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Optimisation of receiver arrays with heuristic algorithms for estimating the transmitter position via arrival time differences

Meltem Temizkan, Oğuzhan Çakır

Abstract


The location of a source emitting electromagnetic, seismic, or acoustic waves can be determined using synchronised receivers placed at geometrically distinct locations. Since the signal emitted from the source reaches the synchronised receivers at different times, a time difference of arrival (TDOA) occurs. Using the time differences formed at the receiver side, position lines are defined, and the source is located at the centre of these position lines. The error in location determination with TDOA depends on the transmitter-receiver geometry and the variance of the TDOA estimation error. When location determination is performed with a well-optimised receiver array for the same target point and TDOA estimation error variance, positioning performance increases significantly. In this study, the receiver array orientation angle optimisation has been performed using particle swarm optimisation (PSO) and krill swarm optimisation (KSO). In the proposed method, the Cramer-Rao lower bound (CRLB) is used as the fitness function for optimising the equiangular circular receiver array in the KSO and PSO algorithms, resulting in a significant reduction in the squared positioning error. Furthermore, the KSO and PSO methods have been compared with each other in terms of convergence speed and with CRLB in terms of positioning accuracy.


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References


C. Tu, X. Cui, G. Liu, S. Zhao, M. Lu, “Parameterized TDOA: TDOA estimation for mobile target localisation in a time-division broadcast positioning system,” IEEE Internet of Things Journal, 12(13), pp. 24131-24147, 2025.

J. Naganawa, Y. Kosuge, J. Kitaori, H. Tajima, T. Koga, “Demonstration of aircraft localization by TDOA AOA and barometric altitude at two sites,” IEICE Communications Express, 14(6), pp. 246-249, 2025.

M. Sadeghi, F. Behnia, R. Amiri, “Optimal geometry analysis for TDOA-based localization under communication constraints,” IEEE Transactions on Aerospace and Electronic Systems, 57(5), pp. 3096-3106, 2021.

M. Temizkan, B. M. Tüzüner, O. Çakır, “Optimization of two-dimensional receiver array for positioning based on time of arrival differences,” in 7. International Congress of Scientific Research, Ankara, pp. 387-398, March 2020,

F. Evennou, F. Marx, S. Nacivet, “An experimental TDOA UWB location system for NLOS environments,” Vehicular Technology, 62(1), pp. 420-423, 2005.

C. Kang, H. Lee, C. Oh, “NLOS signal detection algorithm for TDOA method in wireless sensor network,” Advanced Communication Technology, 11(1), pp. 901-904, 2009.

O. Cakir, I. Kaya, A. Yazgan, Ö. Cakir, E. Tugcu, “Emitter location finding using particle swarm optimisation,” Radioengineering, 23(1), pp. 252–258, 2014.

O. Cakir, I. Kaya, A. Yazgan, Ö. Cakir, “Dynamic orientation of receiver array using particle swarm optimisation,” Electronics Letters, 49(21), pp. 1313– 1315, 2013.

S. Ting, G. Yong, “TDOA estimation of dual satellites interference localization based on blind separation,” Journal of Systems Engineering and Electronics, 30(4), pp. 696-702, 2019.

W. A., Gardner, C.M. Spooner “Spooner comparison of autocorrelation and cross correlation methods for signal selective TDOA estimation,” IEEE Transactions on Signal Processing, 40(10), pp. 2606-2608, 1992.

X. Wang, C. Liu, “Three-station TDOA localization algorithm for fixed ellipsoidal height targets,” IEEE Signal Processing Letters, 32(1), pp. 2893-2897, 2025.

X. Zeng, D. Deng, H. Yang, Z. Yang, L. Yang, Z. Wu, “Hybrid DOA–TDOA method for impact localization on thin-walled structures using sensor clusters,” IEEE Sensors Journal, 25(4), pp. 6659-6672, 2025.

J. Velasco, D. Pizarro, J. Macias-Guarasa, A. Asaei, “TDOA matrices, algebraic properties and their application to robust denoising with missing data,” IEEE Transactions on Signal Processing, 64(20), pp. 5242-5254, 2016.

H. J. Kim, Y. Xie, H. Yang, C. Lee, T. L. Song, “An efficient indoor target tracking algorithm using TDOA measurements with applications to ultra-wideband systems,” IEEE Access, 7(1), pp. 91435-91445, 2019.

G. C. Carter, “Variance bounds for passively locating an acoustic source with a symmetric line array,” Journal of the Acoustic Society of America, 62(4), pp. 922-926, 1977.

J. Abel, “Optimal sensor placement for passive source localization,” in International Conference on Acoustics, Speech and Signal Processing, California, pp. 2927 – 2930, April 1990.

B. Yang, J. Scheuing, “Cramer-Rao bound and optimum sensor array for source localization from time differences of arrival,” in International Conference on Acoustics, Speech and Signal Processing, Pennsylvania, pp. 961–964, March 2005.

B. Yang, J. Scheuing, “A theoretical analysis of 2D sensor arrays for TDOA-based localization,” in International Conference on Acoustics, Speech and Signal Processing, Toulouse, pp. 901–904. May 2006.

B. Yang, “Different sensor placement strategies for TDOA-based localization,” International Conference on Acoustics, Speech and Signal Processing, Hawaii, pp. 1093–96, April 2007.

K. C. Ho, L. M. Vicente, “Sensor allocation for source localization with decoupled range and bearing estimation,” IEEE Transactions on Signal Processing, 56(12), pp. 5773–5789. 2008.

K. Shadi, H. Dehghani, I. Gholampour, “Well-conditioned sensor placement for range-only localization,” in International Conference on New Technologies Mobility and Security, Paris, pp. 1–5, February 2011.

C. Kreucher, “Optimal sensor placement for a constellation of multistatic narrowband pixelated sensors,” IEEE Transactions on Systems Man and Cybernetics Part C Applications and Reviews, 42(6), pp. 1374-1383, 2012.

W. Meng, L. Xie, W. Xiao, “Optimal sensor pairing for TDOA-based source localization and tracking in sensor networks,” in International Conference on Information Fusion, Singapore, pp. 1897–1902, July 2012.

Y. Liang, Y. Jia, J. Du, J. Zhang, “Simultaneous scan-based emitter passive localization and receiver trajectory optimization,” in Annual Conference on Digital Object Identifier, Maui, pp. 788-793, December 2012.

S. Woźniak, K. Kowalczyk, “Passive joint localization and synchronization of distributed microphone arrays,” IEEE Signal Processing Letters, 26(2), pp. 292-296, 2019.

Q. He, M. Gao, K.F.C. Yiu, S. Norholm, “Nordholm distributed microphone array localization problem via SDP-SOCP method,” IEEE/ACM Transactions on Audio Speech and Language Processing, 31(1), pp. 3579-3588, 2023.

J. S. Hu, C. M. Tsai, C. Y. Chan, Y. J. Chang, “Geometrical arrangement of microphone array for accuracy enhancement in sound source localization,” in 8th Asian Control Conference, Kaohsiung, Taiwan, pp. 299-304, 2011.

S. H. Naghavi, Y. Norouzi, “TDOA sensor array optimization using digital elevation model,” Iranian Conference on Electrical Engineering, Tehran, Iran, pp. 1757-1762, 2017.

O. Jean, A. J. Weiss, “Passive localization and synchronization using arbitrary signals,” IEEE Transactions on Signal Processing, 8(15), pp. 2143–2150, 2017.

L. Rui, K. C. Ho, “Elliptic localization performance study and optimum receiver placement,” IEEE Transactions on Signal Processing, 62(18), pp. 4673–4688, 2017.

Y. T. Chan, K. C. Ho, “A simple and efficient estimator for hyperbolic location,” IEEE Transactions on Signal Processing, 42(8) pp. 1905–1915, 2017.

J. Kennedy, R. Eberhart, “Particle swarm optimization,” in IEEE International Conference on Neural Networks, Perth, pp. 1942-1948, December 1995,

J. H. Holland, Adaptation in natural and artificial systems, First Edition, London, University of Michigan Press, 1975.

R. Storn, K. Price, “Differential evolution a simple and efficient heuristic for global optimization over continuous spaces,” Journal of Global Optimization, 11(1), pp.341-59, 1997.

J. Sun, B. Feng, W.B. Xu, “Particle swarm optimization with particles having quantum behavior,” in Proceedings of Congress on Evolutionary Computation, USA, pp. 325–33, June 2004.

J. Sun, W.B. Xu, B. Feng, “A global search strategy of quantum-behaved particle swarm optimization,” in IEEE Conference on Cybernetics and Intelligent Systems, Singapore, pp. 111–116. December 2004.

M. Clerc, “The swarm and the queen towards a deterministic and adaptive particle swarm optimization, IEEE Congress on Evolutionary Computation, Washington, pp. 1951-57, July 1999.

A. Carlisle, G. Dozier, “Adapting particle swarm optimization to dynamic environments,” International Conference on Artificial Intelligence, pp. 429–434. January 2000.

A. Stacey, M. Jancic, I. Grundy, “Particle swarm optimization with mutation,” in IEEE Congress on Evolutionary Computation, Canberra, pp. 1425–1430. December 2003.

X. Jie, X. Deyun, “New metropolis coefficients of particle swarm optimization,” in Chinese Control and Decision Conference, Yantai, pp. 3518–3521, July 2008.

S. Kirkpatrick, C. Gelatt, M. Vecci, “Optimization by simulated annealing,” Science, 220(1), pp. 671–680, 1983.

J. Kennedy, R. Mendes, “Population structure and particle swarm performance,” in Proceedings of the 2002 Congress on Evolutionary Computation, Honolulu, pp. 1671–1676. May 2002.

J. Kennedy, “Small worlds and mega-minds effects of neighbourhood topology on particle swarm performance,” in Proceedings of the IEEE Congress on Evolutionary Computation, Washington, 1931–1938, July 1999.

J. Kennedy, R. Mendes, “Population structure and particle swarm,” in Proceedings of the IEEE Congress on Evolutionary Computation, Honolulu, pp. 1671–1676, May 2002.




URN: https://sloi.org/urn:sl:tjoee102337



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