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Two efficient localization algorithms for multilateration

Published online by Cambridge University Press:  13 July 2009

Mauro Leonardi*
Affiliation:
Tor Vergata University, Via del Politecnico 1, 00131 Rome, Italy. Phone: +39 06 72597417; Fax: +39 06 72597532.
Adolf Mathias
Affiliation:
Deutsche Flugsicherung, Systemhaus, Am DFS-Campus 10, 63225 Langen, Germany. Phone: +49 6103 7074468; Fax: +49 6103 7072595
Gaspare Galati
Affiliation:
Tor Vergata University, Via del Politecnico 1, 00131 Rome, Italy. Phone: +39 06 72597417; Fax: +39 06 72597532.
*
Corresponding author: M. Leonardi Email: leonardi@disp.uniroma2.it

Abstract

Two localization algorithms for multilateration systems are derived and analyzed. Instead of the classical time difference of arrival (TDOA), a direct use of the time of arrival (TOA) is made. The algorithms work for arbitrary spatial dimensions and overdetermined systems. These derivations are tested in a real-case implementation with simulated data (in particular, the multilateration (MLAT) system installed on the Malpensa Airport in Milan was considered for the MLAT simulation and its possible extension to wide area multilateration (WAM) system was considered for WAM trials). The results are also compared with the present-day algorithms performance, mostly based on TDOA.

Keywords

Type
Original Article
Copyright
Copyright © Cambridge University Press and the European Microwave Association 2009

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References

REFERENCES

[1]Shin, D.-H.; Sung, T.-K.: Comparisons of error characteristics between toa and tdoa positioning. IEEE Trans. Aerosp. Electron. Syst., 38 (2002), 307311.CrossRefGoogle Scholar
[2]Schau, H.C.; Robinson, A.Z.: Passive source localization employing spherical surfaces from time-of-arrival differences. IEEE Trans. Acoust. Speech Signal Process., ASSP-35 (1987), 12231225.CrossRefGoogle Scholar
[3]Fang, B.T.: Simple solutions for hyperbolic and related position fixes. IEEE Trans. Aerosp. Electron. Syst., 26 (1990), 748753.CrossRefGoogle Scholar
[4]Smith, J.O.; Abel, J.S.: Closed-form least-squares source location estimation from range–difference measurements. IEEE Trans. Acoust. Speech Signal Process., ASSP-35 (1987), 16611669.CrossRefGoogle Scholar
[5]Torrieri, D.J.: Statistical theory of passive location systems. IEEE Trans. Aerosp. Electron. Sys., AES-20 (1984), 183198.CrossRefGoogle Scholar
[6]Urruela, A.; Riba, J.: Novel closed-form ml position estimator for hyperbolic location, in Proc. IEEE Int. Conf. Acoust, Speech and Signal Processing (ICASSP '04), Vol. 2, 17–21 May 2004, 149–52.Google Scholar
[7]Chan, Y.T.; Ho, K.C.: A simple and efficient estimator for hyperbolic location. IEEE Trans. Signal Process., 42 (1994), 19051915.CrossRefGoogle Scholar
[8]Bancroft, S.: An algebraic solution of the gps equations. IEEE Trans. Aerosp. Electron. Syst., Jan. 1985. 5659.CrossRefGoogle Scholar
[9]Kay, S.M.: Fundamentals of Signal Processing–Estimation Theory, Prentice-Hall, Upper Saddle River. NJ, 1993.Google Scholar
[10]Mathias, A.; Leonardi, M.; Galati, G.: An efficient multilateration algorithm, in Proc. Tyrrhenian Int. Workshop on Digital Communications – Enhanced Surveillance of Aircraft and Vehicles TIWDC/ESAV 2008, 3–5 September 2008, 16.CrossRefGoogle Scholar
[11]Galati, G.; Leonardi, M.; Tosti, M.: Multilateration (local and wide area) as a distributed sensor system: Lower bounds of accuracy, in Proc. European Radar Conference EuRAD 2008, 30–31 October 2008, 196199.Google Scholar