW) low-probability-of- intercept (LPI) radar waveforms, The cyclostationary detection techniques described exploit the fact that digital signals vary in time with single or multiple periodicities, because they have spectral correlation, namely, non-zero correlation between certain frequency components, at certain frequency shifts, The use of cyclostationary signal processing in a non-cooperative intercept receiver can help identify the particular emitter and can help develop electronic attacks, LPI CW waveforms examined include Frank codes, polyphase codes (Pt through P4), Frequency Modulated CW (FMCW), Costas frequencies as well as several frequency-shift-keying/phase-shift-keying (FSK/PSK) waveforms It is shown that for signal-to-noise ratios of OdB and -6 dB, the cyclostationary signal processing can extract the modulation parameters necessary in order to distinguish among the various types of LPI modulations.
Author: Publisher: ISBN: Category : Radar Languages : en Pages : 162
Book Description
LPI radar is a class of radar systems possessing certain performance characteristics that make them nearly undetectable by today's digital intercept receivers. This presents a significant tactical problem in the battle space. To detect these types of radar, new digital receivers that use sophisticated signal processing techniques are required. This thesis investigates the use of cyclostationary processing to extract the modulation parameters from a variety of continuous-wave (CW) low-probability-of-intercept (LPI) radar waveforms. The cyclostationary detection techniques described exploit the fact that digital signals vary in time with single or multiple periodicity, owing to their spectral correlation, namely non-zero correlation between certain frequency components, at certain frequency shifts. The use of cyclostationary signal processing in a non-cooperative intercept receiver can help identify the particular emitter and aid in the development of electronic attack signals. LPI CW waveforms examined include Frank codes, P1 through P4, Frequency Modulated CW (FMCW), Costas frequencies as well as several frequency-shift-keying/phase-shift-keying (FSK/PSK) waveforms. This thesis show that for signal-to-noise ratios of 0 dB and -6 dB, the cyclostationary signal processing can extract the modulation parameters necessary in order to distinguish between the various types of LPI modulations.
Author: Peter Knee Publisher: Morgan & Claypool Publishers ISBN: 1627050345 Category : Computers Languages : en Pages : 88
Book Description
Although the field of sparse representations is relatively new, research activities in academic and industrial research labs are already producing encouraging results. The sparse signal or parameter model motivated several researchers and practitioners to explore high complexity/wide bandwidth applications such as Digital TV, MRI processing, and certain defense applications. The potential signal processing advancements in this area may influence radar technologies. This book presents the basic mathematical concepts along with a number of useful MATLAB(R) examples to emphasize the practical implementations both inside and outside the radar field.
Author: Francesco Bandiera Publisher: Springer Nature ISBN: 3031025326 Category : Technology & Engineering Languages : en Pages : 95
Book Description
Adaptive detection of signals embedded in correlated Gaussian noise has been an active field of research in the last decades. This topic is important in many areas of signal processing such as, just to give some examples, radar, sonar, communications, and hyperspectral imaging. Most of the existing adaptive algorithms have been designed following the lead of the derivation of Kelly's detector which assumes perfect knowledge of the target steering vector. However, in realistic scenarios, mismatches are likely to occur due to both environmental and instrumental factors. When a mismatched signal is present in the data under test, conventional algorithms may suffer severe performance degradation. The presence of strong interferers in the cell under test makes the detection task even more challenging. An effective way to cope with this scenario relies on the use of "tunable" detectors, i.e., detectors capable of changing their directivity through the tuning of proper parameters. The aim of this book is to present some recent advances in the design of tunable detectors and the focus is on the so-called two-stage detectors, i.e., adaptive algorithms obtained cascading two detectors with opposite behaviors. We derive exact closed-form expressions for the resulting probability of false alarm and the probability of detection for both matched and mismatched signals embedded in homogeneous Gaussian noise. It turns out that such solutions guarantee a wide operational range in terms of tunability while retaining, at the same time, an overall performance in presence of matched signals commensurate with Kelly's detector. Table of Contents: Introduction / Adaptive Radar Detection of Targets / Adaptive Detection Schemes for Mismatched Signals / Enhanced Adaptive Sidelobe Blanking Algorithms / Conclusions
Author: Christer Persson
Author: Christer Persson
Author: Phillip E. Pace
Author: Fernando L. Taboada
Author: Antonio F. Lime, Jr.
Author: Fulvio Gini
Author: 
Author: 
Author: Peter Knee
Author: Daniel Lee Stevens
Author: Francesco Bandiera