A Parameterized Design Framework for Hardware Implementation of Particle Filters

Abstract

Particle filtering methods provide powerful techniques for solving non-linear state-estimation problems, and are applied to a variety of application areas in signal processing. Because of their vast computational complexity, real-time hardware implementation of particle-filter-based systems is a challenging task. However, many particle filter applications share common characteristics, and the same system design can be reused with appropriate streamlining. To achieve this, a parameterized design framework for particle filters is proposed in this paper. In this framework, parameterization of system features that vary over specific implementations enables reuse of a generic design for a wide range of applications with minimal re-design effort. Using this framework, we explore different design options for implementing two different particle filtering applications on field-programmable gate arrays (FPGAs), and we present associated results on trade-offs between area (FPGA resource requirements) and execution speed.

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Document Details

Document Type
Technical Report
Publication Date
Mar 01, 2008
Accession Number
ADA482034

Entities

People

  • Neal K. Bambha
  • Sankalita Saha
  • Shuvra S. Bhattacharyya

Organizations

  • University of Maryland

Tags

Communities of Interest

  • Advanced Electronics

DTIC Thesaurus Topics

  • Abstracts
  • Algorithms
  • Computational Complexity
  • Computers
  • Electrical Engineering
  • Engineering
  • Field Programmable Gate Arrays
  • Filters
  • Filtration
  • Generators
  • Noise
  • Noise Generators
  • Probability
  • Sequential Monte Carlo Methods
  • Signal Processing
  • Turbines
  • White Noise

Fields of Study

  • Computer science
  • Engineering

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Distributed Systems and Data Platform Development
  • Integrated Circuit Design and Technology.