Data association and passive tracking for multiple targets based on Gaussian sum particle filter

Feng Xue; Zhong Liu; Zhangsong Shi

doi:10.1117/12.716774

24 October 2006 Data association and passive tracking for multiple targets based on Gaussian sum particle filter

Feng Xue, Zhong Liu, Zhangsong Shi

Proceedings Volume 6357, Sixth International Symposium on Instrumentation and Control Technology: Signal Analysis, Measurement Theory, Photo-Electronic Technology, and Artificial Intelligence; 63570S (2006) https://doi.org/10.1117/12.716774
Event: Sixth International Symposium on Instrumentation and Control Technology, 2006, Beijing, China

Abstract

To improve tracking performance of multi-target tracking, a data association and passive tracking scheme based on the joint probabilistic data association (JPDA) and the Gaussian sum particle filter (GSPF) is proposed. The GSPF is presented to formulate the problem of passive tracking. Compared with sampling importance resampling (SIR) scheme, GSPF can incorporate the most current observations into the particle filter and generate accurate proposal density distribution for the particle filter. Hence, the proposal scheme uses GSPF to track the states of the targets and applies the idea of JPDA directly to the sample sets of multi-target states, and weights of particles are evaluated through the combination of JPDA. The specific implementation steps of JPDA based on GSPF (JPDA/GSPF) are deduced. Trajectory tracking and the root mean square error (RMSE) comparisons are made with JPDA/SIR and JPDA/EKF schemes on simulated data in multi-target passive tracking. Simulation results show that the JPDA/GSPF scheme has better performance than JPDA/SIR and JPDA/EKF scheme in tracking. Furthermore, from the view of particle cost, the JPDA/GSPF introduces higher computation efficiency than JPDA/SIR.

Citation Download Citation

Feng Xue, Zhong Liu, and Zhangsong Shi "Data association and passive tracking for multiple targets based on Gaussian sum particle filter", Proc. SPIE 6357, Sixth International Symposium on Instrumentation and Control Technology: Signal Analysis, Measurement Theory, Photo-Electronic Technology, and Artificial Intelligence, 63570S (24 October 2006); https://doi.org/10.1117/12.716774

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

Members: $17.00

Non-members: $21.00 ADD TO CART

PROCEEDINGS
6 PAGES

DOWNLOAD PAPER SAVE TO MY LIBRARY

GET CITATION

RIGHTS & PERMISSIONS

Get copyright permission Get copyright permission on Copyright Marketplace

KEYWORDS

Particles

Particle filters

Monte Carlo methods

Target detection

Computer simulations

Electronic filtering

Gaussian filters

Show All Keywords

Keywords/Phrases

Search In:

Publication Years