Energy-aware sensor selection in field reconstruction

Sijia Liu, Aditya Vempaty, Makan Fardad, Engin Masazade, Pramod Kumar Varshney

Research output: Contribution to journalArticle

23 Citations (Scopus)

Abstract

In this letter, a new sparsity-promoting penalty function is introduced for sensor selection problems in field reconstruction, which has the property of avoiding scenarios where the same sensors are successively selected. Using a reweighted ℓ1 relaxation of the ℓ0 norm, the sensor selection problem is reformulated as a convex quadratic program. In order to handle large-scale problems, we also present two fast algorithms: accelerated proximal gradient method and alternating direction method of multipliers. Numerical results are provided to demonstrate the effectiveness of our approaches.

Original languageEnglish (US)
Article number6867304
Pages (from-to)1476-1480
Number of pages5
JournalIEEE Signal Processing Letters
Volume21
Issue number12
DOIs
StatePublished - 2014

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Sensor
Sensors
Energy
Method of multipliers
Proximal Methods
Alternating Direction Method
Convex Program
Quadratic Program
Gradient methods
Gradient Method
Large-scale Problems
Penalty Function
Sparsity
Fast Algorithm
Norm
Numerical Results
Scenarios
Demonstrate

Keywords

  • Alternating direction method of multipliers
  • convex relaxation
  • field reconstruction
  • proximal gradient method
  • sensor selection
  • sparsity

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Signal Processing
  • Applied Mathematics

Cite this

Energy-aware sensor selection in field reconstruction. / Liu, Sijia; Vempaty, Aditya; Fardad, Makan; Masazade, Engin; Varshney, Pramod Kumar.

In: IEEE Signal Processing Letters, Vol. 21, No. 12, 6867304, 2014, p. 1476-1480.

Research output: Contribution to journalArticle

Liu, Sijia ; Vempaty, Aditya ; Fardad, Makan ; Masazade, Engin ; Varshney, Pramod Kumar. / Energy-aware sensor selection in field reconstruction. In: IEEE Signal Processing Letters. 2014 ; Vol. 21, No. 12. pp. 1476-1480.
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