Mixed-mode Implementation of Particle Filters (original) (raw)

Profile image of David AndersonDavid Anderson

2007, 2007 IEEE Pacific Rim Conference on Communications, Computers and Signal Processing

On low-power analog implementation of particle filters for target tracking

Rajbabu Velmurugan

2006 14th European Signal Processing Conference, 2006

We propose a low-power, analog and mixed-mode, implementation of particle filters. Low-power analog implementation of nonlinear functions such as exponential and arctangent functions is done using multiple-input translinear element (MITE) networks. These nonlinear functions are used to calculate the probability densities in the particle filter. A bearings-only tracking problem is simulated to present the proposed low-power implementation of the particle filter algorithm.

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Algorithmic and Architectural Design Methodology for Particle Filters in Hardware

Ankur Srivastava

2005

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Bearings-Only Tracking of Manoeuvring Targets Using Particle Filters

Sanjeev Arulampalam

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Howida Abd El-Halym

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A low-power piecewise linear analog to digital converter for use in particle tracking

Roberto Bonino

IEEE Transactions on Nuclear Science, 1995

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On Tracking Applications using Variable Rate Particle Filters

Sze Pang

2006 IEEE Nonlinear Statistical Signal Processing Workshop, 2006

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Performance of the shifted Rayleigh filter in single-sensor bearings-only tracking

Richard Vinter

2007 10th International Conference on Information Fusion, 2007

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Bearings-only tracking with particle filtering for joint parameter learning and state estimation

Lyudmila S Mihaylova

2012

This paper considers the problem of bearings only tracking of manoeuvring targets. A learning particle filtering algorithm is proposed which can estimate both the unknown target states and unknown model parameters. The algorithm performance is validated and tested over a challenging scenario with abrupt manoeuvres. A comparison of the proposed algorithm with the Interacting Multiple Model (IMM) filter is presented. The learning particle filter has shown accurate estimation results and improved accuracy compared with the ...

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Scalable implementation of particle filter-based visual object tracking on network-on-chip (NoC)

Rajbabu Velmurugan

Journal of Real-Time Image Processing, 2019

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Nonlinear multiple model particle filters algorithm for tracking multiple targets

Hicham Tebbikh

Archives of Control Sciences, 2011

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Nenad Mladenović

Computers & Operations Research, 2013

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2010

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Lenni Yulianti

2012 4th International Conference on Intelligent and Advanced Systems (ICIAS2012), 2012

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2007

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A Survey of Recent Advances in Particle Filters and Remaining Challenges for Multitarget Tracking

Tiancheng Li

Sensors (Basel, Switzerland), 2017

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Target Motion Analysis Using Single Sensor Bearings-Only Measurements

Xuezhi Wang

2009

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Chunlin Ji

2009

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SpringerPlus, 2016

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Electronic EngineeringMathematicsComputer ScienceTarget TrackingMixed ModeLow PowerParticle FilterNetwork SimulatorPower Dissipation