Bearing estimation without using complex transform

Author

Lin, Sheng ; Yin, Qin-Ye

Author_Institution

Dept. of Inf. & Control Eng., Xi´´an Jiaotong Univ., Shaanxi, China

fYear

1993

fDate

3-6 May 1993

Firstpage

2307

Abstract

A new eigen-decomposition method of direction of arrival (DOA) estimation for multiple narrowband sources is presented. The most important feature of the method hinges upon the fact that both the signal and eigenvector are real values and the principal components of the input stochastic process can be computed by neuron-like networks such as the APEX method. Thus, the method is simple in computation and beneficial to real-time processing. However, it may introduce uncertainty in its spectrum. The problem is resolved by using two uniform linear arrays. One is placed horizontally and the other is set at a slant. Simulation results show the merit of the new method for bearing estimation of incoherent sources in an additive white noise environment

Keywords

direction-of-arrival estimation; eigenvalues and eigenfunctions; neural nets; stochastic processes; white noise; APEX method; DOA estimation; additive white noise environment; bearing estimation; eigen-decomposition method; incoherent sources; input stochastic process; multiple narrowband sources; neuron-like networks; uncertainty; uniform linear arrays; Additive white noise; Computational modeling; Computer networks; Direction of arrival estimation; Fasteners; Narrowband; Signal processing; Signal resolution; Stochastic processes; Uncertainty;

fLanguage

English

Publisher

ieee

Conference_Titel

Circuits and Systems, 1993., ISCAS '93, 1993 IEEE International Symposium on

Conference_Location

Chicago, IL

Print_ISBN

0-7803-1281-3

Type

conf

DOI

10.1109/ISCAS.1993.394224

Filename

394224