Survey on the performance of source localization algorithms

José Manuel Fresno, Guillermo Robles, Juan Manuel Martínez-Tarifa, Brian G. Stewart

Research output: Contribution to journalArticle

21 Citations (Scopus)
27 Downloads (Pure)


The localization of emitters using an array of sensors or antennas is a prevalent issue approached in several applications. There exist different techniques to source localization which can be classified into multilateration, received signal strength (RSS) and proximity methods. The performance of multilateration techniques relies on measured time variables: the time of flight (ToF) of the emission from the emitter to the sensor, the time differences of arrival (TDoA) of the emission between sensors and the pseudo time of flight (pToF) of the emission to the sensors. The multilateration algorithms presented and compared in this paper can be classified as iterative and non-iterative methods. Both standard least squares (SLS) and hyperbolic least squares (HLS) are iterative and based on Newton-Raphson to solve the non-linear equation system. The metaheuristic technique particle swarm optimization (PSO) used for source localisation is also studied. This optimization technique estimates the source position as the optimum of an objective function based on HLS and is also iterative in nature. Three non-iterative algorithms, namely the hyperbolic positioning algorithms (HPA), maximum likelihood estimator (MLE) and Bancroft algorithm, are also presented. A non-iterative combined algorithm, MLE-HLS, based on MLE and HLS is further proposed in this paper. The performance of all algorithms is analyzed and compared in terms of accuracy in the localization of the position of the emitter and in terms of computational time. The analysis is also undertaken with three different sensor layouts since the positions of the sensors affect in the localization; several source positions are also evaluated to make the comparison more robust. The analysis is carried out using theoretical time differences as well as including errors due to the effect of digital sampling of the time variables. It is shown that the most balanced algorithm, yielding better results than the other algorithms in terms of accuracy and short computational time is the combined MLE-HLS algorithm.
Original languageEnglish
Article number2666
Number of pages25
Issue number11
Publication statusPublished - 18 Nov 2017


  • source Localization
  • emitter localization
  • standard least squares
  • hyperbolic least squares
  • hyperbolic positioning
  • maximum likelihood estimator
  • Bancroft
  • particle swarm optimization
  • combined algorithm

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  • Research Output

    • 21 Citations
    • 2 Conference contribution book
    • 1 Article

    A combined algorithm approach for PD location estimation using RF antennas

    Fresno, J. M., Robles, G., Martinez-Tarifa, J. M. & Stewart, B. G., 18 Aug 2017, 2017 IEEE Electrical Insulation Conference (EIC). Piscataway, NJ: IEEE

    Research output: Chapter in Book/Report/Conference proceedingConference contribution book

    Open Access
  • 4 Citations (Scopus)
    48 Downloads (Pure)

    Quantification of the performance of iterative and non-iterative computational methods of locating partial discharges using RF measurement techniques

    El Mountassir, O., Stewart, B. G., Reid, A. J. & McMeekin, S. G., 28 Feb 2017, In : Electric Power Systems Research. 143, p. 110–120 11 p.

    Research output: Contribution to journalArticle

    Open Access
  • 9 Citations (Scopus)
    17 Downloads (Pure)

    The influence of antenna positioning errors on the radio-frequency localization of partial discharge sources

    Fresno, J. M., Robles, G., Stewart, B. G. & Martínez-Tarifa, J. M., 14 Nov 2016, Proceedings of the 3rd International Electronic Conference on Sensors and Applications. Messervey, T. (ed.). MDPI AG, Vol. 3. 7 p. E003. (Sciforum Electronic Conference Series; vol. 3).

    Research output: Chapter in Book/Report/Conference proceedingConference contribution book

    Open Access
  • 84 Downloads (Pure)

    Cite this

    Fresno, J. M., Robles, G., Martínez-Tarifa, J. M., & Stewart, B. G. (2017). Survey on the performance of source localization algorithms. Sensors, 17(11), [2666].