Research on Bayesian Estimation of Time-Varying Delay

Meng Wang (), Ying Liu and Ji-wang Zhang
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Meng Wang: University of Beijing Transportation
Ying Liu: University of Beijing Transportation
Ji-wang Zhang: University of Beijing Transportation

Chapter Chapter 132 in The 19th International Conference on Industrial Engineering and Engineering Management, 2013, pp 1251-1262 from Springer

Abstract: Abstract Time delay estimation is one of key techniques to array signal processing, and it has already had several mature algorithms. According to its different scenes, time delay estimation can be transferred to the estimation of coefficients of adaptive filter, which is on the basis of parameter model of adaptive filter. The simulations of Bayesian methods including Extended Kalman Filter, Unscented Kalman Filter and Bootstrap Particle Filter show that under Gaussian nonlinear system, EKF and UKF can estimate time-varying delay effectively. Besides, algorithms of UKF perform better than that of EKF, which are only subject to Gaussian system. In the nonlinear non-Gaussian system, BSPF is able to estimate time delay exactly.

Keywords: Time delay estimation; Extended Kalman Filter; Unscented Kalman Filter; Bootstrap Particle Filter (search for similar items in EconPapers)
Date: 2013
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-642-38391-5_132

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DOI: 10.1007/978-3-642-38391-5_132

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