TWO-STAGE METHOD FOR PARAMETER ESTIMATING IN UNKNOWN NOISE ENVIRONMENT
DOI:
https://doi.org/10.34185/1562-9945-5-142-2022-04Keywords:
parameter estimation, cost function, Gaussian pulseAbstract
This paper addresses the parameter estimation problem in the case of an unknown noise environment. A two-stage method consisting of the tuning and estimating stages is pro-posed for solving this problem. At the tuning stage, the estimator is tuned to the noise envi-ronment by minimizing the estimation root-mean-square error for a known data fragment in the space of the three free parameters; these free parameters allow modifying the behavior of the minimization problem objective function. At the estimating stage, estimation is car-ried out by solving the corresponding minimization problem using already tuned free pa-rameters. The features of the proposed method, including algorithms for the tuning and es-timating stages, are demonstrated for estimating a Gaussian pulse that slowly moves in the unknown noise environment and locates on a known constant background. The numerical simulations confirm the high performance of the proposed method.
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