A Novel Accurate Source Number Estimation Method Based on GBSA-MDL Algorithm

  • Taha Bouras
  • Di He
  • Fei Wen
  • Peilin Liu
  • Wenxian Yu
Conference paper
Part of the Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering book series (LNICST, volume 237)

Abstract

Several classical source number estimation methods have been proposed in the past based on information theoretic criteria such as minimum description length (MDL). However, in most known real applications there is a scenario in which the number of sensors goes to infinity at the same speed as the number of snapshots (general asymptotic case) which yields to a blind performance for the classical MDL and results in an inaccurate source number estimation. Accordingly, in this work, the Galaxy Based Search Algorithm (GBSA) is modified and applied with the MDL criteria in order to optimize and correct the detection of source number under such sample-starving case. Simulation results show that the proposed GBSA-MDL based method gives reliable results compared to several used source number estimation methods.

Keywords

Source number estimation methods Minimum Description Length (MDL) General asymptotic case Optimization Galaxy Based Search Algorithm (GBSA) 

Notes

Acknowledgment

This research work is supported by the Important National Science and Technology Specific Project of China under Grant No. 2016ZX03001022-006, the Shanghai Science and Technology Committee under Grant No. 16DZ1100402, and the National Natural Science Foundation of China under Grant No. 91438113.

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Copyright information

© ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2018

Authors and Affiliations

  1. 1.Shanghai Key Laboratory of Navigation and Location-Based ServicesShanghai Jiao Tong UniversityShanghaiPeople’s Republic of China

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