Abstract
This paper presents a novel conditionally suboptimal filtering algorithm on estimation problems that arise in discrete nonlinear time-varying stochastic difference systems. The suboptimal state estimate is formed by summing of conditionally nonlinear filtering estimates that their weights depend only on time instants, in contrast to conditionally optimal filtering, the proposed conditionally suboptimal filtering allows parallel processing of information and reduce online computational requirements in some nonlinear stochastic difference system. High accuracy and efficiency of the conditionally suboptimal nonlinear filtering are demonstrated on a numerical example.
Highlights
Some simple Kalman-Bucy filters [1,2,3,4] lead to some conditionally optimal filtering [5,6,7]
This paper presents a novel conditionally suboptimal filtering algorithm on estimation problems that arise in discrete nonlinear time-varying stochastic difference systems
The suboptimal state estimate is formed by summing of conditionally nonlinear filtering estimates that their weights depend only on time instants, in contrast to conditionally optimal filtering, the proposed conditionally suboptimal filtering allows parallel processing of information and reduce online computational requirements in some nonlinear stochastic difference system
Summary
Some simple Kalman-Bucy filters [1,2,3,4] lead to some conditionally optimal filtering [5,6,7] This main idea is that the absolute unconditional optimality is rejected and in a class of admissible estimates with some nonlinear stochastic differential equations or nonlinear stochastic difference equations that can be solved online while receiving the results of the measurements, the optimal estimate is found. In this paper we are interesting in constituting a novel conditionally filtering algorithm addressing estimation problems that suboptimal arise in discrete nonlinear time-varying stochastic difference systems with different types of measurements [8,9,10]. The aim of this paper is to give an alternative conditionally suboptimal filtering for that kind of discrete time nonlinear stochastic difference systems.
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