The Fast Chirp Transform Home Page


Introduction

The Fast Chirp Transform (FCT) is an algorithm designed to detect varying frequency signals. A full description of the method may be found in "Detection of Variable Frequency Signals Using a Fast Chirp Transform" by F. A. Jenet and T.A. Prince (submitted to PRD). A later report was produced by the FCT group "Generalization of the Fast Chirp Transform Algorithm", Jenet et al. (2003). The FCT along with this web cite are works in progress. A prototype implementation has be written in C++ and may be downloaded from this cite (download).

This web page is dedicated to the development of the FCT as a multipurpose signal processing and data analysis tool. The FCT was conceived in order to detect gravity wave signals from the LIGO observatory. Since varying frequency signals arise in many contexts, the FCT has a wide range of applicability. We welcome and encourage all interested researchers to download the current implementation and start applying it various data analysis problems.

Features

The current implementation performs a two parameter FCT on complex input data using a two dimensional Fast Fourier Transform (FFT). The first parameter is conjugate to the linear phase (constant frequency) term while the second parameter is conjugate to a user specific phase function. This phase function defines the way in which the frequency changes as a function of the independent variable (i.e. time). In order to compile and link the current version, you will need a C++ compiler and a current version of FFTW, an efficient implementation of the fast Fourier transform.

Feedback

We encourage any and all questions, comments, and suggestions concerning the current implementation of the FCT and this Web cite. Feel free to contact me, Fredrick A. Jenet, at merlyn@srl.caltech.edu.

News

5/2/2000 This Web page is activated
5/1/2000 The first C++ FCT implementation is completed

Visitor count since 9/5/2000: 15531

Publications


This material is based upon work supported in part by the National Science Foundation under Grant No. 0071050 Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation

Copyright California Institute of Technology (2000). All rights reserved. Patent Pending.