Papers by Keyword: Music Algorithm

Abstract: To the conformal array antennas, the conventional DOA estimation algorithms will be affected by the Rayleigh limit. While, the MUSIC algorithm can solve this problem, it fully utilizes the orthogonality of noise subspace and signal subspace. It can achieve the DOA estimation through the spectrum peak search. The MUSIC algorithm is analyzed. Based on the cylindrical and conical array antenna, the algorithms are simulated. The simulation results show that the array arrangement mode can exert an important influence on the DOA estimation.

Abstract: The Classical MUSIC algorithm points out that in order to distinguish N waves from different directions,an N element array is needed. Therefore, in order to distinguish multi-detect signal simultaneously, an array is needed ,the payload of satellite and reconnaissance aircraft platform is limited , large array antenna can’t be placed, and application of MUSIC algorithm is restricted on these platform. In this paper a MUSIC algorithm with single antenna is proposed using movement of single antenna, the resource-demanding disadvantage of classical is improved.This algorithm can be used on resource limit satellite and aircraft platform.This algorithm is verified efficacious in the paper by simulation.

Abstract: Music algorithm has good spatial resolution, provides the possibility to further improve the performance of fire radio communication system, but the algorithm in the target range rapidly changing circumstances poor stability. Aiming at this problem, this paper proposes a MUSIC algorithm based on time domain analytical signals (TAMUSIC, Time-domain Analysis MUSIC). The TAMUISC algorithm first constructs analytical time-domain signal; then the time domain analytical signal covariance matrix; finally the covariance matrix eigenvalue decomposition, the noise subspace estimation results of spatial spectrum. The simulation results show that, TAMUSIC algorithm in target azimuth change quickly, compared with the conventional MUSIC algorithm, need a short observation time, observation has smaller variance.

Abstract: This paper presents a beamforming matrix with spatial smoothing effect, and extends it to the space-time 2D signal model, which not only reduces the computational complexity of the space-time 2D MUSIC algorithm and improves the coherence resolution capacity, simulation results show that this algorithm has better performance and effectiveness than MUSIC itself.

Abstract: the correlation coefficient estimation algorithm based on subspace decomposition is presented in this paper. The correlation coefficient between the signals is obtained by getting eigen-value decomposition of the data covariance matrix, and deriving the relationship between signal subspace and noise subspace. Simulation results verify that this algorithm can be realized to get the correlation coefficient between two incident signals whose DOA are known and the effect of the correlation coefficient estimation is made by different signal direction angular intervals.

Abstract: This dissertation systematically studies beam space high resolution bearing estimation algorithms. The solution to target resolving and bearing estimation is proposed to remove the contribution from interferes outside the beam coverage area. MVDR adaptive beam based on sample covariance matrix inversion (SMI) is demonstrated for the condition under which strong interferes and signals are weakly correlated. For the situation that strong interferes and signals are strongly correlated, MVDR beam forming algorithm based on virtual interferes is proposed to suppress strong interferes. Simulation results indicate that the beam space MUSIC algorithm based on MVDR is an effective way to resolve multiple targets in small angle domain.

Abstract: This paper discussed the problem of two dimensional (2D) direction of arrival (DOA) estimation for multi-input multi-output (MIMO) radar. The minimum-redundancy linear array (MLRA) is introduced into the transmitting array and receiving array, which enables the high efficiency of the radar system. By utilizing the algorithm of multiple signal classification (MUSIC), we illustrate that the proposed scheme performs better than the uniform linear arrays (ULA) configuration under the same conditions. Simulation results verify the effectiveness of our scheme.

Abstract: In this paper, a sub-array divided technique using K-means algorithm for spherical conformal array is proposed. All elements of spherical conformal array can be divided into a few sub-arrays by employing the K-means algorithm, and the standard multiple signal classification (MUSIC) algorithm is applied to estimate signals Direction-of-arrival (DOA) on these sub-arrays. Simulations of estimating DOA on a rotational spherical conformal array have been made and the results show that the resolution of DOA is improved by our method compare to existing methods.

Abstract: As a new type of underwater acoustic sensors,the principle of the MEMS hydrophone is introduced in this paper.MUSIC is a algorithm for estimating the parameter of the signal and it has a high resolution.In order to verify DOA estimation performance of MEMS vector array,experiment has been done.the experiments results showed that the MEMS vector array can achieve DOA estimation and track the underwater moving target.thus,it is concluded the feasibility of the MEMS vector array.

Abstract: Vector hydrophone is composed of acoustic pressure sensor and particle velocity sensor, which can simultaneously measure acoustic pressure and orthogonal components of particle velocity. MUSIC (Multiple Signal Classification) algorithm is a high resolution spatial spectrum analysis method based on subspace decomposition. This paper introduces the operation principles of this algorithm in detail and investigates the application of MUSIC algorithm to the DOA estimation of acoustic sources by a vector-hydrophone ULA (Uniform Linear Array) output model. Simulation results indicate that the resolution capability of MUSIC algorithm under larger SNRs is excellent.