A Fast DOA Estimation Algorithm Based on Direct Data Domain Least Square Approach

2006 ◽  
Author(s):  
Shao Wei ◽  
Zu-ping Qian
Keyword(s):  
Estimation Algorithm ◽  
Doa Estimation ◽  
Least Square ◽  
Direct Data ◽  
Least Square Approach ◽  
Direct Data Domain

scholarly journals Generalized Sparse Polarization Array for DOA Estimation Using Compressive Measurements

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Tao Chen ◽  
Jian Yang ◽  
Weitong Wang ◽  
Muran Guo
Keyword(s):  
Degrees Of Freedom ◽  
Elevation Angle ◽  
Least Square Method ◽  
Estimation Algorithm ◽  
Doa Estimation ◽  
Least Square ◽  
Polarization Angle ◽  
Estimation Performance ◽  
The Difference ◽  
Cramer Rao Bound

The compressive array method, where a compression matrix is designed to reduce the dimension of the received signal vector, is an effective solution to obtain high estimation performance with low system complexity. While sparse arrays are often used to obtain higher degrees of freedom (DOFs), in this paper, an orthogonal dipole sparse array structure exploiting compressive measurements is proposed to estimate the direction of arrival (DOA) and polarization signal parameters jointly. Based on the proposed structure, we also propose an estimation algorithm using the compressed sensing (CS) method, where the DOAs are accurately estimated by the CS algorithm and the polarization parameters are obtained via the least-square method exploiting the previously estimated DOAs. Furthermore, the performance of the estimation of DOA and polarization parameters is explicitly discussed through the Cramér-Rao bound (CRB). The CRB expression for elevation angle and auxiliary polarization angle is derived to reveal the limit of estimation performance mathematically. The difference between the results given in this paper and the CRB results of other polarized reception structures is mainly due to the use of the compression matrix. Simulation results verify that, compared with the uncompressed structure, the proposed structure can achieve higher estimated performance with a given number of channels.

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