Signal decomposition of HF radar maneuvering targets by using S&lt;sup&gt;2&lt;/sup&gt;-method with clutter rejection

Yan, Wei; Tan, Shanshan

doi:10.1109/jsee.2012.00021

Cited by 2 publications

(1 citation statement)

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“…Another work by G. Yu proposed a work on audio de-noising by using threshold in timefrequency block [4] . Y. S. Wei and team researched on algorithms for eliminating interference between signals and thus helping multi-target signals in high frequency Radars [5] . Y.C.Jiang worked on generalized time-frequency distributions for multi-component polynomial phase signals.…”

Section: Fig 1: Stft Of the Noisy Signalmentioning

confidence: 99%

Significance of Cohen's Class for Time Frequency Analysis of Signals

ThachamPoyil¹,

M²,

Aljahdali³

2013

IJCA

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In this paper, a study of quadratic transformations under Cohen"s class is presented, to see the variations in resolution for performing time-frequency analysis of signals. The study concentrated on the analysis of linear chirp signals and nonstationary signals in presence of noise as well as without noise. The resolutions based on Wavelet Transform, Short Time Fourier Transform are analysed. The effects of widow length, wavelet scale and presence of noise are researched and analyzed against the performance of different time-frequency representations. The Cohen's class is a class of time-frequency quadratic energy distributions which are covariant by translations in time and in frequency. This important property by the members of Cohen"s class makes those representations suitable for the analysis and detection of linear as well as transient signals. Spectrogram, the squared modulus of Short Time Fourier Transform is considered to be an element of Cohen"s class since it is quadratic and also co-variant in time and frequency. Wigner Ville Distribution is another member of Cohen"s class which can be extended to many other variants by changing the kernel functions used for cross-term reductions. The trade-off in the time-frequency localization are studied and demonstrated with the help of different plots. The result of this study can be applied to enhance the detection and analysis of signals and to develop efficient algorithms in medical diagnosis as well as defense applications.

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Section: Fig 1: Stft Of the Noisy Signalmentioning

confidence: 99%

Significance of Cohen's Class for Time Frequency Analysis of Signals

ThachamPoyil¹,

M²,

Aljahdali³

2013

IJCA

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A Cascaded Approach for Correcting Ionospheric Contamination with Large Amplitude in HF Skywave Radars

Yan

Guo

et al. 2014

The Scientific World Journal

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Ionospheric phase perturbation with large amplitude causes broadening sea clutter's Bragg peaks to overlap each other; the performance of traditional decontamination methods about filtering Bragg peak is poor, which greatly limits the detection performance of HF skywave radars. In view of the ionospheric phase perturbation with large amplitude, this paper proposes a cascaded approach based on improved S-method to correct the ionospheric phase contamination. This approach consists of two correction steps. At the first step, a time-frequency distribution method based on improved S-method is adopted and an optimal detection method is designed to obtain a coarse ionospheric modulation estimation from the time-frequency distribution. At the second correction step, based on the phase gradient algorithm (PGA) is exploited to eliminate the residual contamination. Finally, use the measured data to verify the effectiveness of the method. Simulation results show the time-frequency resolution of this method is high and is not affected by the interference of the cross term; ionospheric phase perturbation with large amplitude can be corrected in low signal-to-noise (SNR); such a cascade correction method has a good effect.

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Signal decomposition of HF radar maneuvering targets by using S<sup>2</sup>-method with clutter rejection

Cited by 2 publications

References 0 publications

Significance of Cohen's Class for Time Frequency Analysis of Signals

Significance of Cohen's Class for Time Frequency Analysis of Signals

A Cascaded Approach for Correcting Ionospheric Contamination with Large Amplitude in HF Skywave Radars

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Signal decomposition of HF radar maneuvering targets by using S<sup>2</sup>-method with clutter rejection

Cited by 2 publications

References 0 publications

Significance of Cohen&apos;s Class for Time Frequency Analysis of Signals

Significance of Cohen&apos;s Class for Time Frequency Analysis of Signals

A Cascaded Approach for Correcting Ionospheric Contamination with Large Amplitude in HF Skywave Radars

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Product

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Significance of Cohen's Class for Time Frequency Analysis of Signals

Significance of Cohen's Class for Time Frequency Analysis of Signals