CSIR Central

EVALUATION OF DATA ASSOCIATION AND FUSION ALGORITHMS FOR TRACKING IN THE PRESENCE OF MEASUREMENT LOSS

IR@NAL: CSIR-National Aerospace Laboratories, Bangalore

View Archive Info
 
 
Field Value
 
Title EVALUATION OF DATA ASSOCIATION AND FUSION ALGORITHMS FOR TRACKING IN THE PRESENCE OF MEASUREMENT LOSS
 
Creator Naidu, VPS
Girija, G
Raol, JR
 
Subject Aircraft Communication & Navigation
Avionics & Aircraft Instrumentation
Communications and Radar
 
Description Tracking in multi sensor multi target (MSMT) scenario is a complex problem due to the uncertainties in the origin of observations. Solution to this problem requires appropriate gating and data association procedures to associate measurements with targets. A PC MATLAB program based on track-oriented approach is evaluated which uses nearest neighbor Kalman filter (NNKF) and probabilistic data association filter (PDAF) for tracking multiple targets from data of multiple sensors. For track-to-track fusion, state vector fusion philosophy is employed. The tracking performance in the presence of simulated track loss and recovery as well as in clutter is evaluated. During data loss PDAF performed better than NNKF. In the presence of mild clutter and sparse target scenarios, the NNKF and PDAF give similar performance.
 
Publisher NAL
 
Type Proj.Doc/Technical Report
NonPeerReviewed
 
Format application/pdf
 
Identifier http://nal-ir.nal.res.in/8531/1/PDFC0315.pdf
Naidu, VPS and Girija, G and Raol, JR EVALUATION OF DATA ASSOCIATION AND FUSION ALGORITHMS FOR TRACKING IN THE PRESENCE OF MEASUREMENT LOSS. Project Report. NAL.
 
Relation http://nal-ir.nal.res.in/8531/