Coherent spatio-temporal sensor fusion on a hybrid multicore processor system

Charlotte Kotas, Eduardo Ponce, Holly Williams, Jacob Barhen

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

We report on the development, implementation, and demonstration of a novel, massively parallel computational scheme for detection of a target radiating a random signal in the presence of noise. This scheme involves coherent spatio-temporal fusion of data streams from multiple sensors, leading to the derivation of LLR detection statistics. Since streaming multicore processors with multi-SIMT architectures open unprecedented opportunities for fast signal processing, our algorithms are implemented on an NVIDIA Tesla C2050 many-core processor. Results achieved to date demonstrate up to two orders of magnitude speedup over a parallel implementation on a conventional quad-core processor, on a per-target-kinematic-hypothesis basis.

Original languageEnglish
Title of host publication15th International Conference on Information Fusion, FUSION 2012
Pages1504-1510
Number of pages7
StatePublished - 2012
Event15th International Conference on Information Fusion, FUSION 2012 - Singapore, Singapore
Duration: Sep 7 2012Sep 12 2012

Publication series

Name15th International Conference on Information Fusion, FUSION 2012

Conference

Conference15th International Conference on Information Fusion, FUSION 2012
Country/TerritorySingapore
CitySingapore
Period09/7/1209/12/12

Keywords

  • CUDA FORTRAN
  • NVIDIA Tesla
  • multicore processors
  • sensor arrays
  • spatio-temporal LLR detection

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