Signals, systems, and transforms
Signals, systems, and transforms
Fundamentals of statistical signal processing: estimation theory
Fundamentals of statistical signal processing: estimation theory
Time-frequency analysis: theory and applications
Time-frequency analysis: theory and applications
Fractional quaternion Fourier transform, convolution and correlation
Signal Processing
Comments on “The Cramer-Rao lower bounds for signals withconstant amplitude and polynomial phase”
IEEE Transactions on Signal Processing
Discrete fractional Fourier transform based on orthogonalprojections
IEEE Transactions on Signal Processing
The discrete fractional Fourier transform
IEEE Transactions on Signal Processing
The fractional Fourier transform and time-frequency representations
IEEE Transactions on Signal Processing
Linear frequency-modulated signal detection using Radon-ambiguitytransform
IEEE Transactions on Signal Processing
A method for the discrete fractional Fourier transform computation
IEEE Transactions on Signal Processing
Digital computation of the fractional Fourier transform
IEEE Transactions on Signal Processing
IEEE Transactions on Signal Processing
Kernel design for time-frequency signal analysis using the Radontransform
IEEE Transactions on Signal Processing
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Fractional autocorrelation of a signal defined for a fractional domain at an arbitrary angle of the time-frequency plane exactly corresponds to the radial slice of the radar ambiguity function (AF) of that signal at that particular angle. In other words, any radial cross-section of the radar AF, that itself serves as a two-dimensional correlation function, can be readily obtained by computing fractional autocorrelation, which is one-dimensional. In this manuscript, we employ a novel fast detection statistic derived utilizing this property of fractional autocorrelation for computationally efficient detection of pulse compression radar waveforms such as the step linear frequency modulated (SLFM) signal, Frank code, and P1 and P4 codes. As a byproduct, the detection algorithm also serves as an unbiased estimator of the sweep rate (chirp rate) of the considered radar waveforms. Through receiver operating characteristic (ROC) curves, we investigate the performance of the detection statistic and compare it against the matched filter and generalized likelihood ratio test (GLRT) detectors of the linear frequency modulated (LFM) signal. Performance of the accompanying sweep rate estimator is also demonstrated using mean square error (MSE) curves and compared with the optimum maximum likelihood (ML) estimator of the sweep rate parameter of the LFM signal.