Hybrid FM-polynomial phase signal modeling: parameter estimation and Cramer-Rao bounds

1999 ◽  
Vol 47 (2) ◽  
pp. 363-377 ◽  
Author(s):  
F. Gini ◽  
G.B. Giannakis
Keyword(s):  
Parameter Estimation ◽  
Signal Modeling ◽  
Polynomial Phase ◽  
Phase Signal

scholarly journals A Novel Parameter Estimation Method Based on LSU-EKF for Polynomial Phase Signal

2017 ◽  
Author(s):  
Yi-xiong Zhang ◽  
Hua-wei Xu ◽  
Rong-rong Xu ◽  
Zhen-miao Deng ◽  
Cheng-Fu Yang
Keyword(s):  
Monte Carlo ◽  
Parameter Estimation ◽  
Kalman Filter ◽  
Estimation Method ◽  
Computation Complexity ◽  
Parameter Estimation Problem ◽  
Performance Loss ◽  
Polynomial Phase ◽  
Polynomial Phase Signals ◽  
Phase Signal

The parameter estimation problem for polynomial phase signals (PPSs) arises in a number of fields, including radar, sonar, biology, etc. In this paper, a fast algorithm of parameter estimation for monocomponent PPS is considered. We propose the so-called LSU-EKF estimator, which combines the least squares unwrapping (LSU) estimator and the extended Kalman filter (EKF). First, the coarse estimates of the parameters of PPS are obtained by the LSU estimator using a small number of samples. Subsequently, these coarse estimates are used to initial the EKF. Monte-Carlo simulations show that the computation complexity of the LSU-EKF estimator is much less than that of the LSU estimator, with little performance loss. Similar to the LSU estimator, the proposed algorithm is able to work over the entire identifiable region. Moreover, in the EKF stage, the accurate estimated results can be output point-by-point, which is useful in real applications.

Parameter Estimation of Hybrid Sinusoidal FM-Polynomial Phase Signal

2017 ◽  
Vol 24 (1) ◽  
pp. 66-70 ◽  
Author(s):  
Pu Wang ◽  
Philip V. Orlik ◽  
Kota Sadamoto ◽  
Wataru Tsujita ◽  
Fulvio Gini
Keyword(s):  
Parameter Estimation ◽  
Polynomial Phase ◽  
Phase Signal
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