Repository logo
Log in(current)
Repository logoMIT Open ScholarshipDSpace@MIT
  1. Home
  2. MIT Open Access Articles
  3. MIT Open Access Articles
  4. DGICat_Heterogeneous Information Fusion for Multitarget Tracking Using the Sum-product Algorithm

DGICat_Heterogeneous Information Fusion for Multitarget Tracking Using the Sum-product Algorithm

Thumbnail Image
Download
Name

ICASSP2019_V15.pdf

Description
Accepted version
Size

3.24 MB

Format

Adobe PDF

Checksum (MD5)

33c69b81599a0016ab6ee5c771b52583

sword-2019-11-04T15:37:36.original.xml (130 B)
Original SWORD entry document
Author(s)
Win, Moe Z.
Date Issued
May 2019
Journal
IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Citation
Soldi, Giovanni et al. “DGICat_Heterogeneous Information Fusion for Multitarget Tracking Using the Sum-product Algorithm.” Paper presented at the ICASSP 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) (Brighton, United Kingdom, 12-17 May 2019): INSPEC Accession Number: 18777798 © 2019 The Author(s)
Version
Author's final manuscript
Abstract
The sum-product algorithm (SPA) was recently shown to provide a scalable methodology for multitarget tracking (MTT) using multiple sensors. Here, we focus on another advantage of the SPA frame-work, namely, its capacity for Bayesian fusion of heterogeneous data sources and auxiliary information. We develop extensions of the SPA-based multisensor MTT algorithm that integrate data from an auxiliary surveillance system and geographic information about standard target routes. The effectiveness of our approach is demonstrated for a simulated scenario and for a real maritime scenario.
MIT Department
Massachusetts Institute of Technology. Laboratory for Information and Decision Systems
Terms of Use
Creative Commons Attribution-Noncommercial-Share Alike
http://creativecommons.org/licenses/by-nc-sa/4.0/
Persistent DSpace Link
https://hdl.handle.net/1721.1/125705
DOI of Published Version
https://doi.org/10.1109/ICASSP.2019.8683891
Repository logo
PrivacyPermissionsAccessibilityContact us
Repository logo
Notify us about copyright concerns.