Square-root algorithms for the continuous-time linear least-square estimation problem

1978 ◽  
Vol 23 (5) ◽  
pp. 907-911 ◽  
Author(s):  
M. Morf ◽  
B. Levy ◽  
T. Kailath
Keyword(s):  
Continuous Time ◽  
Estimation Problem ◽  
Least Square ◽  
Square Root ◽  
Least Square Estimation ◽  
Linear Least Square ◽  
Time Linear

Linear least-square estimation algorithms involving correlated signal and noise

2005 ◽  
Vol 53 (11) ◽  
pp. 4227-4235 ◽  
Author(s):  
R.M. Fernandez-Alcala ◽  
J. Navarro-Moreno ◽  
J.C. Ruiz-Molina
Keyword(s):  
Least Square ◽  
Least Square Estimation ◽  
Estimation Algorithms ◽  
Linear Least Square

Nonlinear Least Square Localization Algorithm Based on Time Difference of Arrival

2013 ◽  
Vol 411-414 ◽  
pp. 903-906 ◽  
Author(s):  
Sheng Dong Xie ◽  
Ai Qun Hu ◽  
Yi Huang
Keyword(s):  
Optimal Solution ◽  
Least Square ◽  
Localization Algorithm ◽  
Least Square Estimation ◽  
Global Optimal Solution ◽  
Time Difference Of Arrival ◽  
Initial Location ◽  
Localization Precision ◽  
Global Optimal ◽  
Linear Least Square

TDOA is a predominant localization algorithm. In this paper, we propose a TDOA localization algorithm called NLLS, using the nonlinear least square estimation. We first get the initial location utilizing the LCLS algorithm, which could achieve the global optimal solution to the ordinary constraint linear least square estimation, and based on the initial location, we make use of nonlinear least square estimation to improve the localization precision. Simulation results show that compared with the CTLS algorithm, its performance is superior especially when the measurement noise is larger.

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