Evaluation of Data Association and Fusion13; Algorithms for Tracking in the Presence of13; Measurement Loss

Naidu, VPS and Girija, G and Raol, JR (2003) Evaluation of Data Association and Fusion13; Algorithms for Tracking in the Presence of13; Measurement Loss. Project Report. National Aerospace Laboratories, Bangalore, NAL.

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Abstract

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 neighbour 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.

Item Type: Monograph (Project Report)
Additional Information: The work was presented at AIAA conference on13; Guidance, Navigation and Control, in Austin, USA13; in August 2003
Uncontrolled Keywords: Data Fusion, Tracking performance,13; Multi sensor multi target scenario
Subjects: AERONAUTICS > Aircraft Stability and Control
Depositing User: Users 3 not found.
Date Deposited: 24 Jan 2005
Last Modified: 24 May 2010 04:09
URI: http://nal-ir.nal.res.in/id/eprint/586

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