The Set IMMJPDA filter for multitarget tracking

Daniel Svensson; David F. Crouse; Lennart Svensson; Marco Guerriero; Peter Willett

doi:10.1117/12.886937

5 May 2011 The Set IMMJPDA filter for multitarget tracking

Daniel Svensson, David F. Crouse, Lennart Svensson, Marco Guerriero, Peter Willett

Author Affiliations +

Proceedings Volume 8050, Signal Processing, Sensor Fusion, and Target Recognition XX; 80500O (2011) https://doi.org/10.1117/12.886937
Event: SPIE Defense, Security, and Sensing, 2011, Orlando, Florida, United States

Abstract

The Set JPDA (SJPDA) filter is a recently developed multi-target tracking filter that utilizes the relation between the density of a random finite set and the ordinary density of a state vector to improve on the Joint Probabilistic Data Association (JPDA) filter. One advantage to the filter is the improved accuracy of the Gaussian approximations of the JPDA, which results in avoidance of track coalescence. Another advantage is an improved estimation accuracy in terms of a measure which disregards target identity. In this paper we extend the filter to also consider multiple motion models. As a basis for the extension we use the Interacting Multiple Model (IMM) algorithm. We derive three alternative filters that we jointly refer to as Set IMMJPDA (SIMMJPDA). They are based on two alternative descriptions of the IMMJPDA filter. In the paper, we also present simulation results for a two-target tracking scenario, which show improved tracking performance for the Set IMMJPDA filter when evaluated with a measure that disregards target identity.

Citation Download Citation

Daniel Svensson, David F. Crouse, Lennart Svensson, Marco Guerriero, and Peter Willett "The Set IMMJPDA filter for multitarget tracking", Proc. SPIE 8050, Signal Processing, Sensor Fusion, and Target Recognition XX, 80500O (5 May 2011); https://doi.org/10.1117/12.886937

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