2001•Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIERequires access

Time-frequency analysis using sidelobe apodization

Gabriel Thomas

Open publisher page 1 citations

Abstract

Time-frequency techniques have been successfully used in the analysis of non-stationary signals. Several approaches have been proposed that address concerns such as Time-Frequency (TF) resolution and the elimination of cross-terms. In this work, a TF technique based on the use of Spatially Variant Apodization (SVA) is introduced that focuses on the detection of non-stationary signals that consists of several components that have different amplitudes. The SVA approach is applied to the Short-Time Fourier Transform (STFT) to detect small intensity components that are buried in high sidelobes of other components. Resolution using the SVA is better than the resolution obtained using the STFT with non-rectangular windows. Synthesis can be performed using the overlap-add method. Because of the implementation of the SVA, the modified STFT using sidelobe apodization can have good resolution, detect small intensity components, and show no cross terms in the TF plane, given that stationarity can be assumed using an appropriate window length in the STFT.

About this research paper

What this paper is about

Time-frequency techniques have been successfully used in the analysis of non-stationary signals. Several approaches have been proposed that address concerns such as Time-Frequency (TF) resolution and the elimination of cross-terms. In this work, a TF technique based on the use of Spatially Variant Apodization (SVA) is introduced that focuses on the detection of non-stationary signals that consists of several components that have different amplitudes. The SVA approach is applied to the Short-Time Fourier Transform (STFT) to detect small intensity components that are buried in high sidelobes of other components. Resolution using the SVA is better than the resolution obtained using the STFT with non-rectangular windows. Synthesis can be performed using the overlap-add method. Because of the implementation of the SVA, the modified STFT using sidelobe apodization can have good resolution, detect small intensity components, and show no cross terms in the TF plane, given that stationarity can be assumed using an appropriate window length in the STFT.

Why it matters

OpenAlex reports 1 citations for this work. Citation counts describe recorded attention and do not establish research quality.

Key contribution

A contribution statement is not available in the OpenAlex record.

Method / approach

Method details are not available in the OpenAlex metadata.

Main findings

Findings are not separately available in the OpenAlex metadata.

Limitations

Limitations are not available in the OpenAlex metadata.

Applications

Application details are not available in the OpenAlex metadata.

Available abstract

Time-frequency techniques have been successfully used in the analysis of non-stationary signals. Several approaches have been proposed that address concerns such as Time-Frequency (TF) resolution and the elimination of cross-terms. In this work, a TF technique based on the use of Spatially Variant Apodization (SVA) is introduced that focuses on the detection of non-stationary signals that consists of several components that have different amplitudes. The SVA approach is applied to the Short-Time Fourier Transform (STFT) to detect small intensity components that are buried in high sidelobes of other components. Resolution using the SVA is better than the resolution obtained using the STFT with non-rectangular windows. Synthesis can be performed using the overlap-add method. Because of the implementation of the SVA, the modified STFT using sidelobe apodization can have good resolution, detect small intensity components, and show no cross terms in the TF plane, given that stationarity can be assumed using an appropriate window length in the STFT.

Key concepts: Apodization, Short-time Fourier transform, Computer science, Time–frequency analysis, Fourier transform, Resolution (logic), Window function, Algorithm

Related papers

Back to paper searchBrowse research topicsOriginal source
Time-frequency analysis using sidelobe apodization — Research Paper | ScholarLens