Reply by Fred Marshall●December 15, 20082008-12-15
Tom wrote:
> Usually a mismatched filter will be optimal for some criteria.
> A matched filter maximizes SNR assuming a linear system with
> independent gaussian noise, but a mismatched filter might be preferred
> that is, for example, more robust to non-gaussian noise, more robust
> to signal distortions - e.g. the response should be of a certain
> nature when the received signal does not equal the reference matched
> signal - sidelobe reduction in radar range processing is one example
> of this. FFT windowing is another.
Just to be picky about it... I think one needs to say
"the response would be of a certain nature *even* when the received signal
*does* equal the reference matched signal"
The trap is using a matched filter as the point of reference at all.
Fred
Reply by Tom●December 12, 20082008-12-12
On Dec 11, 9:47�am, mikess...@optusnet.com.au wrote:
> On Dec 10, 9:38�am, "Fred Marshall" <fmarshallx@remove_the_x.acm.org>
> wrote:
>
>
>
> > Tim Wescott wrote:
> > > Fred Marshall wrote:
> > >> Mike J Smith wrote:
> > >>> Hi
>
> > >>> I'm new to DSP. I'm working on an ultrasonic project which involves
> > >>> measuring the time of flight of a 40khz pulse between 2
> > >>> transducers. I think I understand how to use cross correlation to
> > >>> slide a stored version of the pulse shape across the received
> > >>> signal until a match is found. This seems to be called matched
> > >>> filtering. I have seen references to a technique called mismatched
> > >>> filtering,
> > >>> particularly in radar applications, but despite lots of Googling I
> > >>> haven't been able to find anything which explains the concept it in
> > >>> a non-mathematical way that I understand. I don't have access to a
> > >>> technical library.
>
> > >>> Can anybody help?
>
> > >>> Thanks
>
> > >>> Mike
>
> > >> It occurs to me that "mismatched" filtering is simply filtering that
> > >> isn't "matched".
>
> > >> Matched filtering can be accomplished by convolving the received
> > >> signal with a replica of the transmit signal - and using
> > >> frequency-shifted replicas to deal with Doppler, etc. �The objective
> > >> is to get the best noise gain against white noise in a least-squares
> > >> sense. So, if the reference signal for the convolution isn't exactly a
> > >> replica then the filter might be said to be "not matched" or
> > >> "mismatched". For example, a radar might simply use a passband filter
> > >> that just
> > >> filters away noise that's outside the entire band of interest -
> > >> including Doppler. It's not optimum re: noise gain but it may work
> > >> just fine. �It's not "matched". �But, it a heck of a lot easier to
> > >> implement. Fred
>
> > > That sounds too easy -- but maybe that's it.
>
> > > Or it's a filter that minimizes some error metric in a more robust way
> > > than a matched filter would in the presence of colored noise or
> > > distortion or such.
>
> > > Dunno -- maybe we should have a contest to see what the most
> > > outrageous description we can hang onto the the name "mismatched
> > > filter".
>
> > First Google hit:
>
> >http://home.earthlink.net/~loganscott53/temporal.htm
>
> > Seems many hits are about sidelobe suppression in the filter output. �OK.
> > Probably not what I would have called it..
>
> > Fred- Hide quoted text -
>
> > - Show quoted text -
>
> Thanks to everyone for their input.
>
> Having done some more reading, it's beginning to seem to me that
> "mismatched filter" just means "not a matched filter"?
>
> Seems a bit like calling everything which isn't an elephant a
> "mismatched elephant"!!
>
> Thanks again.
>
> Regards
>
> Mike
Usually a mismatched filter will be optimal for some criteria.
A matched filter maximizes SNR assuming a linear system with
independent gaussian noise, but a mismatched filter might be preferred
that is, for example, more robust to non-gaussian noise, more robust
to signal distortions - e.g. the response should be of a certain
nature when the received signal does not equal the reference matched
signal - sidelobe reduction in radar range processing is one example
of this. FFT windowing is another.
-T
Reply by Fred Marshall●December 11, 20082008-12-11
mikesspam@optusnet.com.au wrote:
> On Dec 10, 9:38 am, "Fred Marshall" <fmarshallx@remove_the_x.acm.org>
> wrote:
>> Tim Wescott wrote:
>>> Fred Marshall wrote:
>>>> Mike J Smith wrote:
>>>>> Hi
>>
>>>>> I'm new to DSP. I'm working on an ultrasonic project which
>>>>> involves measuring the time of flight of a 40khz pulse between 2
>>>>> transducers. I think I understand how to use cross correlation to
>>>>> slide a stored version of the pulse shape across the received
>>>>> signal until a match is found. This seems to be called matched
>>>>> filtering. I have seen references to a technique called mismatched
>>>>> filtering,
>>>>> particularly in radar applications, but despite lots of Googling I
>>>>> haven't been able to find anything which explains the concept it
>>>>> in a non-mathematical way that I understand. I don't have access
>>>>> to a technical library.
>>
>>>>> Can anybody help?
>>
>>>>> Thanks
>>
>>>>> Mike
>>
>>>> It occurs to me that "mismatched" filtering is simply filtering
>>>> that isn't "matched".
>>
>>>> Matched filtering can be accomplished by convolving the received
>>>> signal with a replica of the transmit signal - and using
>>>> frequency-shifted replicas to deal with Doppler, etc. The objective
>>>> is to get the best noise gain against white noise in a
>>>> least-squares sense. So, if the reference signal for the
>>>> convolution isn't exactly a replica then the filter might be said
>>>> to be "not matched" or "mismatched". For example, a radar might
>>>> simply use a passband filter that just
>>>> filters away noise that's outside the entire band of interest -
>>>> including Doppler. It's not optimum re: noise gain but it may work
>>>> just fine. It's not "matched". But, it a heck of a lot easier to
>>>> implement. Fred
>>
>>> That sounds too easy -- but maybe that's it.
>>
>>> Or it's a filter that minimizes some error metric in a more robust
>>> way than a matched filter would in the presence of colored noise or
>>> distortion or such.
>>
>>> Dunno -- maybe we should have a contest to see what the most
>>> outrageous description we can hang onto the the name "mismatched
>>> filter".
>>
>> First Google hit:
>>
>> http://home.earthlink.net/~loganscott53/temporal.htm
>>
>> Seems many hits are about sidelobe suppression in the filter output.
>> OK. Probably not what I would have called it..
>>
>> Fred- Hide quoted text -
>>
>> - Show quoted text -
>
> Thanks to everyone for their input.
>
> Having done some more reading, it's beginning to seem to me that
> "mismatched filter" just means "not a matched filter"?
>
> Seems a bit like calling everything which isn't an elephant a
> "mismatched elephant"!!
>
Well, that was the essence of my first post. But on Googling it seemed to
mean something else to some. I didn't "dig" further.
We surely agree. I like the elephant analogy. In this case it's like
calling a tiger a non-elephant as you say. There must be better ways to
refer to a tiger!
But, to be fair, if one is totally focused on matched filters as the holy
grail of receiver technology then I guess one might be motivated to say:
"Hey! I found a "nonmatched" filter that does some good things!!"
It suggests a rather narrow view doesn't it?
A broader view might refer to a "good" filter according to its goodness
measure. "least squares", "minimax/Chebyshev/equiripple", are examples of
goodness measures we're all familiar with in a slightly different context.
At least they are descriptive. If I were totally absorbed with FIR design
using the Parks-McClellan program (which I often am) then I might call a
slightly different approach "non-FIR" or "non-equiripple" because that's my
point of departure. It wouldn't really help someone else understand that
I'm leading up to a different measure for goodness.
Fred
Reply by ●December 10, 20082008-12-10
On Dec 10, 9:38�am, "Fred Marshall" <fmarshallx@remove_the_x.acm.org>
wrote:
> Tim Wescott wrote:
> > Fred Marshall wrote:
> >> Mike J Smith wrote:
> >>> Hi
>
> >>> I'm new to DSP. I'm working on an ultrasonic project which involves
> >>> measuring the time of flight of a 40khz pulse between 2
> >>> transducers. I think I understand how to use cross correlation to
> >>> slide a stored version of the pulse shape across the received
> >>> signal until a match is found. This seems to be called matched
> >>> filtering. I have seen references to a technique called mismatched
> >>> filtering,
> >>> particularly in radar applications, but despite lots of Googling I
> >>> haven't been able to find anything which explains the concept it in
> >>> a non-mathematical way that I understand. I don't have access to a
> >>> technical library.
>
> >>> Can anybody help?
>
> >>> Thanks
>
> >>> Mike
>
> >> It occurs to me that "mismatched" filtering is simply filtering that
> >> isn't "matched".
>
> >> Matched filtering can be accomplished by convolving the received
> >> signal with a replica of the transmit signal - and using
> >> frequency-shifted replicas to deal with Doppler, etc. �The objective
> >> is to get the best noise gain against white noise in a least-squares
> >> sense. So, if the reference signal for the convolution isn't exactly a
> >> replica then the filter might be said to be "not matched" or
> >> "mismatched". For example, a radar might simply use a passband filter
> >> that just
> >> filters away noise that's outside the entire band of interest -
> >> including Doppler. It's not optimum re: noise gain but it may work
> >> just fine. �It's not "matched". �But, it a heck of a lot easier to
> >> implement. Fred
>
> > That sounds too easy -- but maybe that's it.
>
> > Or it's a filter that minimizes some error metric in a more robust way
> > than a matched filter would in the presence of colored noise or
> > distortion or such.
>
> > Dunno -- maybe we should have a contest to see what the most
> > outrageous description we can hang onto the the name "mismatched
> > filter".
>
> First Google hit:
>
> http://home.earthlink.net/~loganscott53/temporal.htm
>
> Seems many hits are about sidelobe suppression in the filter output. �OK.
> Probably not what I would have called it..
>
> Fred- Hide quoted text -
>
> - Show quoted text -
Thanks to everyone for their input.
Having done some more reading, it's beginning to seem to me that
"mismatched filter" just means "not a matched filter"?
Seems a bit like calling everything which isn't an elephant a
"mismatched elephant"!!
Thanks again.
Regards
Mike
Reply by Fred Marshall●December 9, 20082008-12-09
Tim Wescott wrote:
> Fred Marshall wrote:
>> Mike J Smith wrote:
>>> Hi
>>>
>>> I'm new to DSP. I'm working on an ultrasonic project which involves
>>> measuring the time of flight of a 40khz pulse between 2
>>> transducers. I think I understand how to use cross correlation to
>>> slide a stored version of the pulse shape across the received
>>> signal until a match is found. This seems to be called matched
>>> filtering. I have seen references to a technique called mismatched
>>> filtering,
>>> particularly in radar applications, but despite lots of Googling I
>>> haven't been able to find anything which explains the concept it in
>>> a non-mathematical way that I understand. I don't have access to a
>>> technical library.
>>>
>>> Can anybody help?
>>>
>>> Thanks
>>>
>>> Mike
>>
>> It occurs to me that "mismatched" filtering is simply filtering that
>> isn't "matched".
>>
>> Matched filtering can be accomplished by convolving the received
>> signal with a replica of the transmit signal - and using
>> frequency-shifted replicas to deal with Doppler, etc. The objective
>> is to get the best noise gain against white noise in a least-squares
>> sense. So, if the reference signal for the convolution isn't exactly a
>> replica then the filter might be said to be "not matched" or
>> "mismatched". For example, a radar might simply use a passband filter
>> that just
>> filters away noise that's outside the entire band of interest -
>> including Doppler. It's not optimum re: noise gain but it may work
>> just fine. It's not "matched". But, it a heck of a lot easier to
>> implement. Fred
>>
>>
> That sounds too easy -- but maybe that's it.
>
> Or it's a filter that minimizes some error metric in a more robust way
> than a matched filter would in the presence of colored noise or
> distortion or such.
>
> Dunno -- maybe we should have a contest to see what the most
> outrageous description we can hang onto the the name "mismatched
> filter".
> Mike J Smith wrote:
>> Hi
>>
>> I'm new to DSP. I'm working on an ultrasonic project which involves
>> measuring the time of flight of a 40khz pulse between 2 transducers. I
>> think I understand how to use cross correlation to slide a stored
>> version of the pulse shape across the received signal until a match
>> is found. This seems to be called matched filtering.
>>
>> I have seen references to a technique called mismatched filtering,
>> particularly in radar applications, but despite lots of Googling I
>> haven't been able to find anything which explains the concept it in a
>> non-mathematical way that I understand. I don't have access to a
>> technical library.
>>
>> Can anybody help?
>>
>> Thanks
>>
>> Mike
>
> It occurs to me that "mismatched" filtering is simply filtering that isn't
> "matched".
>
> Matched filtering can be accomplished by convolving the received signal with
> a replica of the transmit signal - and using frequency-shifted replicas to
> deal with Doppler, etc. The objective is to get the best noise gain against
> white noise in a least-squares sense.
>
> So, if the reference signal for the convolution isn't exactly a replica then
> the filter might be said to be "not matched" or "mismatched".
>
> For example, a radar might simply use a passband filter that just filters
> away noise that's outside the entire band of interest - including Doppler.
> It's not optimum re: noise gain but it may work just fine. It's not
> "matched". But, it a heck of a lot easier to implement.
>
> Fred
>
>
That sounds too easy -- but maybe that's it.
Or it's a filter that minimizes some error metric in a more robust way
than a matched filter would in the presence of colored noise or
distortion or such.
Dunno -- maybe we should have a contest to see what the most outrageous
description we can hang onto the the name "mismatched filter".
--
Tim Wescott
Wescott Design Services
http://www.wescottdesign.com
Do you need to implement control loops in software?
"Applied Control Theory for Embedded Systems" gives you just what it says.
See details at http://www.wescottdesign.com/actfes/actfes.html
> Mike J Smith wrote:
>> Hi
>>
>> I'm new to DSP. I'm working on an ultrasonic project which involves
>> measuring the time of flight of a 40khz pulse between 2 transducers. I
>> think I understand how to use cross correlation to slide a stored
>> version of the pulse shape across the received signal until a match
>> is found. This seems to be called matched filtering.
>>
>> I have seen references to a technique called mismatched filtering,
>> particularly in radar applications, but despite lots of Googling I
>> haven't been able to find anything which explains the concept it in a
>> non-mathematical way that I understand. I don't have access to a
>> technical library.
>>
>> Can anybody help?
>>
>> Thanks
>>
>> Mike
>
> It occurs to me that "mismatched" filtering is simply filtering that isn't
> "matched".
>
> Matched filtering can be accomplished by convolving the received signal with
> a replica of the transmit signal - and using frequency-shifted replicas to
> deal with Doppler, etc. The objective is to get the best noise gain against
> white noise in a least-squares sense.
>
> So, if the reference signal for the convolution isn't exactly a replica then
> the filter might be said to be "not matched" or "mismatched".
>
> For example, a radar might simply use a passband filter that just filters
> away noise that's outside the entire band of interest - including Doppler.
> It's not optimum re: noise gain but it may work just fine. It's not
> "matched". But, it a heck of a lot easier to implement.
That sounds plausible. I was thinking that maybe it means a filter
that was matched against a distorted form of the transmit waveform,
assuming the distortion it undergoes in propagating from the tx to
rx.
--
% Randy Yates % "Watching all the days go by...
%% Fuquay-Varina, NC % Who are you and who am I?"
%%% 919-577-9882 % 'Mission (A World Record)',
%%%% <yates@ieee.org> % *A New World Record*, ELO
http://www.digitalsignallabs.com
Reply by Fred Marshall●December 9, 20082008-12-09
Mike J Smith wrote:
> Hi
>
> I'm new to DSP. I'm working on an ultrasonic project which involves
> measuring the time of flight of a 40khz pulse between 2 transducers. I
> think I understand how to use cross correlation to slide a stored
> version of the pulse shape across the received signal until a match
> is found. This seems to be called matched filtering.
>
> I have seen references to a technique called mismatched filtering,
> particularly in radar applications, but despite lots of Googling I
> haven't been able to find anything which explains the concept it in a
> non-mathematical way that I understand. I don't have access to a
> technical library.
>
> Can anybody help?
>
> Thanks
>
> Mike
It occurs to me that "mismatched" filtering is simply filtering that isn't
"matched".
Matched filtering can be accomplished by convolving the received signal with
a replica of the transmit signal - and using frequency-shifted replicas to
deal with Doppler, etc. The objective is to get the best noise gain against
white noise in a least-squares sense.
So, if the reference signal for the convolution isn't exactly a replica then
the filter might be said to be "not matched" or "mismatched".
For example, a radar might simply use a passband filter that just filters
away noise that's outside the entire band of interest - including Doppler.
It's not optimum re: noise gain but it may work just fine. It's not
"matched". But, it a heck of a lot easier to implement.
Fred
Reply by Mike J Smith●December 9, 20082008-12-09
Hi
I'm new to DSP. I'm working on an ultrasonic project which involves
measuring the time of flight of a 40khz pulse between 2 transducers. I
think I understand how to use cross correlation to slide a stored version
of the pulse shape across the received signal until a match is found. This
seems to be called matched filtering.
I have seen references to a technique called mismatched filtering,
particularly in radar applications, but despite lots of Googling I haven't
been able to find anything which explains the concept it in a
non-mathematical way that I understand. I don't have access to a technical
library.
Can anybody help?
Thanks
Mike