Source Localization using TDOA Based on Improved Snake Optimizer (original) (raw)

References

  1. A. Beck, P. Stoica, J. Li, Exact and approximate solutions of source localization problems. IEEE Trans. Signal Process. 56(5), 1770–1778 (2008). https://doi.org/10.1109/TSP.2007.909342
    Article MathSciNet Google Scholar
  2. L.A. Caceres Najarro, I. Song, K. Kim, Differential evolution with opposition and redirection for source localization using rss measurements in wireless sensor networks. IEEE Tran. Autom. Sci. Eng. 17(4), 1736–1747 (2020). https://doi.org/10.1109/TASE.2020.2975287
    Article Google Scholar
  3. B.K. Chalise, Y.D. Zhang, M.G. Amin, B. Himed, Target localization in a multi-static passive radar system through convex optimization. Signal Process. 102, 207–215 (2014). https://doi.org/10.1016/j.sigpro.2014.02.023
    Article Google Scholar
  4. Y.T. Chan, K.C. Ho, A simple and efficient estimator for hyperbolic location. IEEE Trans. Signal Process. 42(8), 1905–1915 (1994). https://doi.org/10.1109/78.301830
    Article Google Scholar
  5. Y.T. Chan, H.Y.C. Hang, P. Ching, Exact and approximate maximum likelihood localization algorithms. IEEE Trans. Veh. Technol. 55(1), 10–16 (2006). https://doi.org/10.1109/TVT.2005.861162
    Article Google Scholar
  6. T. Chen, M. Wang, X. Huang, Q. Xie, TDOA-AOA localization based on improved Salp swarm algorithm, in 2018 14th IEEE International Conference on Signal Processing (ICSP) (2018), pp. 108–112. https://doi.org/10.1109/ICSP.2018.8652322
  7. G.R. Chen, T. Ueta, Yet another chaotic attractor. Int J Bifurc Chaos 9, 1465–1466 (1999). https://doi.org/10.1142/S0218127499001024
    Article MathSciNet Google Scholar
  8. A. Gabbrielli, J. Bordoy, W.X. Xiong et al., RAILS: 3-D real-time angle of arrival ultrasonic indoor localization system. IEEE Trans. Instrum. Meas. 72, 1–15 (2023). https://doi.org/10.1109/TIM.2022.3222485
    Article Google Scholar
  9. Z. Han, C.S. Leung, H.C. So, A.G. Constantinides, Augmented Lagrange programming neural network for localization using time-difference-of-arrival measurements. IEEE Trans. Neural Netw. Learn. Syst. 29(8), 3879–3884 (2018). https://doi.org/10.1109/TNNLS.2017.2731325
    Article MathSciNet Google Scholar
  10. F.A. Hashim, A.G. Hussien, Snake optimizer: a novel meta-heuristic optimization algorithm. Knowl Based Syst. 242, 108320 (2022). https://doi.org/10.1016/j.knosys.2022.108320
    Article Google Scholar
  11. O. Jean, A.J. Weiss, Geolocation by direction of arrival using arrays with unknown orientation. IEEE Trans. Signal Process. 62(12), 3135–3142 (2014). https://doi.org/10.1109/TSP.2014.2321109
    Article MathSciNet Google Scholar
  12. Y.X. Li, G.R. Chen, W.K.S. Tang, Controlling a unified chaotic system to hyperchaotic. IEEE Trans. Circuits Syst. II Express Br. 52(4), 204–207 (2005). https://doi.org/10.1109/TCSII.2004.842413
    Article Google Scholar
  13. J. Liang, Y. Chen, H.C. So, Y. Jing, Circular/hyperbolic/elliptic localization via Euclidean norm elimination. Signal Process. 148, 102–113 (2018). https://doi.org/10.1016/j.sigpro.2018.02.006
    Article Google Scholar
  14. L. Lin, H.C. So, F.K.W. Chan, Y.T. Chan, K.C. Ho, A new constrained weighted least squares algorithm for TDOA-based localization. Signal Process. 93(11), 2872–2878 (2013). https://doi.org/10.1016/j.sigpro.2013.04.004
    Article Google Scholar
  15. Y. Liu, F. Guo, L. Yang, W. Jiang, An improved algebraic solution for TDOA localization with sensor position errors. IEEE Commun. Lett. 19(12), 2218–2221 (2015). https://doi.org/10.1109/LCOMM.2015.2486769
    Article Google Scholar
  16. Z. Liu, R. Wang, Y. Zhao, Noise-resistant estimation algorithm for TDOA, FDOA and differential doppler rate in passive sensing. Circuits Syst. Signal Process. 39, 4155–4173 (2020). https://doi.org/10.1007/s00034-020-01364-3
    Article Google Scholar
  17. E.N. Lorenz, Deterministic nonperiodic flow. J. Atmos. Sci. 20(2), 130–141 (1963). https://doi.org/10.1007/978-0-387-21830-4_2
    Article MathSciNet Google Scholar
  18. X.N. Lu, K.C. Ho, Taylor-series technique for moving source localization in the presence of sensor location errors, in 2006 IEEE International Symposium on Circuits and Systems (2007), p. 4. https://doi.org/10.1109/ISCAS.2006.1692775
  19. X. Ma, T. Ballal, H. Chen, O. Aldayel, T.Y. Al-Naffouri, A maximum-likelihood TDOA localization algorithm using difference-of-convex programming. IEEE Signal Process. Lett. 28, 309–313 (2021). https://doi.org/10.1109/LSP.2021.3051836
    Article Google Scholar
  20. A. Noroozi, A.H. Oveis, S.M. Hosseini, M.A. Sebt, Improved algebraic solution for source localization from TDOA and FDOA measurements. IEEE Wirel. Commun. Lett. 7(3), 352–355 (2018). https://doi.org/10.1109/LWC.2017.2777995
    Article Google Scholar
  21. K.C. Pine, S. Pine, M. Cheney, The geometry of far-field passive source localization With TDOA and FDOA. IEEE Trans. Aerosp. Electron. Syst. 57(6), 3782–3790 (2021). https://doi.org/10.1109/TAES.2021.3087804
    Article Google Scholar
  22. X.M. Qu, L.H. Xie, W.R. Tan, Iterative constrained weighted least squares source localization using TDOA and FDOA measurements. IEEE Trans. Signal Process. 65(15), 3990–4003 (2017). https://doi.org/10.1109/TSP.2017.2703667
    Article MathSciNet Google Scholar
  23. F. Quo, K.C. Ho, A quadratic constraint solution method for TDOA and FDOA localization, in 2011 IEEE International Conference on Acoustics, Speech and Signal Processing (2011), pp. 2588–2591. https://doi.org/10.1109/ICASSP.2011.5947014
  24. J. Smith, J. Abel, Closed-form least-squares source location estimation from range-difference measurements. IEEE Trans. Acoust, Speech, Signal Process. 35(12), 1661–1669 (1987). https://doi.org/10.1109/TASSP.1987.1165089
    Article Google Scholar
  25. F. Solis, R. Wets, Minimization by random search techniques. Math. Oper. Res. 6(1), 19–30 (1981). https://doi.org/10.1287/moor.6.1.19
    Article MathSciNet Google Scholar
  26. L. Sun, Z.Q. Huang, W.M. Fu, The research of image encryption algorithm based on hyper-chaotic chen system integration with time delay. Sci. Tech. Eng. 13, 10523–10530 (2013). https://api.semanticscholar.org/CorpusID:123601773
  27. J.M. Tang, X. Zhou, W. Zhang, C.Y. Wang, H.B. Wang, Multipoint location of TDOA based on improved genetic ant colony algorithm. Commun. Technol. 51(7), 1575–1584 (2018)
    Google Scholar
  28. Z.C. Tian, C.F. Liu, Passive Locating Technology (National Defence Industry Press, Beijing, 2015), pp.264–265
    Google Scholar
  29. H.W. Wei, R. Peng, Q. Wan, Z.X. Chen, S.F. Ye, Multidimensional scaling analysis for passive moving target localization with TDOA and FDOA measurements. IEEE Trans. Signal Process. 58(3), 1677–1688 (2010). https://doi.org/10.1109/TSP.2009.2037666
    Article MathSciNet Google Scholar
  30. D.H. Wolpert, W.G. Macready, No free lunch theorems for optimization. IEEE Trans. Evol. Comput. 1(1), 67–82 (1997). https://doi.org/10.1109/4235.585893
    Article Google Scholar
  31. W.X. Xiong, H.C. So, Outlier-robust passive elliptic target localization. IEEE Geosci. Remote Sens. Lett. 20, 1–5 (2023). https://doi.org/10.1109/LGRS.2023.3270929
    Article Google Scholar
  32. W.X. Xiong, S. Christian, H.C. So et al., TDOA-based localization with NLOS mitigation via robust model transformation and neurodynamic optimization. Signal Process. 178, 107774 (2021). https://doi.org/10.1016/j.sigpro.2020.107774
    Article Google Scholar
  33. W.X. Xiong, C. Schindelhauer, H.C. So, Globally optimized TDOA high-frequency source localization based on quasi-parabolic ionosphere modeling and collaborative gradient projection. IEEE Trans. Aerosp. Electron. Syst. 59(1), 580–590 (2023). https://doi.org/10.1109/TAES.2022.3185971
    Article Google Scholar
  34. E. Xu, Z. Ding, S. Dasgupta, Source localization in wireless sensor networks from signal time-of-arrival measurements. IEEE Trans. Signal Process. 59(6), 2887–2897 (2011). https://doi.org/10.1109/TSP.2011.2116012
    Article MathSciNet Google Scholar
  35. Z. Xu, H. Li, K. Yang, L.P. Lin, A robust constrained total least squares algorithm for three-dimensional target localization with hybrid TDOA-AOA measurements. Circuits Syst Signal Process. 42, 3412–3436 (2023). https://doi.org/10.1007/s00034-022-02270-6
    Article Google Scholar
  36. K. Yang, G. Wang, Z. Luo, Efficient convex relaxation methods for robust target localization by a sensor network using time differences of arrivals. IEEE Trans. Signal Process. 57(7), 2775–2784 (2009). https://doi.org/10.1109/TSP.2009.2016891
    Article MathSciNet Google Scholar
  37. G.H. Zhu, D.Z. Feng, Y. Zhou, H.X. Zhao, A linear-correction based on time difference of arrival localization algorithm. J. Electron. Inf. Technol. 37, 85–90 (2015). https://doi.org/10.11999/JEIT140313
    Article Google Scholar

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