Autonomous Non-linear Classification of LPI Radar Signal Modulations PDF Download

Author: Phillip E. Pace
Publisher: Artech House
ISBN: 9781580533225
Category : Technology & Engineering
Languages : en
Pages : 496

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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:
Publisher:
ISBN:
Category : Algorithms
Languages : en
Pages : 195

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Book Description
In this thesis, an autonomous feature extraction algorithm for classification of Low Probability of Intercept (LPI) radar modulations is investigated. A software engineering architecture that allows a full investigation of various preprocessing algorithms and classification techniques is applied to a database of important LPI radar waveform modulations including Frequency Modulation Continuous Waveform (FMCW), Phase Shift Keying (PSK), Frequency Shift Keying (FSK) and combined PSK and FSK. The architecture uses time-frequency detection techniques to identify the parameters of the modulation. These include the Wigner-Ville distribution, the Choi-Williams distribution and quadrature mirror filtering. Autonomous time-frequency image cropping algorithm is followed by a feature extraction algorithm based on principal components analysis. Classification networks include the multilayer perceptron, the radial basis function and the probabilistic neural networks. Lastly, using image processing techniques on images obtained by the Wigner-Ville distribution and the Choi-Williams distribution, two autonomous extraction algorithms are investigated to derive the significant modulation parameters of polyphase coded LPI radar waveform modulations.

Author:
Publisher:
ISBN:
Category : Algorithms
Languages : en
Pages : 78

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Book Description
Three autonomous cropping and feature extraction algorithms are examined that can be used for classification of low probability of intercept radar modulations using time-frequency (T-F) images. The first approach, Erosion Dilation Adaptive Binarization (EDAB), uses erosion and a new adaptive threshold binarization algorithm embedded within a recursive dilation process to determine the modulation energy centroid (radar's carrier frequency) and properly place a fixed-width cropping window. The second approach, Marginal Frequency Adaptive Binarization (MFAB), uses the marginal frequency distribution and the adaptive threshold binarization algorithm to determine the start and stop frequencies of the modulation energy to locate and adapt the size of the cropping window. The third approach, Fast Image Filtering, uses the fast Fourier transform and a Gaussian lowpass filter to isolate the modulation energy. The modulation is then cropped from the original T-F image and the adaptive binarization algorithm is used again to compute a binary feature vector for input into a classification network. The binary feature vector allows the image detail to be preserved without overwhelming the classification network that follows. A multi-layer perceptron and a radial basis function network are used for classification and the results are compared. Classification results for nine simulated radar modulations are shown to demonstrate the three feature-extraction approaches and quantify the performance of the algorithms. It is shown that the best results are obtained using the Choi-Williams distribution followed by the MFAB algorithm and a multi-layer perceptron. This setup produced an overall percent correct classification (Pcc) of 87.2% for testing with noise variation and 77.8% for testing with modulation variation. In an operational context, the ability to process and classify LPI signals autonomously allows the operator in the field to receive real-time results.

Author: Antonio F. Lime, Jr.
Publisher:
ISBN: 9781423507642
Category :
Languages : en
Pages : 186

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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: Fernando L. Taboada
Publisher:
ISBN: 9781423507079
Category :
Languages : en
Pages : 297

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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: Christer Persson
Publisher:
ISBN: 9781423500759
Category :
Languages : en
Pages : 148

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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: Jen-Yu Gau
Publisher:
ISBN: 9781423507581
Category :
Languages : en
Pages : 166

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Book Description
The parameters of Low Probability of Intercept (LPI) radar signals are hard to identity by using traditional periodogram signal processing techniques. Using the Wigner Distribution (WD), this thesis examines eight types of LPI radar signals. Signal to noise ratios of 0 dB and -6 dB are also investigated. The eight types LPI radar signals examined include Frequency Modulation Continuous Wave (FMCW), Frank code, Pt code, P2 code, P3 code, P4 code, COSTAS frequency hopping and Phase Shift Keying/Frequency Shift Keying (PSK/FSK) signals. Binary Phase Shift Keying (BPSK) signals although not used in modern LPI radars are also examined to further illustrate the principal characteristics of the WD.

Author: Jonah Gamba
Publisher: Springer
ISBN: 9811391939
Category : Technology & Engineering
Languages : en
Pages : 142

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Book Description
The subject of this book is theory, principles and methods used in radar algorithm development with a special focus on automotive radar signal processing. In the automotive industry, autonomous driving is currently a hot topic that leads to numerous applications for both safety and driving comfort. It is estimated that full autonomous driving will be realized in the next twenty to thirty years and one of the enabling technologies is radar sensing. This book presents both detection and tracking topics specifically for automotive radar processing. It provides illustrations, figures and tables for the reader to quickly grasp the concepts and start working on practical solutions. The complete and comprehensive coverage of the topic provides both professionals and newcomers with all the essential methods and tools required to successfully implement and evaluate automotive radar processing algorithms.

Author:
Publisher:
ISBN:
Category : Radar
Languages : en
Pages : 162

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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:
Publisher:
ISBN:
Category :
Languages : en
Pages : 186

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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.