COPELABS - Artigos de Revistas Internacionais com Arbitragem Científica

URI permanente para esta coleção:

http://hdl.handle.net/10437/10958

Navegar

Percorrer COPELABS - Artigos de Revistas Internacionais com Arbitragem Científica por autor "Dinis, Rui"

A mostrar 1 - 2 de 2
  • Item
    Algorithms for estimating the location of remote nodes using Smartphones
    (Institute of Electrical and Electronics Engineers Inc., 2019) Pedro, Dario; Tomic, Slavisa; Bernardo, Luís; Beko, Marko; Oliveira, Rodolfo; Dinis, Rui; Pinto, Paulo; Amaral, Pedro; COPELABS - Cognitive and People-centric Computing
    Locating the position of a remote node on a wireless network is becoming more relevant, as we move forward in the Internet of things and in autonomous vehicles. This paper proposes a new system to implement the location of remote nodes. A new prototype Android application has been developed to collect real measurements and to study the performance of several smartphone's sensors and location algorithms, including an innovative one, based on the second order cone programming (SOCP) relaxation. The application collects theWiFi access points information and the terminal location. An internal odometry module developed for the prototype is used when Android's service is unavailable. This paper compares the performance of existing location estimators given in closed form, an existing SOCP one, and the new SOCP location estimator proposed, which has reduced complexity. An algorithm to merge measurements from non-identical terminals is also proposed. Cooperative and terminal stand-alone operations are compared, showing a higher performance for SOCP-based ones, that are capable of estimating the path loss exponent and the transmission power. The heterogeneous terminals were also used in the tests. Our results show that the accurate positioning of static remote entities can be achieved using a single smartphone. On the other hand, the accurate real-time positioning of the mobile terminal is provided when three or more scattered terminal nodes cooperate sharing the samples taken synchronously.
  • Item
    Estimating directional data from Network Topology for improving tracking performance
    (Multidisciplinary Digital Publishing Institute (MDPI), 2019) Tomic, Slavisa; Beko, Marko; Dinis, Rui; Montezuma, Paulo; COPELABS - Cognitive and People-centric Computing
    This work proposes a novel approach for tracking a moving target in non-line-of-sight (NLOS) environments based on range estimates extracted from received signal strength (RSS) and time of arrival (TOA) measurements. By exploiting the known architecture of reference points to act as an improper antenna array and the range estimates, angle of arrival (AOA) of the signal emitted by the target is first estimated at each reference point. We then show how to take advantage of these angle estimates to convert the problem into a more convenient, polar space, where a linearization of the measurement models is easily achieved. The derived linear model serves as the main building block on top of which prior knowledge acquired during the movement of the target is incorporated by adapting a Kalman filter (KF). The performance of the proposed approach was assessed through computer simulations, which confirmed its effectiveness in combating the negative effect of NLOS bias and superiority in comparison with its naive counterpart, which does not take prior knowledge into consideration.