See also<br><br><div class="bookinfo_section_line book_title_line">Spectral analysis for physical applications: multitaper and conventional univariate techniques</div><div class="bookinfo_section_line">Donald B. Percival, Andrew T. Walden</div>
<div class="bookinfo_section_line">Cambridge University Press, 1993</div><div class="bookinfo_section_line">ISBN 0521435412, 9780521435413<br><br>It's really good.<br><br>73<br>Frank<br>AB2KT<br></div><br><br><div class="gmail_quote">
On Mon, Jun 8, 2009 at 5:57 PM, David McQuate <span dir="ltr"><<a href="mailto:mcquate@sonic.net">mcquate@sonic.net</a>></span> wrote:<br><blockquote class="gmail_quote" style="border-left: 1px solid rgb(204, 204, 204); margin: 0pt 0pt 0pt 0.8ex; padding-left: 1ex;">
***** High Performance Software Defined Radio Discussion List *****<br>
<br>
If I have a block of samples (say N = 4096, fs = 122.88 Msps),<br>
a straightforward FFT produces data with frequency resolution of 30kHz.<br>
<br>
Is there a technique that will allow me to obtain information on a finer<br>
frequency grid (say 1kHz or 300Hz or ...)--other than "simply" acquiring<br>
additional data, extending the length of the time record?<br>
<br>
I've looked at Chirp-Z transforms and polyphase decimation, but neither<br>
seems to produce higher frequency resolution. I've also looked into DttSP,<br>
but not found a solution there.<br>
<br>
Am I hoping for the impossible?<br>
<br>
Suggestions please.<br>
<br>
73,<br>
Dave<br>
wa8ywq<br>
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</blockquote></div><br><br clear="all"><br>-- <br>...although production beyond capacity is a contradiction in terms, it is observed every day in academia. -- Frank Knight<br>