Nonlinear State Estimation Using Hybrid Robust Cubature Kalman Filter
Journal Title: Journal of Information Systems and Telecommunication - Year 2016, Vol 4, Issue 2
Abstract
In this paper, a novel filter is provided that estimates the states of any nonlinear system, both in the presence and absence of uncertainty with high accuracy. It is well understood that a robust filter design is a compromise between the robustness and the estimation accuracy. In fact, a robust filter is designed to obtain an accurate and suitable performance in presence of modelling errors.So in the absence of any unknown or time-varying uncertainties, the robust filter does not provide the desired performance. The new method provided in this paper, which is named hybrid robust cubature Kalman filter (CKF), is constructed by combining a traditional CKF and a novel robust CKF. The novel robust CKF is designed by merging a traditional CKF with an uncertainty estimator so that it can provide the desired performance in the presence of uncertainty. Since the presence of uncertainty results in a large innovation value, the hybrid robust CKF adapts itself according to the value of the normalized innovation. The CKF and robust CKF filters are run in parallel and at any time, a suitable decision is taken to choose the estimated state of either the CKF or the robust CKF as the final state estimation. To validate the performance of the proposed filters, two examples are given that demonstrate their promising performance.
Authors and Affiliations
Behrouz Safarinejadian, Mohsen Taher
Keywords
Related Articles
- EP ID EP184445
- DOI 10.7508/jist.2016.02.005
- Views 120
- Downloads 0
A New Recursive Algorithm for Universal Coding of Integers
In this paper, we aim to encode the set of all positive integers so that the codewords not only be uniquely decodable but also be an instantaneous set of binary sequences. Elias introduces three recursive algorithms for...
Improved Generic Object Retrieval In Large Scale Databases By SURF Descriptor
Normally, the-state-of-the-art methods in field of object retrieval for large databases are achieved by training process. We propose a novel large-scale generic object retrieval which only uses a single query image and t...
The Surfer Model with a Hybrid Approach to Ranking the Web Pages
Users who seek results pertaining to their queries are at the first place. To meet users’ needs, thousands of webpages must be ranked. This requires an efficient algorithm to place the relevant webpages at first ranks. R...
Cover Selection Steganography Via Run Length Matrix and Human Visual System
A novel approach for steganography cover selection is proposed, based on image texture features and human visual system. Our proposed algorithm employs run length matrix to select a set of appropriate images from an imag...
Scalable Community Detection through Content and Link Analysis in Social Networks
Social network analysis is an important problem that has been attracting a great deal of attention in recent years. Such networks provide users many different applications and features; as a result, they have been mentio...