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Cascade-Connected ANN Structures for Indoor WLAN Positioning

  • Miloš Borenović
  • Aleksandar Nešković
  • Djuradj Budimir
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5788)

Abstract

Various radio systems can be used to obtain the position information in indoor environments. Due to the ubiquitous presence of WLAN networks, positioning techniques in these environments are the scope of intense research. This paper explores the properties of cascade-connected Artificial Neural Networks (ANNs) structures. Several cascade-connected ANN structures with space partitioning are compared to the single ANN multilayer feedforward structure. The benefits of using cascade-connected ANNs structures are shown and discussed in terms of the size of the environment and subspaces. The optimal cascade-connected ANN structure with space partitioning shows a 41% decrease in median error with respect to the single ANN model.

Keywords

artificial neural network cascade-connected location positioning radio space partitioning WLAN 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Miloš Borenović
    • 1
    • 2
  • Aleksandar Nešković
    • 1
  • Djuradj Budimir
    • 2
  1. 1.School of Electrical EngineeringBelgradeSerbia
  2. 2.Wireless Communications Research Group, School of InformaticsUniversity of WestminsterLondonUnited Kingdom

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