A New Method for Geolocating of Radiation Sources Based on Evolutionary Computation of TDOA Equations

Document Type: Research Paper

Authors

1 Department of Electrical Engineering and Information Technology, Iranian Research Organization for Science and Technology, Iran.

2 Department of Electrical, Biomedical and Mechatronics Engineering, Qazvin Branch, Islamic Azad University, Qazvin, Iran.

Abstract

In this article a new method is introduced for geolocating of signal emitters which is based on evolutionary computation (EC) concept. In the proposed method two well-known members of EC techniques including Bees Algorithm (BA) and Genetic Algorithm (GA), are utilized to estimate the positions of emitters by optimizing the hyperbola equations which have been resulted from Time Difference of Arrival (TDOA) of their radiated signals. To show the effectiveness of the EC concept in positioning the simulation is carried for linear and nonlinear moving emitters in presence of several amounts of noise. Then obtained results are compared with Maximum Likelihood (ML) estimator as one of the most common approaches among traditional methods. The results showed better performance of the EC family compared to ML in such way that they estimate the position of emitters even up to 33% and 30% more accurate than ML in presence of 5 and 10 percent of noise respectively. Furthermore the comparison among the examined methods belong to EC family shows that BA leads to the accuracy of 3 to 12 percent better than GA in estimating positions of radiation sources.

Graphical Abstract

A New Method for Geolocating of Radiation Sources Based on Evolutionary Computation of TDOA Equations

Keywords


[1] M. A. Spirito and A. G. Mattioli, “On the hyperbolic positioning of GSM mobile stations,” in Proc. 1998 international Symposium on Signals, Systems and Electronics, Conf, Pisa, Italy, 1998.

 

[2] K. C. Ho and Y. T. Chan, “An asymptotically unbiased estimator for bearings-only and doppler-bearing target motion analysis,” IEEE Trans. Signal Processing, vol. 54, no. 3, pp. 809-822, Mar. 2006.

[3] G. C. Carter, “Time delay estimation for passive sonar signal processing,” IEEE Trans. Acoust., Speech, Signal Processing, vol. ASSP-29, no. 3, pp. 462–470, Jun. 1981.

[4] Y. T. Chan and J. J. Towers, “Passive localization from Dopplershifted frequency measurements,” IEEE Trans. Signal Processing, vol. 40, no. 10, pp. 2594-2598, Oct. 1992.

[5] Y. T. Chan and K. C. Ho, “A simple and efficient estimator for hyperbolic location,” IEEE Trans. Signal Processing, vol. 42, no. 8, pp. 1905-1915, Aug. 1994.

[6] F. Evennou, F. Marx, and S. Nacivet, “An experimental TDOA UWB location system for NLOS environments,” in Proc. IEEE 62 nd Vehicular Technology Conference-Fall, Conf., pp. 420-423, Dallas, TX, USA, 2005.

[7] R. Poisel, “Electronic warfare target location methods,” Boston:Artech House, 2005, p. 272.

[8] H. C. Schau and A. Z. Robinson, “Passive source localization employing intersecting spherical surfaces from time-of-arrival differences,” IEEE Trans. Acoust., Speech, Signal Processing, vol. ASSP-35, pp.1223-1225, Aug. 1987.

[9] S. Fischer, H. Koorapaty, E. Larsson, and A. Kangas, “System performance evaluation of mobile positioning methods,” in Proc. 1999 IEEE Vehicular Technology, Conf., Houston, TX, USA, 1999.

[10] M. A. Spirito, “Further results on GSM mobile station location,” IEEE Trans. Electronics Letters, vol. 35, no. 11, pp. 867-869, May. 1999.

[11] D. Koks, “Numerical Calculations for Passive Geolocation,” Defence Science and Technology Organisation, Edinburgh, SA, Tech. Rep. AR-013-779, Jan. 2007.

[12] K. W. K. Lui, J. Zheng, and H. C. So, “Particle swarm optimization for time-difference-of-arrival based localization,” In Proc. 2007 of European Signal Processing Conference, Conf., p. 414-417, Poznan, Poland, 2007.

[13] G. Mellen, M. Pachter, and J. Raquet, “Closed-form solution for determining emitter location using time difference of arrival measurements,” IEEE Trans. Aerospace and Electronic Systems, vol. 39, no. 3, pp. 1056-1058, Jul. 2003.

[14] B. T. Fang, “Simple solutions for hyperbolic and related position fixes,” IEEE Trans. Aerosp. Electron. Syst., vol. 26, pp. 748-753, Sept. 1990.

[15] B. Friedlander, “A passive localization algorithm and its accuracy analysis,” IEEE J. Ocean. Eng., vol. OE-12, pp. 234-245, Jan. 1987.

[16] O. Smith and J. S. Abel, “Closed-form least-squares source location estimation from range-difference measurements,” IEEE Trans. Acoust., Speech, Signal Processing, vol. ASSP-35, pp.1661-1669, Dec. 1987.

[17] J.S. Abel and J. O. Smith, “The spherical interpolation method for closed-form passive source localization using range difference measurements,” in Proc. ICASSP-87, pp. 471-474, Dallas, TX, USA, 1987.

[18] W. H. Foy, “Position-location solutions by Taylor-series estimation,” IEEE Trans. Aerosp. Electron. Syst., vol. AES-12, no. 2, pp. 187-194, Mar. 1976.

[19] D. J. Torrieri, “Statistical theory of passive location systems,” IEEE Trans. Aerosp. Electron. Syst., vol. AES-20, pp. 183-198, Mar. 1984.

[20] R. C. Eberhart and Y. H. Shi, “Particle swarm optimization: developments, applications and resources,” in Proc. 2001 IEEE Congress on Evolutionary Computation, pp. 81-86, Seoul, South Korea, 2001.

[21] E. Bonabeau, M. Dorigo, and G. Theraulaz, “Swarm intelligence: from natural to artificial systems,” New York: Oxford University Press, 1999, pp. 320.

[22] S. Camazine, J. Deneubourg, N. R. Franks, J. Sneyd, G. Theraula, and E. Bonabeau, “Self-Organization in Biological Systems,” Princeton: Princeton University Press, 2003, pp. 560.

[23] G. Bilchev and I. C. Parmee, “The ant colony metaphor for searching continuous design spaces,” AISB Workshop Sheffield on Evolutionary Computing, 1995, pp. 25-39.

[24] T. D. Seeley, “The wisdom of the hive: the social physiology of honey bee colonies,” Massachusetts: Harvard University Press, Cambridge, 1996, p. 318.

[25] B. Yuce, M. S. Packianather, E. Mastrocinque, D. T. Pham, and A. Lambiase, “Honey bees inspired optimization method: The bees algorithm,” Insects, vol. 4, pp. 646-662, 2013.

[26] P. Curkovic and B. Jerbic, “Honey-bees optimization algorithm applied to path planning problem,” Int. J. Simul. Model, vol. 6, pp. 154-164, 2007.