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Parallel Hardware for Sampling Based Nonlinear Filters in FPGAs
Linköping University, Department of Electrical Engineering, Electronics System. Linköping University, The Institute of Technology.
2014 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

Particle filters are a class of sequential Monte-Carlo methods which are used commonly when estimating various unknowns of the time-varying signals presented in real time, especially when dealing with nonlinearity and non-Gaussianity in BOT applications. This thesis work is designed to perform one such estimate involving tracking a person using the road information available from an IR surveillance video. In this thesis, a parallel custom hardware is implemented in Altera cyclone IV E FPGA device utilizing SIRF type of particle filter. This implementation has accounted how the algorithmic aspects of this sampling based filter relate to possibilities and constraints in a hardware implementation. Using 100MHz clock frequency, the synthesised hardware design can process almost 50 Mparticles/s. Thus, this implementation has resulted in tracking the target, which is defined by a 5-dimensional state variable, using the noisy measurements available from the sensor.

Place, publisher, year, edition, pages
2014. , 77 p.
Keyword [en]
Particle filters, Sampling Importance Resampling Filter, Hardware architectures, Bearings-only tracking.
National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering
URN: urn:nbn:se:liu:diva-112926ISRN: LiTH-ISY-EX--14/4821--SEOAI: diva2:774383
Subject / course
Electronics Systems
2014-12-18, Nollstället, B-Huset, Campus Valla., Linköping, 17:12 (English)
Available from: 2014-12-23 Created: 2014-12-22 Last updated: 2015-01-07Bibliographically approved

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Kota Rajasekhar, Rakesh
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