Performance Analysis of Angular-Smoothing.doc
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1、豆丁网精品论文Performance Analysis of Angular-SmoothingBased Root-MUSIC for an L-ShapedAcoustic Vector-Sensor ArrayYougen Xu Zhiwen LiuDepartment of Electronic Engineering, Beijing Institute of Technology, Beijing, PRC AbstractEigenstructure-based direction-of-arrival (DOA) estimation algorithms such as M
2、ultiple Signal Classification (MUSIC), Root-MUSIC, Estimation of Signal Parameters via Rotational Invariance Techniques (ESPRIT), encounter great difficulty in the presence of perfectly correlated incident signals. For an array composed of a number of translational invariant subarrays such as a unif
3、orm linear scalar-sensor array, this problem can be solved by spatial smoothing. An array of identically oriented acoustic vector-sensors can be grouped into four coupled subarrays of identical grid geometry, respectively corresponding to the pressure sensors and differently oriented velocity-sensor
4、s. These four subarrays are angular invariant dependent only on signals direction cosines and an angular smoothing can be exploited for source decorrelation. In this paper, the performance of root-MUSIC incorporated with angular smoothing for correlated source direction finding with an L-shaped acou
5、stic vector-sensor array is analyzed in terms of the overall root mean-square errors (RMSE) of DOA estimates. We derive the analytical expression of the RMSE and compare it with simulation results and that of spatial smoothing for a rectangular pressure-sensor array instead.Keywords: Antenna arrays,
6、 array signal processing, direction-of-arrival estimation, acoustic array1 Introduction1.1 Acoustic Vector-SensorsAcoustic vector-sensors have attracted increasing interest for subspace-based direction-finding8-17. A “complete” acoustic vector-sensor such as a vector-hydrophone and a microflown cons
7、ists of a pressure sensor and a collocated triad of three orthogonal velocity sensors 8. These four sensors together measure the scalar acoustic pressure and all three components of the acoustic particle velocity vector of the incident wave-field at a given point. An “incomplete” acoustic vector-sen
8、sor consists of a subset of the above four component-sensors, e.g., a three-component hydrophone formed from two orthogonally oriented velocityThis work was supported by the National Natural Science Foundation of China under grant no.60272025, the University Basic Research Foundation of Beijing Inst
9、itute of Technology under grant no.BIT-UBF-200301F07 and no. BIT-UBF-200501F4202, and the Specialized Research Fund for the DoctoralProgram of Higher Education under grant no. 20040007013.hydrophones and a pressure hydrophone 13.It is assumed that the acoustic wave is traveling in a quiescent, homog
10、eneous, and isotropic fluid, and isfrom a source of azimuth and elevation , where 0 Q ). This proposed angular smoothing scheme represents a counterpart of polarisation smoothing 18 for an array of identically orientedelectromagnetic vector-sensors.Although developed here for a very regular L-shaped
11、 acoustic vector-sensor array to apply computationally efficient root-MUSIC, the angular smoothing algorithm is applicable for an array of identically oriented acoustic vector-sensors but with any arbitrary grid geometry. In addition, unlike classical spatial smoothing,the angular smoothing can be a
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