A New Method for Angle Estimation in MIMO Radar with Blind Source Separation

2014 ◽  
Vol 543-547 ◽  
pp. 2500-2504 ◽  
Author(s):  
Yu Cai Pang ◽  
Chao Zhu Zhang
Keyword(s):  
Closed Form ◽  
Blind Source Separation ◽  
Source Separation ◽  
Algebraic Method ◽  
Mimo Radar ◽  
New Method ◽  
Relative Advantage ◽  
Joint Direction ◽  
Simulation Results ◽  
Source Signals

A joint direction of departures (DODs) and direction of arrivals (DOAs) estimation for bistatic MIMO radar with an algebraic method for blind source separation (BSS) is presented. The proposed method has the relative advantage of simplicity. The DODs and DOAs of targets can be solved in closed-form and paired automatically. Moreover, BSS techniques enable this approach to recover the source signals from the mixed signals. Simulation results verify the effectiveness of the method.

Multiset Canonical Correlation Analysis Using for Blind Source Separation

2012 ◽  
Vol 195-196 ◽  
pp. 104-108 ◽  
Author(s):  
Hua Gang Yu ◽  
Gao Ming Huang ◽  
Jun Gao
Keyword(s):  
Correlation Analysis ◽  
Blind Source Separation ◽  
Canonical Correlation Analysis ◽  
Statistical Characteristic ◽  
Canonical Correlation ◽  
Temporal Structure ◽  
Source Separation ◽  
Simulation Results ◽  
Source Signals ◽  
Novel Algorithm

To solve the problem of blind source separation, a novel algorithm based on multiset canonical correlation analysis is presented by exploiting the different temporal structure of uncorrelated source signals. In contrast to higher order cumulant techniques, this algorithm is based on second order statistical characteristic of observation signals, can blind separate super-Gaussian and sub-Gaussian signals successfully at the same time with relatively light computation burden. Simulation results confirm that the algorithm is efficient and feasible.

A Novel Blind Source Separation Algorithm for Linear Mixture Signals

2014 ◽  
Vol 599-601 ◽  
pp. 1357-1359
Author(s):  
Wei Hua Liu ◽  
Yun Zhang ◽  
Ying Fu Chen ◽  
Lei Wang ◽  
Jian Cheng Liu
Keyword(s):  
Cost Function ◽  
Blind Source Separation ◽  
Source Separation ◽  
Separation Algorithm ◽  
Mixing Matrix ◽  
Separate Source ◽  
Simulation Results ◽  
The Cost ◽  
Source Signals

A novel blind source separation (BSS) algorithm for linear mixture signals is proposed. It is shown that the property can be used to separate source signals by finding an un-mixing matrix that maximizes the cost function value of separated signals. Simulation results illustrate the efficiency and the good performance of the algorithm.

Blind Complex Source Separation Based on Cyclostationary Statistics

2014 ◽  
Vol 519-520 ◽  
pp. 1051-1056
Author(s):  
Jie Guo ◽  
An Quan Wei ◽  
Lei Tang
Keyword(s):  
Blind Source Separation ◽  
Source Separation ◽  
Separation Performance ◽  
Separation Algorithm ◽  
Complex Signals ◽  
Cyclic Frequency ◽  
Complex Source ◽  
Simulation Results ◽  
Better Than ◽  
Separation Model

This paper analyzed a blind source separation algorithm based on cyclic frequency of complex signals. Under the blind source separation model, we firstly gave several useful assumptions. Then we discussed the derivation of the BSS algorithm, including the complex signals and the normalization situation. Later, we analyzed the complex WCW-CS algorithm, which was compared with NGA, NEASI and NGA-CS algorithms. Simulation results show that the complex WCW-CS algorithm has the best convergence and separation performance. It can also effectively separate mixed image signals, whose performance was better than NGA algorithm.

A New Method for Multi-Fault Diagnosis of Rotor System

2005 ◽  
Author(s):  
Jian Ping Jing ◽  
Guang Meng
Keyword(s):  
Fault Diagnosis ◽  
Blind Source Separation ◽  
Frequency Spectrum ◽  
Source Separation ◽  
Rotor System ◽  
New Method ◽  
Oil Whirl ◽  
System 2

A Blind Source Separation (BSS) based new method for multi-fault diagnosis of rotors is presented. The statistic variable based decorrelation approach is employed to analyze the signals of the rotors with crack and rub-impact, crack and oil-whirl multi-faults, the typical features of the frequency spectrum of each fault of the rotor are separated out. The separated results show that (1) the BSS technique is helpful to the multi-fault diagnosis of a rotor system. (2) Due to the signals in the same direction at different locations of a rotor is correlative in some extent, if the observed points are not chosen properly, the separated accuracy will be affected greatly. The analysis shows that: for a one shaft rotor, choosing the signals in x, y direction at a same point of a rotor will lead to a better separated result. (3) If want to applying the BSS to practical diagnosis of rotor system, some efforts and works still need to be done.

Sign in / Sign up

Export Citation Format

Share Document