Optimal Periodic Sensor Scheduling in Networks of Dynamical Systems

Liu S., Fardad M., MAŞAZADE E., Varshney P. K.

IEEE TRANSACTIONS ON SIGNAL PROCESSING, cilt.62, sa.12, ss.3055-3068, 2014 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 62 Sayı: 12
  • Basım Tarihi: 2014
  • Doi Numarası: 10.1109/tsp.2014.2320455
  • Dergi Adı: IEEE TRANSACTIONS ON SIGNAL PROCESSING
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.3055-3068
  • Anahtar Kelimeler: Alternating direction method of multipliers, dynamical systems, optimization, sensor networks, sensor scheduling, sparsity, state estimation, TARGET TRACKING, SELECTION
  • Marmara Üniversitesi Adresli: Hayır

Özet

We consider the problem of finding optimal time-periodic sensor schedules for estimating the state of discrete-time dynamical systems. We assume that multiple sensors have been deployed and that the sensors are subject to resource constraints, which limits the number of times each can be activated over one period of the periodic schedule. We seek an algorithm that strikes a balance between estimation accuracy and total sensor activations over one period. We make a correspondence between active sensors and the nonzero columns of the estimator gain. We formulate an optimization problem in which we minimize the trace of the error covariance with respect to the estimator gain while simultaneously penalizing the number of nonzero columns of the estimator gain. This optimization problem is combinatorial in nature, and we employ the alternating direction method of multipliers (ADMM) to find its locally optimal solutions. Numerical results and comparisons with other sensor scheduling algorithms in the literature are provided to illustrate the effectiveness of our proposed method.