Classificaiton and Discrimination of Sources with Time-Varying Frequency and Spatial Spectra

The research efforts proceeded on different fronts leading to advances in target detection, tracking, and characterization for over the Over-the-Horizon radar applications as well as for urban sensing and through-the-wall radar imaging applications. Improved characterizations of the targets are achi...

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Bibliographic Details
Main Authors: Amin, Moeness G, Zhang, Yimin, Wang, Genyuan, Obeidat, Baha, Setlur, Pawan, Estephan, Habib
Format: Report
Language:English
Subjects:
Active & Passive Radar Detection & Equipment
CHIRP RADAR
DIRECTION OF ARRIVAL ESTIMATION
DOPPLER RADAR
FREQUENCY MODULATION
HOUGH TRANSFORMS
MICRODOPPLER
MOVING TARGETS
MULTIPLE HYPOTHESIS TESTING
OVER THE HORIZON RADAR
POLARIZATION
RADAR SIGNALS
SIGNAL PROCESSING
TARGET CLASSIFICATION
TARGET DETECTION
Target Direction, Range and Position Finding
TARGET SIGNATURES
THROUGH THE WALL RADAR IMAGING
TIME FREQUENCY DISTRIBUTION
TRACKING
URBAN AREAS
WIDEBAND
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Summary:The research efforts proceeded on different fronts leading to advances in target detection, tracking, and characterization for over the Over-the-Horizon radar applications as well as for urban sensing and through-the-wall radar imaging applications. Improved characterizations of the targets are achieved using multiple OTHRs operating simultaneously as compared to a single OTHR operating alone. We have introduced the spatial polarimetric time-frequency distributions (SPTFDs) as a platform for processing polarized nonstationary signals incident on multiple dual-polarized double-feed antennas. For urban sensing applications two different techniques to provide high imaging quality of scenes behind walls when wall characteristic are unknown were proposed. When considering chirp radar signals or complex Doppler target signatures we have improved blind separation of signals with time-varying spectra using Multiple Hypothesis Testing. Further, we have enhanced the estimation of the phase parameters of mono- or multi-component frequency modulated signals from noisy observations using the Time-Frequency Hough Transform.