Abstract
In this paper, we present an asymptotic analysis of a recursive cross-coupled Kalman filter algorithm for estimating the state of a partially observed bilinear stochastic system. The cross-coupled Kalman filter algorithm consists of two Kalman filters – each Kalman filter estimating the state of one of the two state components of the bilinear system. Our asymptotic analysis provides weak convergence results on the tracking capabilities of the resulting cross-coupled Kalman filter algorithm.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
