A study on input noise second-order filtering and smoothing of linear stochastic discrete systems with packet dropouts

Huihong Zhao,Tongxing Li,Bin Li,Zhifang Li

doi:10.1186/s13662-020-02903-7

Abstract

We investigate non-Gaussian noise second-order filtering and fixed-order smoothing problems for non-Gaussian stochastic discrete systems with packet dropouts. We present a novel Kalman-like nonlinear non-Gaussian noise estimation approach based on the packet dropout probability distribution and polynomial filtering technique. By means of properties of Kronecker product we first introduce a second-order polynomial extended system and then analyze the means and variances of the Kronecker powers of the extended system noises. To generate noise estimators in forms of filtering and smoothing, we use the innovation approach. We give an example to illustrate that the presented algorithm has better robustness against packet dropouts than conventional linear minimum variance estimation.

Highlights

During the last three decades, the estimation problem of input noise has become an active field in industry and has a wide range of applications in fault detection, petroleum prospecting, image restoration, speech processing, and so forth [1,2,3,4,5,6]
Because of the limitation of the communication bandwidth, service capacity, and carrying capacity of the network control systems, packet dropouts inevitably exist in the data transmission, which lead to the performance degradation or even instability of the control systems [14]
5 Conclusions A novel input noise nonlinear estimate algorithm is put forward for nonGaussian stochastic systems with packet dropouts, where the packet dropout characteristic is modeled as a multiplicative binary (0 or 1) distributed stochastic white sequence

Summary

Introduction

During the last three decades, the estimation problem of input noise has become an active field in industry and has a wide range of applications in fault detection, petroleum prospecting, image restoration, speech processing, and so forth [1,2,3,4,5,6]. We use the polynomial filtering theory to investigate the second-order polynomial estimator design problem for a class of packet dropout systems in non-Gaussian manner.

Results

Conclusion