Autonomous non-linear classification of LPI radar signal modulations
Gulum, Taylan O.
Pace, Phillip E.
MetadataShow full item record
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.
Showing items related by title, author, creator and subject.
Mcgowan, Jeremy A. (Monterey, CA; Naval Postgraduate School, 2018-06);The potential feasibility for on-board image processing on small satellites was investigated to meet rapid revisit requirements for Maritime Domain Awareness (MDA). Hardware and software solutions for on-board processing ...
Huat, Lim Chin (Monterey, California. Naval Postgraduate School, 1996-03);This thesis investigated a laboratory synthetic aperture sonar designed to test the algorithms and techniques needed to detect, classify and identify minelike objects. Previous synthetic aperture sonar work at NPS achieved ...
McIver, Charles A. (Monterey, California: Naval Postgraduate School, 2017-03);Remote-sensing analysis is conducted for the Naval Postgraduate School campus, containing buildings, impervious surfaces (asphalt and concrete), natural ground, and vegetation. Data is from the Optech Titan, providing ...