Cyclic MUSIC Algorithm Research Articles

A Novel Extended Cyclic MUSIC algorithm using Wavelet Decomposition Technique

The study and analysis of direction of arrival(DOA) estimation has been a very challenging aspect in wireless communication systems, radar and sonar in the presence of a fading channel. Extended cyclic MUSIC subspace based method is reviewed for the DOA when noise is present. An extension of the Cyclic MUSIC algorithm is the Extended mode of the cyclic MUSIC which uses an extended version of the data array vector. Based upon the spectral correlation of the inbound signals these algorithms can estimate the signals’ direction of arrival. The spatially correlated noises, present degrade the performance of the Cyclic MUSIC algorithms and also fail to make an estimate of the signals' direction of arrival when they are closely spaced. The paper proposes an improved DOA estimation technique of Wavelet Decomposition when spatially correlated noises are present. The signals present at the receiver side are denoised and the required estimates of the transmitted signals are obtained by using the Extended Cyclic MUSIC algorithm to the denoised data. Simulations prove that the output SNR has been enhanced considerably.

DOA Estimation Using Single or Dual Reception Channels Based on Cyclostationarity

This paper addresses the problem of direction-of-arrival (DOA) estimation for cyclostationary signals using less reception channel in comparison with the number of sensors. The system is considered to be realized by using the reception channel(s) to receive the signal reached each sensor in turn. Such simplification results in a cost reduction of the system and the effect of inconsistency among different channels are removed. However, non-synchronized sampling also makes the traditional DOA estimation algorithms ineffective. To cope with the problem, the signal models for DOA estimation using a single channel and dual channels are formulated based on signal cyclostationary, and the single channel cyclic MUSIC (SC-Cyclic-MUSIC) algorithm and the dual channels cyclic MUSIC (DC-Cyclic-MUSIC) algorithm are proposed correspondingly. This paper shows that both SC-Cyclic-MUSIC algorithm and DC-Cyclic-MUSIC algorithm work well when the switching interval is known, and a satisfied performance can also be obtained by DC-Cyclic-MUSIC algorithm when the uncertainty of the switching interval exists. Moreover, the proposed estimators are suitable for both narrow-band and wide-band signals. The computer simulations are provided to verify the effectiveness of the proposed algorithms.

Novel Direction Findings for Cyclostationary Signals in Impulsive Noise Environments

We consider the problem of direction-of-arrival (DOA) estimation for cyclostationary signals in impulsive noise modeled as a complex symmetric α-stable (SαS) process. Since the DOA estimation based on second-order cyclic statistics degrades seriously in an α-stable distribution noise environment, we define a novel pth-order cyclic correlation by fusing the fractional lower order statistics and second-order cyclic correlation. After briefly introducing the statistical characteristics of pth-order cyclic correlation and building the extended data model, we first propose a novel extended pth-order cyclic MUSIC algorithm (EX-POC-MUSIC) by exploiting both pth-order cyclic correlation and pth-order cyclic conjugate correlation. The algorithm allows us to select desired signals and to ignore interference in the communication system. Second, in order to increase the resolution capabilities and the noise robustness significantly, an improved EX-POC-MUSIC algorithm called the extended pth-order cyclic Root-MUSIC (EX-POC-RMUSIC) algorithm is also presented. This algorithm has all the merits of the EX-POC-MUSIC algorithm, and it is also a fast DOA estimation algorithm because it avoids spatial spectrum searching. Under some conditions, both proposed algorithms are able to handle more sources than the number of sensors. Simulation results strongly verify the effectiveness of the two algorithms.

Performance comparison of wavelet denoising based fast DOA estimation of MIMO OFDM system over Rayleigh Fading Channel

This paper presents a tool for the analysis, and simulation of direction-of-arrival estimation for MIMO OFDM signal over the Rayleigh fading channel. The performance of the proposed technique is tested for wavelet denoising based CYCLIC MUSIC algorithm. Simulation results demonstrate that the proposed system not only has good ability of suppressing interference, but also significantly improves the DOA estimation of the system. In this paper, it is proposed to find DOA of the received MIMO OFDM signal, and the performances are analyzed using matlab simulation by the Monte Carlo computer iteration. This paper provides a fairly complete image of the performance and statistical efficiency with QPSK signal model for coherent system at a lower SNR(18dB) and interference environment.

Robust direction finding for cyclostationary signals with cycle frequency error

The cyclic MUSIC algorithm exploits the cyclostationarity exhibited by most man-made communication signals to perform signal-selective estimation of direction-of-arrival at an array sensor. The performance of cyclic MUSIC suffers from severe degradation even if there is a small mismatch in the cycle frequency of the signals of interest. Two improved cyclic MUSIC algorithms are introduced with which robustness to the cycle frequency error (CFE) is emphasized. Both methods allow simplicity in implementation and are shown to perform significantly better than conventional cyclic MUSIC when CFE exits. We evaluate their performance in both uncorrelated and coherent source scenarios by computer simulations.

Wideband cyclic MUSIC algorithms

In this paper, we propose two cyclic-MUSIC-like DOA estimation algorithms for wideband cyclostationary signals, the averaged cyclic MUSIC (ACM) algorithm and the extended wideband cyclic MUSIC (EWCM) algorithm. Compared with the existing spectral correlation signal subspace fitting (SC-SSF) algorithm, which was also developed for wideband cyclostationary signals, our new methods have more relaxed requirements on the signals. Simulation results show that under those circumstances, both our methods are superior to the existing SC-SSF algorithm.

An extended cyclic MUSIC algorithm

Many modulated communication signals exhibit a cyclostationarity (or periodic correlation) property, corresponding to the underlying periodicity arising from carrier frequencies or baud rates. In this paper, we propose a new MUSIC-like direction-finding algorithm that exploits cyclostationarity in order to improve the direction-of-arrival (DOA) estimation. Both cyclic and conjugate cyclic correlation matrices are used in the proposed method so that it can be considered as an extension of the cyclic MUSIC algorithm . The proposed cyclic method allows an increase in resolution power and noise robustness. Depending on the modulation type of incoming signals, the proposed method is also able to handle more sources than the number of sensors.

Performance analysis of the cyclic MUSIC method of direction estimation for cyclostationary signals

The cyclic MUSIC algorithm exploits the cyclostationarity exhibited by most man-made communication signals to perform signal-selective estimation of directions of arrival at an array of sensors. In the paper, the bias and mean-squared error of these direction estimates are derived under the assumption that the signals are complex, possibly non-Gaussian, and cyclostationary. The analytical results are shown to be excellent predictors of empirical results obtained from computer simulation of the cyclic MUSIC algorithm, and are also compared with the Cramer-Rao bound, which in certain cases can be orders of magnitude less than the Cramer-Rao bound for the directions of arrival of stationary signals.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>