Application of a Time-Frequency-Based Blind Source Separation to an Instantaneous Mixture of Secondary Radar Sources
نویسندگان
چکیده
In Secondary Surveillance Radar (SSR) systems, it is more difficult to locate and recognise aircrafts in the neighbourhood of civil airports since aerial traffic becomes greater. Here, we propose to apply a recent Blind Source Separation (BSS) algorithm based on Time-Frequency Analysis, in order to separate messages sent by different aircrafts and falling in the same radar beam in reception. The above source separation method involves joint-diagonalization of a set of smoothed version of spatial Wigner-Ville distributions. The technique makes use of the difference in the t− f signatures of the nonstationary sources to be separated. Consequently, as the SSR sources emit different messages at different frequencies, the above method is fitted to this new application. We applied the technique in simulation to separate SSR replies. Results are provided at the end of the paper. Keywords—Blind Source Separation, Time-Frequency Analysis, Secondary Radar
منابع مشابه
Blind Spectral-GMM Estimation for Underdetermined Instantaneous Audio Source Separation
The underdetermined blind audio source separation problem is often addressed in the time-frequency domain by assuming that each time-frequency point is an independently distributed random variable. Other approaches which are not blind assume a more structured model, like the Spectral Gaussian Mixture Models (Spectral-GMMs), thus exploiting statistical diversity of audio sources in the separatio...
متن کاملA Frequency Grouping Approach for Blind Deconvolution of Fairly Motionless Sources
A frequency grouping approach for multi-channel instantaneous blind source separation (I-BSS) of convolutive mixtures is proposed for a lower net residual inter-symbol interference (ISI) and inter-channel interference (ICI) than the conventional short-time Fourier transform (STFT) approach. Starting in the time domain, STFTs are taken with overlapping windows to convert the convolutive mixing p...
متن کاملSTFT based Blind Separation of Underdetermined Speech Mixtures
Analysis of non stationary signals like audio, speech and biomedical signals require good resolution both in time and frequency as their spectral components are not fixed. There are many applications of time-frequency analysis in non stationary signals like source separation, signal denoising etc. This paper presents an application of time frequency analysis using STFT, Short Time Fourier Trans...
متن کاملSTFT based Blind Separation of Underdetermined Speech Mixtures
Analysis of non stationary signals like audio, speech and biomedical signals require good resolution both in time and frequency as their spectral components are not fixed. There are many applications of time-frequency analysis in non stationary signals like source separation, signal denoising etc. This paper presents an application of time frequency analysis using STFT, Short Time Fourier Trans...
متن کاملAdaptive subspace algorithm for blind separation of independent sources in convolutive mixture
We propose an algorithm for blind separation of sources in convolutive mixtures based on a subspace approach. The advantage of this algorithm is that it reduces a convolutive mixture to an instantaneous mixture by using only second-order statistics (but more sensors than sources). Furthermore, the sources can be separated by using any algorithm for an instantaneous mixture (based generally on f...
متن کامل