Alpha Stable Distribution Noise Research Articles

Simulation of VLF CSS System in Atmospheric Noise

Very Low Frequency (VLF) communication is designed to operate in the frequency between 3 kHz and 30 kHz. The atmospheric noise generated by lightning phenomena is the main source of interference in VLF communications, it is rather difficult to detect the communication signal that not only merged in strong channel noise, but probably interfered by high-tension impulse caused by thunder. This paper, Alpha stable distribution noise model is proposed to simulate atmospheric noise firstly, then, we study a new technique of Chirp Spread Spectrum (CSS) communication based on Fractional Fourier Transform (FRFT), This paper studies a new VLF communication technique of the Chirp Spread Spectrum (CSS) communication based on Fractional Fourier Transform (FRFT), and it demodulates message utilizing energy gathering property of chirp signal in FRFT domain.

Parameter estimation based on fractional power spectrum under alpha-stable distribution noise environment in wideband bistatic MIMO radar system

This paper takes the alpha-stable distribution as the noise model and works on the parameter estimation problem of wideband bistatic Multiple-Input Multiple-Output (MIMO) radar system in the impulsive noise environment. In many applications, it is not appropriate to approximate the wideband signal by the narrowband model. Furthermore, the echo signal may be corrupted by the non-Gaussian noise. The conventional algorithms degenerate severely in the impulsive noise environment. Thus, this paper proposes a new wideband signal model and a novel method in wideband bistatic MIMO radar system. It combines the fractional lower order statistics and fractional power spectrum, for suppressing the impulse noise and estimating parameters of the target. Firstly, a new signal array model is proposed under the alpha-stable distribution noise model. Secondly, Doppler stretch and time delay are jointly estimated by peak searching of the FLOS-FPSD. Furthermore, two modified algorithms are proposed for the estimation of the direction-of-departure and direction-of-arrival, including the fractional power spectrum density based on MUSIC algorithm (FLOS-FPSD-MUSIC) and the fractional lower-order ambiguity function based on ESPRIT algorithm (FLOS-FPSD-ESPRIT). Simulation results are presented to verity the effectiveness of the proposed method.

Modulation Recognition of MFSK Signals Based on Multifractal Spectrum

In order to solve the problem that modulation recognition of MFSK signals in alpha-stable distribution noise, a novel algorithm using multifractal spectrum is proposed. Multifractal spectrum characteristics of signals and noise are discussed firstly. Then algorithm extracts the difference between maximum and minimum values of spectrum as classification feature. Finally, algorithm employs threshold decision method to achieve modulation recognition of 2FSK, 4FSK and 8FSK signals. Numerical results show that algorithm has good performance in both alpha-stable distribution noise and Gaussian noise, and it is less affected by characteristic exponent of noise and data points.

A new blind source separation method based on fractional lower‐order statistics

AbstractWe proposed neural network structures related to multilayer feed‐forward networks for performing blind source separation (BSS) based on fractional lower‐order statistics. As alpha stable distribution process has no its second‐ or higher‐order statistics, we modified conventional BSS algorithms so that their capabilities are greatly improved under both Gaussian and lower‐order alpha stable distribution noise environments. We analysed the performances of the new algorithm, including the stability and convergence performance. The analysis is based on the assumption that the additive noise can be modelled as alpha stable process. The simulation experiments and analysis show that the proposed class of networks and algorithms is more robust than second‐order‐statistics‐based algorithm. Copyright © 2006 John Wiley & Sons, Ltd.