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DSP Blogs > Rick Lyons > Spectral Flipping Around Signal Center Frequency

Rick Lyons
Richard (Rick) Lyons is a consulting Systems Engineer and lecturer with Besser Associates in Mountain View, California. He is the author of "Understanding Digital Signal Processing 2/E" (Prentice-Hall, 2004), and Editor of, and contributor to, "Streamlining Digital Signal Processing, A Tricks of the Trade Guidebook" (IEEE Press/Wiley, 2007). He is also an Associate Editor for the IEEE Signal Processing Magazine.

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Spectral Flipping Around Signal Center Frequency

Posted by Rick Lyons on Nov 7 2007 under Tips and Tricks | Multirate DSP   

Most of us are familiar with the process of flipping the spectrum (spectral inversion) of a real signal by multiplying that signal's time samples by (-1)n. In that process the center of spectral rotation is fs/4, where fs is the signal's sample rate in Hz. In this blog we discuss a different kind of spectral flipping process.

Consider the situation where we need to flip the X(f) spectrum in Figure 1(a) to obtain the desired Y(f) spectrum shown in Figure 1(b). Notice that the center of rotation of the desired spectral flipping is not fs /4, but is instead the signal's fcntr center frequency. The simple spectral flipping process of multiplying a signal's time samples by (-1)n does not solve our problem because that process would result in the undesirable spectrum shown in Figure 1(c).

Spectral Flipping

 

Figure 1: Spectral flipping, centered at fcntr: (a) original spectrum; (b) desired spectrum; (c) incorrect spectrum.

There are two methods to solve our fcntr-centered spectral flipping problem. Figure 2(a) shows the first method, comprising a multirate processing technique. In considering this spectral flipping method, we should keep in mind that:

* The two identical lowpass filters have passbands that extends from zero Hz to fH Hz. (Note that the sample rate for both filters is 2fs Hz.)

* The cosine mixing sequence uses the upsampled-by-two time index variable n'.

* The multiply by four operation compensates for the sequence u(n') amplitude loss by a factor of two caused by interpolation, and the amplitude loss by another factor of two due to the cosine mixing.

Of course, a clever engineer will eliminate the multiply by four operation altogether by increasing the DC (zero Hz) gain of one of the lowpass filters by four.

The second method we could use to obtain a signal having the desired Figure 1(b) spectrum is the neat process shown in Figure 2(b), suggested by Dirk Bell [1]. While somewhat more computationally intensive than the above multirate method, this technique works well and deserves mention here. In this second method, as Bell recommends, we can combine the last two stages of the process (the complex multiply and the Real Part extraction) by computing only the real part of sequence v(n) yielding our desired y(n).

Spectral Flipping Techniques

Figure 2: Spectral flipping techniques: (a) first method; (b) second method.

 

[1] Bell, D. "Subject: Re: Frequency Inversion", Usenet group comp.dsp post, Aug. 30, 2006.

 

Copyright © 2007, Richard Lyons, All Rights Reserved



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posted by Rick Lyons
Richard (Rick) Lyons is a consulting Systems Engineer and lecturer with Besser Associates in Mountain View, California. He is the author of "Understanding Digital Signal Processing 2/E" (Prentice-Hall, 2004), and Editor of, and contributor to, "Streamlining Digital Signal Processing, A Tricks of the Trade Guidebook" (IEEE Press/Wiley, 2007). He is also an Associate Editor for the IEEE Signal Processing Magazine.

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Comments


 

SteveSmith wrote:

11/25/2007
 
Hi Rick,
Interesting technique. I saw this done with analog circuits about 25 years ago for police radio communications. Someone had the idea that if you flipped the spectrum of the voice (exchanging the high and low frequencies) that eavesdroppers would not be able to understand it. Didn’t work very well– people could actually learn to understand the inverted sound! Thanks for the article.
 

johnnyyy-be-good wrote:

12/27/2007
 
thnx rick this is great

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