Adaptive Filter | ADPCM | ADSP | ADSP-2181 | Aliasing | AMR | Anti-Aliasing | ARMA | Autocorrelation | AutoCovariance | Beamforming | Bessel | Blackfin | Butterworth | C6713 | CCS | Chebyshev | CIC Filter | Circular Convolution | Code Composer Studio | Comb Filter | Compression | Convolution | Cross Correlation | DCT | Decimation | Deconvolution | Demodulation | DM642 | DSP Boards | DSP/BIOS | DTMF | Echo Cancellation | Equalization | Equalizer | ETSI | EZLITE (Ez-kit Lite) | FFT | FFTW | FIR Filter | Fixed Point | FSK | G.711 | G.723 | G.729 | Gaussian Noise | Goertzel | GPIO | Hilbert Transform | IFFT | IIR Filter | Interpolation | Invariance | JTAG | Kalman | Laplace Transform | Levinson | LPC | McBSP | MIPS | Modulation | MPEG | Multirate | Notch Filter | Nyquist | OFDM | Oversampling | Pink Noise | Pitch | PLL | Polyphase | QAM | QDMA | Quantization | Quantizer | Radar | Random Noise | Reed Solomon | Remez | Resampling | RTDX | Sampling | Sharc | TI C6711 | Undersampling | Viterbi | Wavelets | White Noise | Wiener Filter | Windowing | XDS510PP | Z Transform

Hello 

   It is Required to continuously monitor, the received signal from a
sensor and detect the presence of the pulse. The amplitude of the
pulse remains constant. After A/D conversion, we were trying to pass
the discrete time signal through a Long Time Analysis(LTA) Filter and
Short Time Analysis(STA) Filter and compare their outputs to detect
the pulse (start and end points of the pulse). It is required to know
these points as precisely as possible. The SNR of the signal is 5 dB.

I am unable to decide on the filter - type,order, time constant.

Please comment,tell me if there is a fallacy in the above method. 

Suggest any references to LTA and STA filter design and selection.

Is it more advantageous to do the above process in analog domain?

I will be grateful to know about any other better ways of solving this
problem(references).


Thanks in advance.
Parthasaraty

______________________________
New DSP Code Snippets Section now Live.   Learn more about the reward program for contributors here.

"Parthasarathy" <p...@yahoo.co.in> wrote in message
news:7...@posting.google.com...
> Hello
>
>    It is Required to continuously monitor, the received signal from a
> sensor and detect the presence of the pulse. The amplitude of the
> pulse remains constant. After A/D conversion, we were trying to pass
> the discrete time signal through a Long Time Analysis(LTA) Filter and
> Short Time Analysis(STA) Filter and compare their outputs to detect
> the pulse (start and end points of the pulse). It is required to know
> these points as precisely as possible. The SNR of the signal is 5 dB.

Why is a proposed method being mixed up with the objective here?

How can the SNR always be 5dB? - that doesn't sound very real.

What does "the pulse" look like?
What does the noise look like?

Fred

______________________________
New DSP Code Snippets Section now Live.   Learn more about the reward program for contributors here.

Fred Marshall wrote:

> "Parthasarathy" <p...@yahoo.co.in> wrote in message
> news:7...@posting.google.com...
> 
>>Hello
>>
>>   It is Required to continuously monitor, the received signal from a
>>sensor and detect the presence of the pulse. The amplitude of the
>>pulse remains constant. After A/D conversion, we were trying to pass
>>the discrete time signal through a Long Time Analysis(LTA) Filter and
>>Short Time Analysis(STA) Filter and compare their outputs to detect
>>the pulse (start and end points of the pulse). It is required to know
>>these points as precisely as possible. The SNR of the signal is 5 dB.
> 
> 
> Why is a proposed method being mixed up with the objective here?
> 
> How can the SNR always be 5dB? - that doesn't sound very real.

Problems out of a book are often idealized to hammer on a particular
point.

   ...

Jerry
-- 
Engineering is the art of making what you want from things you can get.
¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯

______________________________
New DSP Code Snippets Section now Live.   Learn more about the reward program for contributors here.

"Jerry Avins" <j...@ieee.org> wrote in message
news:412f5e4e$0$19713$6...@news.rcn.com...
>
> Problems out of a book are often idealized to hammer on a particular
> point.


Book?  What book?  .....

______________________________
New DSP Code Snippets Section now Live.   Learn more about the reward program for contributors here.

Fred Marshall wrote:

> "Jerry Avins" <j...@ieee.org> wrote in message
> news:412f5e4e$0$19713$6...@news.rcn.com...
> 
>>Problems out of a book are often idealized to hammer on a particular
>>point.
> 
> 
> 
> Book?  What book?  .....

I assumed a text. Given the season. self study, rather than homework.

Jerry
-- 
Engineering is the art of making what you want from things you can get.
¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯

______________________________
New DSP Code Snippets Section now Live.   Learn more about the reward program for contributors here.

Sounds like a DC shift in stationary white Gaussian noise.  I think for a long 
term integrator and a short term integrator, the F-Ratio test is appropriate 
with the number of degrees of freedom equal to the the number of samples in 
the filters.  A sliding boxcar filter would be nice from an analysis 
perspective.  There is a book on this subject but I'm drawing a blank on the 
title.

The random telegraph signal from Papoulous (?) might be the source of the 
problem.

In article <412f77f9$0$19708$6...@news.rcn.com>, Jerry Avins 
<j...@ieee.org> wrote:
>Fred Marshall wrote:
>
>> "Jerry Avins" <j...@ieee.org> wrote in message
>> news:412f5e4e$0$19713$6...@news.rcn.com...
>> 
>>>Problems out of a book are often idealized to hammer on a particular
>>>point.
>> 
>> 
>> 
>> Book?  What book?  .....
>
>I assumed a text. Given the season. self study, rather than homework.
>
>Jerry

______________________________
New DSP Code Snippets Section now Live.   Learn more about the reward program for contributors here.

g...@whitehouse.com (George Bush) wrote in message
news:<SBPXc.18184$Q...@twister.socal.rr.com>...
> Sounds like a DC shift in stationary white Gaussian noise.  I think for a long 
> term integrator and a short term integrator, the F-Ratio test is appropriate 
> with the number of degrees of freedom equal to the the number of samples in 
> the filters.  A sliding boxcar filter would be nice from an analysis 
> perspective.  There is a book on this subject but I'm drawing a blank on the 
> title.
> 
> The random telegraph signal from Papoulous (?) might be the source of the 
> problem.
> 
> In article <412f77f9$0$19708$6...@news.rcn.com>, Jerry Avins 
> <j...@ieee.org> wrote:
> >Fred Marshall wrote:
> >
> >> "Jerry Avins" <j...@ieee.org> wrote in message
> >> news:412f5e4e$0$19713$6...@news.rcn.com...
> >> 
> >>>Problems out of a book are often idealized to hammer on a particular
> >>>point.
> >> 
> >> 
> >> 
> >> Book?  What book?  .....
> >
> >I assumed a text. Given the season. self study, rather than homework.
> >
> >Jerry

As an alternative to the sliding boxcar, consider using a "leaky
integrator" to establish the background noise level:

y[n] = (1-alpha)*x[n] + alpha*y[n-1], 0 < alpha < 1

John

______________________________
New DSP Code Snippets Section now Live.   Learn more about the reward program for contributors here.

On Fri, 27 Aug 2004 12:16:14 -0400, Jerry Avins <j...@ieee.org> wrote:

>Fred Marshall wrote:
>
>> "Parthasarathy" <p...@yahoo.co.in> wrote in message
>> news:7...@posting.google.com...
>> 
>>>Hello
>>>
>>>   It is Required to continuously monitor, the received signal from a
>>>sensor and detect the presence of the pulse. The amplitude of the
>>>pulse remains constant. After A/D conversion, we were trying to pass
>>>the discrete time signal through a Long Time Analysis(LTA) Filter and
>>>Short Time Analysis(STA) Filter and compare their outputs to detect
>>>the pulse (start and end points of the pulse). It is required to know
>>>these points as precisely as possible. The SNR of the signal is 5 dB.
>> 
>> 
>> Why is a proposed method being mixed up with the objective here?
>> 
>> How can the SNR always be 5dB? - that doesn't sound very real.
>
>Problems out of a book are often idealized to hammer on a particular
>point.
>

Hi Jerry,

  This sounded much like a homework problem 
to me too.  I suggest Parthasaraty look into 
"matched filters".

[-Rick-]
 

______________________________
New DSP Code Snippets Section now Live.   Learn more about the reward program for contributors here.

Hello 

> 
> Why is a proposed method being mixed up with the objective here?
  
  What are you trying to convey? 
 
 
> How can the SNR always be 5dB? - that doesn't sound very real.
 
  I intended to say that, the SNR is >= 5dB.  
 
> What does "the pulse" look like?
  
  The Pulse is a chirp signal.  

> What does the noise look like?
  
  I am not sure, how it looks like, I have assumed to be gaussian.

Also, please tell about the various signal detection methods

Thanks in advance
Parthasarathy

______________________________
New DSP Code Snippets Section now Live.   Learn more about the reward program for contributors here.

"Parthasarathy" <p...@yahoo.co.in> wrote in message
news:7...@posting.google.com...
> Hello
>
> >
> > Why is a proposed method being mixed up with the objective here?
>
>   What are you trying to convey?
>
>
> > How can the SNR always be 5dB? - that doesn't sound very real.
>
>   I intended to say that, the SNR is >= 5dB.
>
> > What does "the pulse" look like?
>
>   The Pulse is a chirp signal.
>
> > What does the noise look like?
>
>   I am not sure, how it looks like, I have assumed to be gaussian.
>
> Also, please tell about the various signal detection methods
>
> Thanks in advance
> Parthasarathy


> > Why is a proposed method being mixed up with the objective here?
>
>   What are you trying to convey?

You said:
"we were trying to pass
the discrete time signal through a Long Time Analysis(LTA) Filter and
Short Time Analysis(STA) Filter and compare their outputs to detect
the pulse (start and end points of the pulse)"

and, that is a "method".  So, I was asking why the proposed method was part
of the statement of the objective.  That's all.  Maybe you have a constraint
that requires this approach / half developed, etc.

You might consider a matched filter - one that's matched to the chirp.  In
the time domain, this would amount to correlating the chirp with the input
signal - multiply and add/integrate the products.  This could be done at
each sample interval but perhaps doesn't need to be that frequent.  You
would be looking for a peak in this result.

In the frequency domain you would first zero-pad the chirp and FFT, keeping
this as a reference.
Then, you would take longer segments of the signal (equal to the length of
the padded chirp) and FFT them - perhaps overlapped.
Then you would multiply the filter by the signal in the frequency domain and
IFFT the result.
You would be looking for a peak in this result.

This process would identify the presence of the pulse in noise but might not
be so good for finding the edges of the pulse.  You might use it to find the
center of the pulse and measure using some other technique around the center
looking for the edges.  Maybe that's where long and short term "analysis"
comes in.

The problem with finding the edges is that it implies a much higher
bandwidth.  So, the matched filter isn't going to be optimum for that
purpose.  If you know the frequencies of the chirp, maybe you can match
filter over a shorter time period at the leading and trailing edge
frequencies - at quite a loss in processing gain.

Fred

Fred

______________________________
New DSP Code Snippets Section now Live.   Learn more about the reward program for contributors here.