Unscented Kalman filter with improved forward-backward prediction for target tracking

Yang Liu; Pingbo Wang

doi:10.1117/12.2640016

23 May 2022 Unscented Kalman filter with improved forward-backward prediction for target tracking

Yang Liu, Pingbo Wang

Proceedings Volume 12254, International Conference on Electronic Information Technology (EIT 2022); 122540D (2022) https://doi.org/10.1117/12.2640016
Event: International Conference on Electronic Information Technology (EIT 2022), 2022, Chengdu, China

Abstract

In order to improve the accuracy of active sonar underwater target tracking, an improved algorithm is proposed based on the existing forward-backward prediction algorithm of unscented Kalman filter. The algorithm can adaptively perform forward-backward prediction operation, and replace the measured value with the state estimate value of the past moment to avoid nonlinear problem in reverse prediction. The simulation results show that when the total calculation amount is almost the same, the algorithm can improve the accuracy of state estimation better than the standard algorithm.

Citation Download Citation

Yang Liu and Pingbo Wang "Unscented Kalman filter with improved forward-backward prediction for target tracking", Proc. SPIE 12254, International Conference on Electronic Information Technology (EIT 2022), 122540D (23 May 2022); https://doi.org/10.1117/12.2640016

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available