Sensor Selection for Target Tracking in Wireless Sensor Networks With Uncertainty

Cao N., Choi S., MAŞAZADE E., Varshney P. K.

IEEE TRANSACTIONS ON SIGNAL PROCESSING, cilt.64, sa.20, ss.5191-5204, 2016 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 64 Sayı: 20
  • Basım Tarihi: 2016
  • Doi Numarası: 10.1109/tsp.2016.2595500
  • Dergi Adı: IEEE TRANSACTIONS ON SIGNAL PROCESSING
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.5191-5204
  • Anahtar Kelimeler: Fisher information (FI), information fusion, mutual information (MI), multiobjective optimization, sensor selection, Target tracking, wireless sensor networks (WSNs), MULTIOBJECTIVE OPTIMIZATION, STATE ESTIMATORS
  • Marmara Üniversitesi Adresli: Hayır

Özet

In this paper, we propose a multiobjective optimization framework for the sensor selection problem in uncertain Wireless Sensor Networks (WSNs). The uncertainties of the WSNs result in a set of sensor observations with insufficient information about the target. We propose a novel mutual information upper bound (MIUB)-based sensor selection scheme, which has a low computational complexity, same as the Fisher information (FI)-based sensor selection scheme, and gives an estimation performance similar to the mutual information-based sensor selection scheme. Without knowing the number of sensors to be selected a priori, the multiobjective optimization problem (MOP) gives a set of sensor selection strategies that reveal different tradeoffs between two conflicting objectives: minimization of the number of selected sensors and minimization of the gap between the performance metric (MIUB and FI) when all the sensors transmit measurements and when only the selected sensors transmit their measurements based on the sensor selection strategy. Illustrative numerical results that provide valuable insights are presented.