Abstract
The three-dimensional geolocation of a radio frequency RF emitting source is commonly determined using two RF sensors. Most researchers work on one of three emitter-sensors motion platforms. These are: (a) stationary sensors - stationary emitter, (b) moving sensors - stationary emitter, (c) stationary sensors - moving emitter. The present work aims to investigate a fourth scenario of moving RF sensors and emitter to determine the emitter location. A proposed algorithm is designed to deal with this case as well as the three formal ones. We consider the straight line and maneuvering motions of the emitter and sensors. The presented algorithm uses a hybrid situation of angle of arrival (AOA) and time of arrival (TOA) of the emitter RF signal to estimate the 3D moving emitter geolocation. We test the algorithm for long and short distances and it is found be reliable. The algorithm is also tested for different values of AOAs, and TOAs with different standard deviations. Compared with the previous works, relatively small resulting emitter position error has been detected. A MATLAB programming environment is utilized to build up the algorithm.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Okello, N.: Emitter geolocation with multiple UAVs. In: 9th International Conference on Information Fusion, Florence (2006)
Scerri, P., Glinton, R., Owens, S., Scerri, D., Sycara, K.: Geolocation of RF Emitters by Many UAVs. Carnegie Mellon University, Pittsburch (2007)
Kaune, R., Musicki, D., Koch, W.: On Passive emitter tracking in sensor networks, sensor fusion and its applications. In: Ciza, T., (Ed.) (2010). ISBN: 978- 953-307-101-5
Fisher, G.W.: Robust Geolocation Techniques for Multiple Receiver Systems. MSc. Thesis, Department of Electrical and Computer Engineering, Graduate Faculty, Baylor University, USA (2011)
Bamberger, R.J., Moore, J.G., Goonasekeram, R.P., Scheidt, D.H.: Autonomous geolocation of RF emitters using small, unmanned platforms. Johns Hopkins APL Technical Digest 32(3), 636–646 (2013)
Thoresen, T., Moen, J., Engebråten, S.A., Kristiansen, L.B., Nordmoen, J.H., Olafsen, H.K., Gullbekk, H., Hoelster, I.T., Bakstad, L.H.: Distribuerte COTS UAS for PDOA WiFi geolokalisering med Android smarttelefoner. Technical report, Forsvarets forskningsinstitutt, FFI-rapport 14/00958 (2014)
Bailey, E.J.: Single Platform Geolocation of Radio Frequency Emitters. MSc. thesis, Air Force Institute of Technology, Ohio, USA (2015)
Kim, Y.-H., Kim, D.-G., Kim, H.-N.: Two-step estimator for moving-emitter geolocation using time difference of arrival/frequency-difference of arrival measurements. IET Radar Sonar Navig. 9(7), 881–87 (2015). The Institution of Engineering and Technology, UK
Li, X., Deng, Z.D., Rauchenstein, L.T., Carlson, T.J.: Source localization algorithms and applications using time of arrival and time difference of arrival measurements. Rev. Sci. Instrum. 87, 041502, 1–12 (2016)
Liu, Z., Zhao, Y., Hu, D., Liu, C.: A moving source localization method for distributed passive sensor using TDOA and FDOA measurements. Int. J. Antennas Propag., 8625039, 12 (2016). Accessed 18 May 2018. https://doi.org/10.1155/2016/8625039
Boukerche, A., Oliveira, H.A., Nakamura, E.F., Loureiro, A.A.: Localization systems for wireless sensor networks. IEEE Wirel. Commun. 14, 6–12 (2007)
Alfandi, O., Bochem, A., Bulert, K., Maier, A., Hogrefe, D.: Received signal strength indication for movement detection. In: Eighth International Conference on Mobile Computing and Ubiquitous Networking (ICMU), Hakodate, Japan, pp. 82–83 (2015)
Fowler, M.L., Hu, X.: Signal models for TDOA/FDOA estimation. IEEE Trans. Aerosp. Electron. Syst. 44(4), 1543–1550 (2008)
Mušicki, D., Koch, W.: Geolocation using TDOA and FDOA measurements. In: 11th International Conference on Information Fusion, pp. 1987–1994, Germany (2008)
Lee, B.H., Chan, Y.T., Chan, F., Du, H., Dilkes, F.A.: Doppler frequency geolocation of uncooperative radars. In: MILCOM 2007 - IEEE Military Communications Conference, USA (2007)
Lee, J., Liu, J.: Passive emitter AOA determination and geolocation using a digital interferometer. In: RTO SET Symposium on Passive and LPI Radio Frequency Sensor, Poland, p. 23–25 (2001)
Du, H.-J., Lee, J.P.Y.: Simulation of Multi-Platform Geolocation using a Hybrid TDOA/AOA Method, Technical Report, Ministry of Defence R&D Canada, Ottawa (2004)
Høye, G.: Analyses of the geolocation accuracy that can be obtained from shipborne sensors by use of time difference of arrival (TDOA), scanphase, and angle of arrival (AOA) measurements. Forsvarets forsknings institutt Norwegian Defence Research Establishment (FFI), Norway (2010)
Tufan, B., Tuncer, T.E.: Combination of emitter localization techniques with angle, frequency and time difference of arrival. In: IEEE 21st Signal Processing and Communications Applications Conference (SIU), Turkey (2013)
International Telecommunication Union, Radio Sector Comparison of time difference-of-arrival and angle-of-arrival methods of signal geolocation, Report ITU-R SM.2211-2, Switzerland (2018)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Switzerland AG
About this paper
Cite this paper
Rahouma, K.H., Mostafa, A.S.A. (2020). 3D Geolocation Approach for Moving RF Emitting Source Using Two Moving RF Sensors. In: Hassanien, A., Azar, A., Gaber, T., Bhatnagar, R., F. Tolba, M. (eds) The International Conference on Advanced Machine Learning Technologies and Applications (AMLTA2019). AMLTA 2019. Advances in Intelligent Systems and Computing, vol 921. Springer, Cham. https://doi.org/10.1007/978-3-030-14118-9_73
Download citation
DOI: https://doi.org/10.1007/978-3-030-14118-9_73
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-14117-2
Online ISBN: 978-3-030-14118-9
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)