Particle Filtering for Track Before Detect Applications

• Main Authors: Torstensson, Johan, Trieb, Mikael
• Format: Others
• Language: English
• Published: Linköpings universitet, Institutionen för systemteknik 2005
• Subjects: Particle Filter; Target Tracking; Track Before Detect; TBD; Bayesian Estimation; Monte Carlo Methods; Nonlinear Filtering.; Signal processing; Signalbehandling
• Online Access: http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-4046

Integrated tracking and detection, based on unthresholded measurements, also referred to as track before detect (TBD) is a hard nonlinear and non-Gaussian dynamical estimation and detection problem. However, it is a technique that enables the user to track and detect targets that would be extremely hard to track and detect, if possible at all with ''classical'' methods. TBD enables us to be better able to detect and track weak, stealthy or dim targets in noise and clutter and particles filter have shown to be very useful in the implementation of TBD algorithms. This Master's thesis has investigated the use of particle filters on radar measurements, in a TBD approach. The work has been divided into two major problems, a time efficient implementation and new functional features, as estimating the radar cross section (RCS) and the extension of the target. The later is of great importance when the resolution of the radar is such, that specific features of the target can be distinguished. Results will be illustrated by means of realistic examples.