A Novel Combination Method for Image Restoration Based on Bootstrap Filter and DWT

In our paper, we propose a novel combination of two methods based on the bootstrap filter. We will use the fusion technique to combine the restored images from the bootstrap multivariate kernel density filter and the bootstrap kernel-diffeomorphism filter. Experimental results have shown that our method has proved the image restoration results.

Particle Filters

This chapter explains how the key difficulty that arises when the Bayesian estimation of DSGE models is extended from linear to nonlinear models is the evaluation of the likelihood function, and focuses on the use of particle filters to accomplish this task. The basic bootstrap particle filtering algorithm is remarkably straightforward, but may perform quite poorly in practice. Thus, much of the literature about particle filters focuses on refinements of the bootstrap filter that increases the efficiency of the algorithm. The accuracy of the particle filter can be improved by choosing other proposal distributions. While the tailoring (or adaption) of the proposal distributions tends to require additional computations, the number of particles can often be reduced drastically, which leads to an improvement in efficiency.

Searching and Localizing a Radio Target by an Unmanned Flying Vehicle Using Bootstrap Filtering

In this article, an algorithm has been developed to search and localize a radio target in a marine area. This algorithm consists of two main parts, estimation and guidance. In the estimation part, bootstrap filtering has been employed to extract the target states from measurements. Although, by utilizing bootstrap filter, the target states can be estimated without requiring special maneuvers, exploiting proper guidance law to maximize the information gain can significantly enhance the localization performance. For evaluating the developed algorithm, an accurate simulation software with six degrees of freedom mathematical model including autopilot is used. Obtained statistical results from different simulation runs for both stationary and moving targets are presented to demonstrate the performance of the developed algorithm.