dsp tips & tricks - the sliding DFT
- 10 March 2003
- journal article
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Signal Processing Magazine
- Vol. 20 (2), 74-80
- https://doi.org/10.1109/msp.2003.1184347
Abstract
The sliding DFT process for spectrum analysis was presented and shown to be more efficient than the popular Goertzel (1958) algorithm for sample-by-sample DFT bin computations. The sliding DFT provides computational advantages over the traditional DFT or FFT for many applications requiring successive output calculations, especially when only a subset of the DFT output bins are required. Methods for output stabilization as well as time-domain data windowing by means of frequency-domain convolution were also discussed. A modified sliding DFT algorithm, called the sliding Goertzel DFT, was proposed to further reduce the computational workload. We start our sliding DFT discussion by providing a review of the Goertzel algorithm and use its behavior as a yardstick to evaluate the performance of the sliding DFT technique. We examine stability issues regarding the sliding DFT implementation as well as review the process of frequency-domain convolution to accomplish time-domain windowing. Finally, a modified sliding DFT structure is proposed that provides improved computational efficiency.Keywords
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