Given a (FFT-sized) frame of data, and detection of a spectral component statistically above the noise floor in the FFT of this window, what characteristics or signal analysis could be used to determine that this spectral component is more likely to be a linearly swept sinusoid, rather than one that is stationary across the frame?
And, assuming the dF/dt sweep across the data window is small (from a fraction of an FFT bin to a couple bins), how can one estimate the sweep parameter (but, beyond answer offered to this question, assuming this is an estimation of a detected signal in noise.)
One offered solution seems to be to segment the FFT frame into several shorter subframes, do shorter STFTs, and look for a linear best fit among the resulting set of subframe FFT peak magnitude frequency estimates (which all have poorer frequency resolution due to the shorter subframes). Are there any other or better options for detection and estimation?
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