Localization of ground emitters using LEO satellites in LER scenario based on combined TDOA-FDOA method

Document Type : Original Article

Authors

1 Master's degree, Imam Hossein University (AS), Tehran, Iran

2 Assistant Professor, Imam Hossein University (AS), Tehran, Iran

3 Associate Professor Imam Hossein University (AS), Tehran, Iran

Abstract

Knowing the location of the emitter is essential in almost all electronic warfare systems. This article studies and investigates methods of emitter localization using satellites. In emitter localization based on combined TDOA-FDOA measurements, Linear Least Squares (LLS) estimation is widely used due to its computational efficiency. Two-stage weighted least squares and constrained weighted least squares are common LLS methods, but their performance decreases significantly under Large Equal Radius (LER) scenarios, which is a common geometry in satellite-based localization. In this scenario, conventional localization methods often face ill-conditioned matrix problems. In addition, these methods suffer from problems such as high complexity or complex root selection strategy. In the LER scenario, the equations of the combined TDOA-FDOA measurements are linearized using a geometric approach. Linear equations provide the possibility of using weighted least squares estimation to obtain a closed-form solution for the emitter location. This technique does not require initial guess, auxiliary variable, two-stage estimation and complex root selection strategies. In this method, the estimation bias caused by LER modeling is significant in the absence of measurement noise and in weak LER conditions; which it can be compensated and by establishing a strong LER condition, an unbiased estimator can be obtained, ultimately. By analyzing and evaluating the performance of the proposed estimator theoretically, it is shown that the covariance matrix of the emitter location error reaches the Cramér-Rao Lower Bound (CRLB) in strong LER conditions. The simulation results show that the proposed algorithm reaches CRLB in a wider range of measurement noise range with lower run time and complexity compared to other conventional methods.

Keywords

Main Subjects


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[1]          Y. U. Huagang, G. Huang, G. Jun, and W. U. Xinhui, “Approximate maximum likelihood algorithm for moving source localization using TDOA and FDOA measurements,” Chinese J. Aeronaut., vol. 25, no. 4, pp. 593–597, 2012, doi: 10.1016/S1000-9361(11)60423-8.
[2]          J. Smith and J. Abel, “Closed-form least-squares source location estimation from range-difference measurements,” IEEE Trans. Acoust., vol. 35, no. 12, pp.1661–1669, 1987, doi: 10.1109/TASSP.1987.1165089.
[3]          W. Hao, S. Wei-min, and G. Hong, “A novel Taylor series method for source and receiver localization using TDOA and FDOA measurements with uncertain receiver positions,” in Proceedings of 2011 IEEE CIE International Conference on Radar, IEEE, pp. 1037–1040, 2011, doi: 10.1109/CIE-Radar.2011.6159729.
[4]          K. C. Ho and Y. T. Chan, “Geolocation of a known altitude object from TDOA and FDOA measurements,” IEEE Trans. Aerosp. Electron. Syst., vol. 33, no. 3, pp. 770–783, 1997, doi: 10.1109/7.599239.
[5]          L. Lin, H.-C. So, F. K. W. Chan, Y. T. Chan, and K. C. Ho, “A new constrained weighted least squares algorithm for TDOA-based localization,” Signal Processing, vol. 93, no. 11, pp. 2872–2878, 2013, doi: 10.1016/j.sigpro.2013.04.004.
[6]          X. Qu, L. Xie, and W. Tan, “Iterative constrained weighted least squares source localization using TDOA and FDOA measurements,” IEEE Trans. Signal Process., vol. 65, no. 15, pp. 3990–4003, 2017, doi: 10.1109/TSP.2017.2703667.
[7]          K. C. Ho and W. Xu, “An accurate algebraic solution for moving source location using TDOA and FDOA measurements,” IEEE Trans. Signal Process., vol. 52, no. 9, pp. 2453–2463, 2004, doi: 10.1109/TSP.2004.831921.
[8]          A. Noroozi, A. H. Oveis, S. M. Hosseini, and M. A. Sebt, “Improved algebraic solution for source localization from TDOA and FDOA measurements,” IEEE Wirel. Commun. Lett., vol. 7, no. 3, pp. 352–355, 2017, doi: 10.1109/LWC.2017.2777995
[9]          K. C. Ho, X. Lu, and L. Kovavisaruch, “Source localization using TDOA and FDOA measurements in the presence of receiver location errors: Analysis and solution,” IEEE Trans. Signal Process., vol. 55, no. 2, pp. 684–696, 2007, doi: 10.1109/TSP.2006.885744
[10]        E. Choi and D. A. Cicci, “Analysis of GPS static positioning problems,” Appl. Math. Comput., vol. 140, no. 1, pp. 37–51, 2003, doi: 10.1016/S0096-3003(02)00193-5.
[11]        L. A. Romero, J. Mason, and D. M. Day, “The large equal radius conditions and time of arrival geolocation algorithms,” SIAM J. Sci. Comput., vol. 31, no. 1, pp. 254–272, 2008, doi: 10.1137/070699020.
[12]        L. A. Romero and J. Mason, “Evaluation of direct and iterative methods for overdetermined systems of TOA geolocation equations,” IEEE Trans. Aerosp. Electron. Syst., vol. 47, no. 2, pp. 1213–1229, 2011, doi: 10.1109/TAES.2011.5751253.
[13]        S. Li and K. C. Ho, “Accurate and Effective Localization of an Object in Large Equal Radius Scenario,” IEEE Trans. Wirel. Commun., vol. 15, no. 12, pp. 8273–8285, 2016, doi: 10.1109/TWC.2016.2613534.
[14]        X. Li, F. Guo, L. Yang, and K. C. Ho, “Complexity-Reduced Solution for TDOA Source Localization in Large Equal Radius Scenario with Sensor Position Errors,” in 2018 26th European Signal Processing Conference (EUSIPCO), IEEE, pp. 361–365, 2018, doi: 10.23919/EUSIPCO.2018.8553125.
[15]        J. Li et al., “Joint TDOA, FDOA and PDOA localization approaches and performance analysis,” Remote Sens., vol. 15, no. 4, p. 915, 2023, doi: 10.3390/rs15040915.
[16]        X. Zhang, F. Wang, H. Li, and B. Himed, “Covariance-free TDOA/FDOA-based moving target localization for multi-static radar,” in 2020 IEEE International Radar Conference (RADAR), IEEE, pp. 901–905, 2020, doi: 10.1109/RADAR42522.2020.9114799.
 
Volume 12, Issue 2 - Serial Number 46
number 46, summer 2024
September 2024
  • Receive Date: 10 April 2024
  • Revise Date: 25 May 2024
  • Accept Date: 29 July 2024
  • Publish Date: 22 August 2024