Correcting large variable dc bias in signal FFT I am somewhat new to signal processing, but i'm hoping I can provide enough information in order to be pointed in the right direction.

I am working on analyzing the frequency spectrum of audio signal impulse response.  A few of the impulses seem to have what looks like a large variable dc bias, and when performing a FFT they come back with very large DC values.

subtracting the mean did not help much in ways of correction.  I think there may be other issues besides what appears to be DC but I am stuck.  

The graphs below are plots of the FFT results from two signals - one with the warped dc bias, and one without. Hopefully this demonstrates better what may be happening to cause this.  Any help is greatly appreciated.

both Signals are of the same sample length and FFT size

1st Image - FFT of good Signal, small-no DC value



2nd Image - FFT of problem Signal Large DC value
Based on the plots shown in the OP, it doesn't appear that the signal you've noted as "bad" just has a DC bias. If there was a DC bias, then it would be expressed graphically as a bulk shift by some amount in the complex plane. Compared to the "good" example, it appears that the "bad" one has some time-varying amplitude modulation, which, when viewed as applied to a phasor in the complex plane, could trace out the loopy patterns shown in the plot.

This supports your claim that you tried just subtracting the mean of the signal and saw little improvement; while there does appear to be a nonzero DC value in the "bad" example, the differences aren't isolated to just the mean value, as I said above. The apparent amplitude modulation will add spectral content over some swath of bandwidth of the signal, which could overlap with the region that you want to analyze.