The Kalman-Bucy filter accuracy in the guaranteed parameter estimation problem with uncertain statistics

1994 ◽  
Vol 39 (3) ◽  
pp. 635-639 ◽  
Author(s):  
A.I. Matasov
Keyword(s):  
Parameter Estimation ◽  
Estimation Problem ◽  
Parameter Estimation Problem ◽  
Uncertain Statistics

A RELAX Based Method for Spotlight SAR Imaging

2012 ◽  
Vol 500 ◽  
pp. 362-367
Author(s):  
Xiao Zhen Ren ◽  
Yao Qin ◽  
Hong Liang Fu
Keyword(s):  
Parameter Estimation ◽  
Estimation Problem ◽  
Noisy Environment ◽  
Parameter Estimation Problem ◽  
Imaging Algorithm ◽  
Imaging Results ◽  
Sar Imaging ◽  
Simulation Results ◽  
Noisy Condition

The imaging problem of spotlight SAR is converted to a parameter estimation problem of several monochromatic signals in additive white Gaussian noisy condition in this paper. Moreover, a spotlight SAR imaging algorithm based on RELAX is presented in detail. Traditional polar format algorithm and the presented method are applied to spotlight SAR imaging respectively, and the imaging results are compared. Simulation results show that the polar format algorithm doesn’t give satisfactory imaging results, while the proposed method adapts the noisy environment better and obtains better results.

Exponential ergodicity of an affine two-factor model based on the α-root process

2017 ◽  
Vol 49 (4) ◽  
pp. 1144-1169 ◽  
Author(s):  
Peng Jin ◽  
Jonas Kremer ◽  
Barbara Rüdiger
Keyword(s):  
Parameter Estimation ◽  
Factor Model ◽  
Estimation Problem ◽  
Two Dimensional ◽  
Dimensional Model ◽  
Parameter Estimation Problem ◽  
Exponential Ergodicity ◽  
Model Based ◽  
Defaultable Bonds ◽  
Two Dimensional Model

Abstract We study an affine two-factor model introduced by Barczy et al. (2014). One component of this two-dimensional model is the so-called α-root process, which generalizes the well-known Cox–Ingersoll–Ross process. In the α = 2 case, this two-factor model was used by Chen and Joslin (2012) to price defaultable bonds with stochastic recovery rates. In this paper we prove exponential ergodicity of this two-factor model when α ∈ (1, 2). As a possible application, our result can be used to study the parameter estimation problem of the model.

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