Elsevier

Digital Signal Processing

Volume 16, Issue 5, September 2006, Pages 597-606
Digital Signal Processing

Adaptive interference removal based on concentration of the STFT

https://doi.org/10.1016/j.dsp.2005.03.004Get rights and content

Abstract

We propose a new method for adaptively removing noise and interference from a signal. In this method unwanted components are removed from the short time Fourier transform (STFT) surface, and the clean signal is estimated by integrating the modified STFT with respect to frequency. Isolation of the signal and interference components is facilitated by a concentration process based on the phase of the STFT differentiated with respect to time. The concentrated STFT is a linear representation, free of cross terms and having the property that signal and interference components are easily recognized because their distributions are more concentrated in frequency. Interference removal may be accomplished by removing unwanted components from the concentrated STFT, and the clean signal may be estimated by integration of the modified concentrated STFT. We demonstrate the advantages of the proposed method over conventional methods.

Section snippets

Douglas J. Nelson was born in Minneapolis, Minnesota on November 5, 1945. He received a bachelor's degree in mathematics from the University of Minnesota in 1967 and a Ph.D. in mathematics from Stanford University in 1972. After spending three years as an assistant professor at Carnegie-Mellon University, he accepted a position as a mathematician at the National Security Agency at Fort Meade, Maryland, where he has been from 1975 to the present. Dr. Nelson's primary interests are linear

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Cited by (5)

Douglas J. Nelson was born in Minneapolis, Minnesota on November 5, 1945. He received a bachelor's degree in mathematics from the University of Minnesota in 1967 and a Ph.D. in mathematics from Stanford University in 1972. After spending three years as an assistant professor at Carnegie-Mellon University, he accepted a position as a mathematician at the National Security Agency at Fort Meade, Maryland, where he has been from 1975 to the present. Dr. Nelson's primary interests are linear time-frequency methods, signal processing, signal analysis, signal detection and interference mitigation. At the NSA, he has applied these methods to the analysis and processing of radar, communications, spread spectrum and speech signals.

David C. Smith earned the B.S. degree in mathematics (1971) from the University of New Hampshire. He earned the M.A. in mathematics (1979) and the M.S. in computer sciences (1984) from the University of Texas at Austin, where he was an assistant instructor from 1977 to 1983. After earning the Ph.D. in mathematics (1985) from Texas, he worked for Lockheed Missiles & Space Co. (1985–1991) as a mathematician modeling electromagnetic scattering and propagation, while simultaneously working as an adjunct professor at San Jose State University. Dr. Smith joined the National Security Agency in 1991 as a mathematician working on cryptologic and signal processing problems. He earned an M.S. in physics (2002) from Johns Hopkins University. He is a member of Phi Beta Kappa.

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