dear ikaro,
              why dont you go for cylcostatinarity properties. i dont
know whether chirp signals qualify for such prorperties, for that do
refer william gardner's book on cyclostationarity. if chirp signals
come under cyclostatinarity signals, then frequency shift evaulation is
easy, never mind even under worse SNR Conditions as mentioned in one of
the letters.

anyway, by next post i will come up with some answer for your problem

regards
particle (filter) reddy

Ikaro wrote:

> In his original post he never mentions noise (if fact he seems to be
> doing  noise free simulations).
> Offcourse a word of caution to real-world scenarios are always welcome,
> but I don't see the point of adding arbitrary difficulty to the problem
> and trying to implement sophisticated solutions when a simple one might
>  work...

My dear Ikaro,

In the worlds of the spherical horses in the vacuum, the frequency is 
measured with the frequency counter. Just measure the zero crossing 
rate, what's the problem.


> 
> 
> Afterall, this might be a simple exercise for a course....
> 

The whole point of the exercise is that for the linear chirp the small 
Doppler shift is indistinguishable from the time shift...




VLV

In his original post he never mentions noise (if fact he seems to be
doing  noise free simulations).

Offcourse a word of caution to real-world scenarios are always welcome,
but I don't see the point of adding arbitrary difficulty to the problem
and trying to implement sophisticated solutions when a simple one might
 work...


Afterall, this might be a simple exercise for a course....

Fox wrote:
> Hello,
> I have a question for you. I have to simulate the
> signal received in a radar system by applying a time delay and a
> doppler shift. By now I have delayed the original signal and I have
> estimated the delay by correlating the original transmitted signal
> with the received one and by picking the max. Now I have to estimate
> the shift in frequency but I don't know how to proceed. I think I
> should multiply the delayed signal for exp(-j*2pi*fd*t) but how can I
> estimate the shift? The transmitted signal is a chirp, duration of 100
> microsec sampled at 0.5 MHz (50 samples)
> Thanks in advance!

> 1) High SNR so you can actually find the edges.

Correct. But with really low SNRs I doubt any technique will stand-out
unless we can exploit/assume properties on the type of noise.

Thus we might estimate the noise PSD in silents interval (asssuming
WN), and consider any edges by simple thresholding based on the average
noise power at silent intervals. Seems like a common detection problem
(at least if the noise is white, or some of it's properties are known).



> 2) High bandwidth so you can actually find the edges in time accurately
> enough.


Agreed, but that's the typical trade-off between time vs frequency
resolution....
That why I suggested that the chirp's bandwidth bemuch smaller compared

to the channel's bandwidth (ie, the sampling frequency much higher than

say, 5*nyquist).
By selecting an appropiately high sampling frequency *and* *keeping the

desired time resolution constant  we approximately achieve the desired
spectral resolution (at the cost of more samples per second and cpu
time offcourse)


> 3) Long time processing so you can actually find the edges in time
> accurately enough. 


I think you meant "edges in frequency" here...

> 1) High SNR so you can actually find the edges.

Correct, you can also estimate the noise power in a silent interval
(asssuming WN), and consider any edges by simple thresholding. Seems
like a common detection problem (at least if the noise is white, or
some of it's properties are known).

> 2) High bandwidth so you can actually find the edges in time accurately
> enough.

Agreed, but that's the typical trade-off between time vs frequency
resolution....
That why I suggested that the chirp's bandwidth bemuch smaller compared
to the channel's bandwidth (ie, the sampling frequency much higher than
say, 5*nyquist).
By selecting an appropiately high sampling frequency *and* *keeping the
desired time resolution constant  we approximately achieve the desired
spectral resolution (at the cost of more samples per second and cpu
time offcourse)

> 3) Long time processing so you can actually find the edges in time
> accurately enough.
I think you meant "edges in frequency" here...

Yes,  but I don't see how this answers the question...since in my post
the frequency shift can also apply to the powe spectral density.


> We are talking about the radars here. The SNR at the input may be as low
> as -20dB or less. Therefore you can't say anything about the signal
> until you compute the correlation.
>

"Ikaro" <ikarosilva@hotmail.com> wrote in message 
news:1158165965.508867.289920@m73g2000cwd.googlegroups.com...
> Sorry if my question might sound naive ...
>
> If your chirp starts at Fo and Fn, and your measured signal starts at
> F1 and ends at Fm
> can't you take the spectral shift as the average difference between
> these two frequencies (ie, the edge frequencies)?
>
>
> Fshift= 0.5*(F1-Fo + Fm-Fn);
>
>
> That is offcourse assuming that the chirp is fairly bandlimited
> compared to your recording bandwidth, and the the chirp has constant
> amplitude....
>

"compared to your recording bandwidth" is a key point.
To do what you suggest requires a couple of things:

1) High SNR so you can actually find the edges.

2) High bandwidth so you can actually find the edges in time accurately 
enough.

3) Long time processing so you can actually find the edges in time 
accurately enough.

So, yes, with infinite signal to noise ratio in a laboratory environment as 
with Matlab you could likely come up with processing that would do it.  But, 
in the real world where SNR is often not ideal then the processing you 
choose will probably not have the properties needed.

See "ambiguity function"  It's called that for a reason.  :-)

Fred 

I agree with Vladimir.  The signal's ambiguity function and the
Cramer-Rao Bound can be computed for the SNR's of interest to convince
yourself that the estimation of doppler shift from a single return is
difficult at best.  Estimation of doppler is usually performed using
multiple coherent returns in a radar system.

Mike




Vladimir Vassilevsky wrote:
> Ikaro wrote:
>
> > Sorry if my question might sound naive ...
> >
> > If your chirp starts at Fo and Fn, and your measured signal starts at
> > F1 and ends at Fm
> > can't you take the spectral shift as the average difference between
> > these two frequencies (ie, the edge frequencies)?
> >
> >
> > Fshift= 0.5*(F1-Fo + Fm-Fn);
> >
> >
> > That is offcourse assuming that the chirp is fairly bandlimited
> > compared to your recording bandwidth, and the the chirp has constant
> > amplitude....
>
> We are talking about the radars here. The SNR at the input may be as low
> as -20dB or less. Therefore you can't say anything about the signal
> until you compute the correlation.
>
> Vladimir Vassilevsky
> 
> DSP and Mixed Signal Design Consultant
> 
> http://www.abvolt.com

Ikaro wrote:

> Sorry if my question might sound naive ...
> 
> If your chirp starts at Fo and Fn, and your measured signal starts at
> F1 and ends at Fm
> can't you take the spectral shift as the average difference between
> these two frequencies (ie, the edge frequencies)?
> 
> 
> Fshift= 0.5*(F1-Fo + Fm-Fn);
> 
> 
> That is offcourse assuming that the chirp is fairly bandlimited
> compared to your recording bandwidth, and the the chirp has constant
> amplitude....

We are talking about the radars here. The SNR at the input may be as low 
as -20dB or less. Therefore you can't say anything about the signal 
until you compute the correlation.

Vladimir Vassilevsky

DSP and Mixed Signal Design Consultant

http://www.abvolt.com

Sorry if my question might sound naive ...

If your chirp starts at Fo and Fn, and your measured signal starts at
F1 and ends at Fm
can't you take the spectral shift as the average difference between
these two frequencies (ie, the edge frequencies)?


Fshift= 0.5*(F1-Fo + Fm-Fn);


That is offcourse assuming that the chirp is fairly bandlimited
compared to your recording bandwidth, and the the chirp has constant
amplitude....


> Fox wrote:
> > Hello,
> > I have a question for you. I have to simulate the
> > signal received in a radar system by applying a time delay and a
> > doppler shift. By now I have delayed the original signal and I have
> > estimated the delay by correlating the original transmitted signal
> > with the received one and by picking the max. Now I have to estimate
> > the shift in frequency but I don't know how to proceed. I think I
> > should multiply the delayed signal for exp(-j*2pi*fd*t) but how can I
> > estimate the shift? The transmitted signal is a chirp, duration of 100
> > microsec sampled at 0.5 MHz (50 samples)
> > Thanks in advance!