use chirp z transform for spectral resolution let us suppose that we some signal $x(t)$,which consist of sinusoidal   components and white noise,i would like to know how to use    chirp z transform for improving spectral resolution?i found   this article about  chirp z transform 

http://prod.sandia.gov/techlib/access-control.cgi/2005/057084.pdf

also  similar  article on official matlab side

http://www.mathworks.com/help/signal/ref/czt.html

but  as i know always in spectral estimation methods,some  knowledge we should know how process is going,or  some other things,let us suppose that we know sampling frequency lat say $Fs=100$,and   also we know that it consist as i mentioned by periodic components(sin or cosine),but i dont  know number of components,neither frequency or neither phases(+neither amplitudes),how can i apply chirp z transform to this signal?we have just some signal samples  with size $N=294$ ,please help me how to  choose correct components so that  get  effectively spectral structure and if let say one frequency is $f_1=13$ and second $f_2=13.5$,this transform be able to separate this  frequencies from each other,thanks
If you have no prior knowledge about the approximate locations of the frequencies, the Chirp Z-transform is of no immediate use to you. The Chirp Z-transform functions like a magnifying glass, so you need to know where you want to look and the Chirp Z-transform will show you the details. I would suggest you use an FFT to get an idea where the frequencies are, and if you need a very high resolution in a certain area of the spectrum, then the Chirp Z-transform can be useful. However, if computational complexity and memory are no issue, you can simply use a long FFT to achieve the same. If you want to know more about the Chirp Z-transform I would recommend this paper to you.