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Simulation of Multiplatform Source Localization Using Three Dimensional Time Difference of Arrival with Multipath Exploitation and Clock Bias Among Receivers


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DOI: https://doi.org/10.15866/iremos.v12i6.17966

Abstract


Source localization using Time Difference of Arrival has been a subject of research over the years due to its wide applications in civilian and military sectors. In electronic warfare systems, the source estimation is important for better surveillance and planning of military strategies. Among the various approaches of Time Difference of Arrival, Three Dimensional  Time Difference of Arrival algorithms have drawn much attention as it does not require synchronization between emitter and the base stations and also provides better estimation performance. However, it certainly requires synchronization among the receiving base stations. In this paper an algorithm is proposed for source localization using Three Dimensional Time Difference of Arrival in presence of multipath scenario and clock bias in the receiving base stations.  Most of the existing techniques require range data for obtaining the closed form Time Difference of Arrival solution. The algorithm presented in this paper is based on Ezzat’s closed form solution, which does not depend on range data.  Simulations are carried out and performance is evaluated by placing receivers on ship/land and Unmanned Aerial Vehicle platforms. Standard deviation in estimated Three Dimensional Time Difference of Arrival is measured using cross correlation between the signals and a closed form solution is obtained. Simulations support the theoretical developments in multipath scenario and clock bias.
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Keywords


Clock Bias; Cross-Correlation; Multipath; Source Localization; Time Difference of Arrival

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References


Khan, U. A., Kar, S., & Moura, J. M. (2009). Distributed sensor localization in random environments using minimal number of anchor nodes, IEEE Transactions on Signal Processing, 57(5), 2000-2016.
https://doi.org/10.1109/tsp.2009.2014812

Addesso, P., Marano, S., & Matta, V. (2010). Estimation of target location via likelihood approximation in sensor networks, IEEE Transactions on Signal Processing, 58(3), 1358-1368.
https://doi.org/10.1109/tsp.2009.2036036

Urruela, A., Sala, J., & Riba, J. (2006). Average performance analysis of circular and hyperbolic geolocation. IEEE Transactions on Vehicular Technology, 55(1), 52-66.
https://doi.org/10.1109/tvt.2005.861172

Zhang, Y., Ansari, N., & Su, W. (2015). Multi‐sensor signal fusion‐based modulation classification by using wireless sensor networks. Wireless Communications and Mobile Computing, 15(12), 1621-1632.
https://doi.org/10.1002/wcm.2450

Nishiyama, H., Ngo, T., Ansari, N., & Kato, N. (2012). On minimizing the impact of mobility on topology control in mobile ad hoc networks. IEEE Transactions on Wireless Communications, 11(3), 1158-1166.
https://doi.org/10.1109/twc.2012.010312.110783

Peters, D. J. (2017). A bayesian method for localization by multistatic active sonar. IEEE Journal of Oceanic Engineering, 42(1), 135-142.
https://doi.org/10.1109/joe.2016.2540744

Rui, L., & Ho, K. C. (2015). Efficient closed-form estimators for multistatic sonar localization. IEEE Transactions on Aerospace and Electronic Systems, 51(1), 600-614.
https://doi.org/10.1109/taes.2014.140482

Chen, S., & Ho, K. C. (2013). Achieving asymptotic efficient performance for squared range and squared range difference localizations. IEEE Transactions on Signal Processing, 61(11), 2836-2849.
https://doi.org/10.1109/tsp.2013.2254479

Kay, S., & Vankayalapati, N. (2013). Improvement of TDOA position fixing using the likelihood curvature. IEEE Transactions on Signal Processing, 61(8), 1910-1914.
https://doi.org/10.1109/tsp.2013.2246154

Patwari, N., Ash, J. N., Kyperountas, S., Hero, A. O., Moses, R. L., & Correal, N. S. (2005). Locating the nodes: cooperative localization in wireless sensor networks. IEEE Signal processing magazine, 22(4), 54-69.
https://doi.org/10.1109/msp.2005.1458287

Vaghefi, R. M., Gholami, M. R., Buehrer, R. M., & Strom, E. G. (2013). Cooperative received signal strength-based sensor localization with unknown transmit powers. IEEE Transactions on Signal Processing, 61(6), 1389-1403.
https://doi.org/10.1109/tsp.2012.2232664

Martin, R. K., King, A. S., Pennington, J. R., Thomas, R. W., Lenahan, R., & Lawyer, C. (2012). Modeling and mitigating noise and nuisance parameters in received signal strength positioning. IEEE Transactions on Signal Processing, 60(10), 5451-5463.
https://doi.org/10.1109/tsp.2012.2207118

Kupershtein, E., Wax, M., & Cohen, I. (2013). Single-site emitter localization via multipath fingerprinting. IEEE Transactions on signal processing, 61(1), 10-21.
https://doi.org/10.1109/tsp.2012.2222395

Adamy, D. (2008). EW 103: Tactical battlefield communications electronic warfare. Artech House.

de Sousa, M. N., & Thoma, R. S. (2018, August). Single Sensor RF Emitter Location Using Ray Tracing Multipath Exploitation. In 2018 15th International Symposium on Wireless Communication Systems (ISWCS) (pp. 1-6). IEEE.
https://doi.org/10.1109/iswcs.2018.8491074

Chan, Y. T., & Ho, K. C. (1994). A simple and efficient estimator for hyperbolic location. IEEE Transactions on signal processing, 42(8), 1905-1915.
https://doi.org/10.1109/78.301830

Ho, K. C., & Xu, W. (2004). An accurate algebraic solution for moving source location using TDOA and FDOA measurements. IEEE Transactions on Signal Processing, 52(9), 2453-2463.
https://doi.org/10.1109/tsp.2004.831921

Reza, R., Srivastava, V., Improving Cell Tower Geo-Location Using Quantum Clock Timing, (2018) International Journal on Communications Antenna and Propagation (IRECAP), 8 (4), pp. 340-345.
https://doi.org/10.15866/irecap.v8i4.13528

Sassi, H., Najeh, T., Liouane, N., The Hybrid Technique for Improvement DV-Hop Localization Algorithms, (2016) International Journal on Communications Antenna and Propagation (IRECAP), 6 (2), pp. 96-102.
https://doi.org/10.15866/irecap.v6i2.8448

Higashino, S., Maruyama, Y., Flight Demonstration of Realtime Path Planning of an UAV Using Evolutionary Computation and Rule-Based Hybrid Method, (2018) International Journal on Engineering Applications (IREA), 6 (5), pp. 156-162.
https://doi.org/10.15866/irea.v6i5.16629

Manzoor, M., Maqsood, A., Hasan, A., Quadratic Optimal Control of Aerodynamic Vectored UAV at High Angle of Attack, (2016) International Review of Aerospace Engineering (IREASE), 9 (3), pp. 70-79.
https://doi.org/10.15866/irease.v9i3.8119

Tiemann, J., &Wietfeld, C. (2017, September). Scalable and precise multi-UAV indoor navigation using TDOA-based UWB localization. In 2017 International Conference on Indoor Positioning and Indoor Navigation (IPIN) (pp. 1-7). IEEE.
https://doi.org/10.1109/ipin.2017.8115937

Wang, G., So, A. M. C., & Li, Y. (2016). Robust convex approximation methods for TDOA-based localization under NLOS conditions, IEEE Transactions on Signal processing, 64(13), 3281-3296.
https://doi.org/10.1109/tsp.2016.2539139

Schreiber, R., & Bajer, J. (2016, September). Software defined radio based receiver for TDOA positioning system. In 2016 IEEE/AIAA 35th Digital Avionics Systems Conference (DASC) (pp. 1-5). IEEE.
https://doi.org/10.1109/dasc.2016.7778086

Shi, H., Zhang, H., & Wang, X. (2016). A TDOA technique with super-resolution based on the volume cross-correlation function. IEEE Transactions on Signal Processing, 64(21), 5682-5695.
https://doi.org/10.1109/tsp.2016.2548988

Schreiber, R., & Bajer, J. (2016, September). Software defined radio based receiver for TDOA positioning system. In 2016 IEEE/AIAA 35th Digital Avionics Systems Conference (DASC) (pp. 1-5). IEEE.
https://doi.org/10.1109/dasc.2016.7778086

Qu, X., &Xie, L. (2016). An efficient convex constrained weighted least squares source localization algorithm based on TDOA measurements. Signal Processing, 119, 142-152.
https://doi.org/10.1016/j.sigpro.2015.08.001

Jin, B., Xu, X., & Zhang, T. (2018). Robust time-difference-of-arrival (TDOA) localization using weighted least squares with cone tangent plane constraint. Sensors, 18(3), 778.
https://doi.org/10.3390/s18030778

Noroozi, A., Oveis, A. H., Hosseini, S. M., &Sebt, M. A. (2017). Improved algebraic solution for source localization from TDOA and FDOA measurements. IEEE Wireless Communications Letters, 7(3), 352-355.
https://doi.org/10.1109/lwc.2017.2777995

Compagnoni, M., Canclini, A., Bestagini, P., Antonacci, F., Sarti, A., &Tubaro, S. (2017). Source localization and denoising: a perspective from the TDOA space. Multidimensional Systems and Signal Processing, 28(4), 1283-1308.
https://doi.org/10.1007/s11045-016-0400-9

Tiemann, J., Eckermann, F., &Wietfeld, C. (2016, October). Atlas-an open-source tdoa-based ultra-wideband localization system. In 2016 International Conference on Indoor Positioning and Indoor Navigation (IPIN) (pp. 1-6). IEEE.
https://doi.org/10.1109/ipin.2016.7743707

Du, P., Zhang, S., Chen, C., Alphones, A., &Zhong, W. D. (2018). Demonstration of a low-complexity indoor visible light positioning system using an enhanced TDOA scheme. IEEE Photonics Journal, 10(4), 1-10.
https://doi.org/10.1109/jphot.2018.2841831

Liu, L., & Liu, H. (2016). Joint estimation of DOA and TDOA of multiple reflections in mobile communications. IEEE Access, 4, 3815-3823.
https://doi.org/10.1109/access.2016.2584088

Meng, W., Xie, L., & Xiao, W. (2016). Optimal TDOA sensor-pair placement with uncertainty in source location. IEEE Transactions on Vehicular Technology, 65(11), 9260-9271.
https://doi.org/10.1109/tvt.2016.2516031

Ennasr, O., Xing, G., & Tan, X. (2016, December). Distributed time-difference-of-arrival (TDOA)-based localization of a moving target. In 2016 IEEE 55th Conference on Decision and Control (CDC) (pp. 2652-2658). IEEE.
https://doi.org/10.1109/cdc.2016.7798662

Niitsoo, A., Edelhäuβer, T., &Mutschler, C. (2018, September). Convolutional neural networks for position estimation in tdoa-based locating systems. In 2018 International Conference on Indoor Positioning and Indoor Navigation (IPIN) (pp. 1-8). IEEE.
https://doi.org/10.1109/ipin.2018.8533766

Li, W., Tang, Q., Huang, C., Ren, C., & Li, Y. (2017). A new close form location algorithm with AOA and TDOA for mobile user. Wireless Personal Communications, 97(2), 3061-3080.
https://doi.org/10.1007/s11277-017-4661-x

Wang, Y., &Ho, K. C. (2016). TDOA positioning irrespective of source range. IEEE Transactions on Signal Processing, 65(6), 1447-1460.
https://doi.org/10.1109/tsp.2016.2630030

Le, T. K., & Ono, N. (2016). Closed-form and near closed-form solutions for TDOA-based joint source and sensor localization. IEEE Transactions on Signal Processing, 65(5), 1207-1221.
https://doi.org/10.1109/tsp.2016.2633784

Leugner, S., Pelka, M., &Hellbrück, H. (2016, October). Comparison of wired and wireless synchronization with clock drift compensation suited for U-TDoA localization. In 2016 13th Workshop on Positioning, Navigation and Communications (WPNC) (pp. 1-4). IEEE.
https://doi.org/10.1109/wpnc.2016.7822846

Su, Z., Shao, G., & Liu, H. (2017). Semidefinite programming for NLOS error mitigation in TDOA localization. IEEE Communications Letters, 22(7), 1430-1433.
https://doi.org/10.1109/lcomm.2017.2787739

Dalveren, Y., & Kara, A. (2017, April). Comparative analysis of TDOA-based localization methods in the presence of sensor position errors. In 2017 4th International Conference on Control, Decision and Information Technologies (CoDIT), (pp. 0556-0560). IEEE.
https://doi.org/10.1109/codit.2017.8102652

Shi, H., Zhang, H., & Wang, X. (2016). A TDOA Technique with Super-Resolution Based on the Volume Cross-Correlation Function. IEEE Trans. Signal Processing, 64(21), 5682-5695.
https://doi.org/10.1109/tsp.2016.2548988

Bakhoum, E. G. (2006). Closed-form solution of hyperbolic geolocation equations. IEEE Transactions on Aerospace and Electronic Systems, 42(4).
https://doi.org/10.1109/taes.2006.314580

Chen, J., Zhao, Y., Zhao, C., & Zhao, Y. (2018, June). Improved Two-Step Weighted Least Squares Algorithm for TDOA-Based Source Localization. In 2018 19th International Radar Symposium (IRS) (pp. 1-6). IEEE.
https://doi.org/10.23919/irs.2018.8448149

Wang, Y., & Ho, K. C. (2013). TDOA source localization in the presence of synchronization clock bias and sensor position errors. IEEE Transactions on Signal Processing, 61(18), 4532-4544.
https://doi.org/10.1109/tsp.2013.2271750

Zhong, X., Tay, W. P., Leng, M., Razul, S. G., & See, C. M. S. (2016, July). Tdoa-fdoa based multiple target detection and tracking in the presence of measurement errors and biases. In 2016 IEEE 17th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC), (pp. 1-6). IEEE.
https://doi.org/10.1109/spawc.2016.7536786

Watson, W. D. (2017, April). 3D active and passive geolocation and tracking of Unmanned Aerial Systems. In 2017 IEEE International Symposium on Technologies for Homeland Security (HST), (pp. 1-6). IEEE.


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