Adaptive Transformed Unscented Simplex Cubature Kalman Filter for Target Tracking

ABSTRACT

This paper peruses the Doppler-bearing passive target tracking (DBT), a task that is subject to the nonlinear measurement equations. These measurement equations form the target tracking a nontrivial duty. In order to defeat these problems, many studies have reported various nonlinear estimation techniques, such as sigma-point Kalman filters. These types of filters have demonstrated superior performances for nonlinear system parameter estimation. Consequently, the main contribution of this paper is to improve the performance of the sigma-point Kalman filters. Thereafter, this paper introduces a transformed unscented simplex cubature Kalman filter, in which adaptation techniques are utilized to reduce the dependency of the proposed filter performance on the priori statistical information of the process and measurement noises. Moreover, the proposed filter is initialized by the range-parameterised Unscented Kalman filter. The Cramér–Rao lower bound (CRLB) determines the best accessible accuracy of estimators, which is utilized in this paper to accredit the performance of the proposed filter. The validity and feasibility of the proposed filter are confirmed by Monte Carlo simulations.

Keywords:

• Adaptation filters
• Doppler-shifted frequency
• Nonlinear equations
• Range-parameterised techniques
• Sigma-point Kalman filters
• Target tracking

Additional information

Funding

This work was supported by Ferdowsi University of Mashhad (FUM) [grant number 51094].

Notes on contributors

Seyed Hamed Hashemi

Seyed Hamed Hashemi received the BSc degree in electrical engineering from Babol Noshirvani University of Technology (BUT), Babol, Iran, in 2014, and received the MSc degree in electrical engineering from Shahroud University of Technology, Shahroud, Iran, in 2017. He is currently a PhD candidate and a research assistant at Ferdowsi University of Mashhad, Mashhad, Iran. His research interests include topological constraints in control systems, nonlinear control theory, control of hybrid systems, and estimation theory. Email: [email protected]

Naser Pariz

Naser Pariz received the BSc and MSc degrees in electrical engineering with Hons, from Ferdowsi University of Mashhad, Mashhad, Iran, in 1988 and 1991, respectively, and the PhD degree from the Department of Electrical Engineering, Ferdowsi University of Mashhad, in 2001. From 1991 to 1995, he was a lecturer at Ferdowsi University of Mashhad, where he is currently a professor. His research interests include power and control systems.