Enhancing positioning accuracy of GPS/INS system during GPS outages utilizing artificial neural network

Kaygisiz B. H., Erkmen A. M., Erkmen I.

NEURAL PROCESSING LETTERS, cilt.25, sa.3, ss.171-186, 2007 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 25 Sayı: 3
  • Basım Tarihi: 2007
  • Doi Numarası: 10.1007/s11063-007-9036-y
  • Dergi Adı: NEURAL PROCESSING LETTERS
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.171-186
  • Anahtar Kelimeler: inertial navigation, global positioning system, strapdown, backpropagation neural network, Kalman filter, SENSITIVITY ANALYSIS
  • Orta Doğu Teknik Üniversitesi Adresli: Evet

Özet

Integrated global positioning system and inertial navigation system (GPS/INS) have been extensively employed for navigation purposes. However, low-grade GPS/INS systems generate erroneous navigation solutions in the absence of GPS signals and drift very fast. We propose in this paper a novel method to integrate a low-grade GPS/INS with an artificial neural network (ANN) structure. Our method is based on updating the INS in a Kalman filter structure using ANN during GPS outages. This study focuses on the design, implementation and integration of such an ANN employing an optimum multilayer perceptron (MLP) structure with relevant number of layers/perceptrons and an appropriate learning. As a result, a land test is conducted with the proposed ANN + GPS/INS system and we here provide the system performance with the land trials.