Affiliation of Author(s):航天学院

Journal:PROCEEDINGS OF THE 2017 2ND INTERNATIONAL CONFERENCE ON MACHINERY, ELECTRONICS AND CONTROL SIMULATION (MECS 2017)

Key Words:arbitrary array acoustic vector-sensor compress PARAFAC model angle estimation

Abstract:In this paper, in order to estimate the angles for arbitrarily spaced arrays with acoustic vector-sensor, we combine the compressed sensing theory with parallel factor (PARAFAC) model, and propose a neoteric angle estimation algorithm. The proposed algorithm firstly compressed the PARAFAC model, then exploit trilinear alternating least square (TALS) algorithm to estimate the parameter matrices and obtains the angle estimation. Owing to compression, the proposed algorithm has smaller storage requirement and lower computational complexity, compared with the conventional PARAFAC algorithm. It's also works well to achieve automatically paired azimuth and elevation angles. The angle estimation performance of the proposed algorithm is close to the conventional PARAFAC algorithm, and is better than the estimation of signal parameters via rotational invariance techniques (ESPRIT) algorithm. Various simulation results demonstrate the effectiveness of our algorithm.

ISSN No.:2352-5401

Translation or Not:no

Date of Publication:2017-01-01

Co-author:许乐,孙友,Shi, Na

Correspondence Author:许乐,zxf