Using Machine Learning and Raytracing Fingerprint to enhance TDoA localization System in Outdoar environment
– the chapters need to be with equations and Figures!!!
A Hybrid technique is proposed to improve the Time Difference of Arrival (TDoA) Localization systems in Non-line of Sight situation. A Ray tracing simulation tool is used to extract the time of arrival difference characteristic from the environment and binding with the TDoA a multilateration sensor scheme to estimate the position of an electromagnetic emitter. The idea was to improve the TDoA sensor performance to overcome multipath imprecision typical in the urban environment, where different rays are sum up at each sensor increasing the error position. The technique proposed uses time Channel Impulse Response estimation and a Ray Tracing propagation tool to build a geographic time difference fingerprint that is used to enhance the performance. A measurement campaign was done to validate the technique and showed an enhancement in the localization precision.
1- B. Y. Shikur and T. Weber:TDOA/AOD/AOA localization in NLOS environments,2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP),2014,6518-6522.
2- I. Guvenc and C. C. Chong, IEEE Communications Surveys Tutorials, A Survey on TOA Based Wireless Localization and NLOS Mitigation Techniques, 2009, Vol 11,3 pp. 107-124.
3- M. P. Wylie and J. Holtzman,Proceedings of ICUPC – 5th International Conference on Universal Personal Communications, The non-line of sight problem in mobile location estimation,1996, vol. 2, pp. 827-831.
4- Yiu-Tong Chan and Wing-Yue Tsui and Hing-Cheung So and Pak-chung Ching, IEEE Transactions on Vehicular Technology, Time-of-arrival based localization under NLOS conditions,2006, vol. 55, 1, pp. 17-24.
5- B. R. Phelan and E. H. Lenzing and R. M. Narayanan, 2012 IEEE 7th Sensor Array and Multichannel Signal Processing Workshop (SAM), Source localization using unique characterizations of multipath propagation in an urban environment, 2012, pp.
6- J. Schmitz and F. Schröder and R. Mathar, 2015 International Symposium on Antennas and Propagation (ISAP), TDOA fingerprinting for localization in non-line-of-sight and multipath environments,2015, pp 1-4.
7- Q. Baoping and S. Gang and J. Zhanrong,2012 4th International Conference on Intelligent Human-Machine Systems and Cybernetics, An Improved TDOA Location Algorithm in LOS Environment, 2012,1,pp. 70-73.
8- R. Heddergott and P. E. Leuthold,IEEE Transactions on Antennas and Propagation, An extension of stochastic radio channel modeling considering propagation environments with clustered multipath components, 2003, vol. 51, 8, pp. 1729-1739
W. J. D. Johnson and T. Weller and X. Gong,WAMICON 2013,Pactive sensors for security applications,2013, pp. 1-4.
S. Al-Jazzar and J. Caffery,Proceedings IEEE 56th Vehicular Technology Conference,ML and Bayesian TOA location estimators for NLOS environments, 2002, vol. 2, pp. 1178-1181.
B. Kwon and Y. Park and Y. s. Park, ICCAS 2010,
Analysis of the GCC-PHAT technique for multiple sources, 2010, pp. 2070-2073.
H. Miao and K. Yu and M. J. Juntti,IEEE Transactions on Vehicular Technology,Positioning for NLOS Propagation: Algorithm Derivations and Cramer-Rao Bound, 2007, vol.56,5,pp. 2568-2580.
J. Yin and Q. Wan and S. Yang and K. C. Ho, IEEE Signal Processing Letters, A Simple and Accurate TDOA-AOA Localization Method Using Two Stations, 2016, Vol 23, 1, pp144-148.
W. C. Li, P. Wei and X. C. Xiao, “TDOA and T2/R radar based target location method and performance analysis,” in IEE Proceedings – Radar, Sonar and Navigation, vol. 152, no. 3, pp. 219-223, 3 June 2005.
Costanzo, S., Di Massa, G., Costanzo, A., Borgia, A., Raffo, A., Viggiani, G., Versace, P.: Software-Defined Radar System for Landslides Monitoring. New Advances in Information Systems and Technologies. 325-331 (2016).