Analysis of condition number and position estimation error for multiangulation position estimation system

A passive wireless positioning system could be used to detect the location of low-level airborne targetssuch as drones or unmanned aircraft systems from the electromagnetic emission detected at spatially deployed ground receiving stations (GRSs). The multiangulation system proposed in this paper makes use of the angle of arrival (AOA) of the transmitted signal from the target to estimate its position through a 2-stage process. The AOA is the positiondependent signal parameter (PDSP) obtained from the target emission in the first stage, and using the PDSP and GRSs, the target location is estimated in the second stage by the angulation algorithm. Noise in the received signal results in AOA estimation error and subsequently error in the position estimation (PE). This paper focuses on the angulation process, which is the second stage of the multiangulation target location estimation process. Analysis is conducted to determine the correlation between the PE error and the condition number of the coefficient matrix of a multiangulationposition estimation system. The results based on Monte Carlo simulations show that both condition number and PE error distribution increase with the target range, where the higher condition number values correlate with higher PE error values appearing around 80◦to 110◦ and 260◦ to 280◦ of both distributions.

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[1] Poisel R. Electronic Warfare Target Location Methods. Boston, MA, USA: Artech House, 2012.
[2] Bagheri M, Sedaaghi MH. A new approach to pulse deinterleaving based on adaptive thresholding. Turkish Journal of Electrical Engineering & Computer Sciences 2017; 25 (5): 3827-3838. doi: 10.3906/elk-1606-415
[3] Ayazgok S, Erdem C, Ozturk MT, Orduyilmaz A, Serin M. Automatic antenna scan type classification for nextgeneration electronic warfare receivers. IET Radar, Sonar & Navigation 2018; 12 (4): 466-474. doi: 10.1049/ietrsn.2017.0354
[4] Lambert G. Electronic Warfare: Rethinking the Importance of Its Role in the Military Operations. Norfolk, VA, USA: Marine Corps, Joint Forces Staff College, National Defense University, 2016.
[5] Boyacı A, Ekti AR, Yarkan S, Aydın MA. Monitoring, surveillance, and management of the electromagnetic spectrum: current issues in electromagnetic spectrum monitoring. Electrica 2018; 18 (1): 100-108. doi: 10.5152/iujeee.2018.1816
[6] ITU Radiocommunication Sector (ITU-R). Handbook on National Spectrum Management, 2015.
[7] Pace PE. Detecting and Classifying Low Probability of Intercept Radar. 2nd ed. Boston, MA, USA: Artech House, 2009.
[8] Poisel RA. Introduction to Communication Electronic Warfare Systems. 2nd ed. Boston, MA, USA: Artech House, 2008.
[9] Sha’ameri AZ, Yaro AS, Amjad FM, Hamdi MN. Performance comparison of emitter locating system for low level airborne targets. Defence S and T Technical Bulletin 2017; 10(3): 199-217.
[10] Hassanhosseini S, Taban MR, Abouei J. Indoor localization of wireless emitter using direct position determination and particle swarm optimization. Turkish Journal of Electrical Engineering & Computer Sciences 2018; 26 (2): 655-665. doi: 10.3906/elk-1706-332
[11] Fard HT, Atashbar M, Norouzi Y, Kashani FH. Multireference TDOA-based source localization. Turkish Journal of Electrical Engineering & Computer Sciences 2013; 21 (Suppl. 1): 1920-1929. doi: 10.3906/elk-1109-46
[12] International Civil Aviation Organisation (ICAO). Guidance Material on Comparison of Surveillance Technologies (GMST), 2007.
[13] Norouzi Y, Kashani ES, Ajorloo A. Angle of arrival-based target localisation with low earth orbit satellite observer. IET Radar, Sonar & Navigation 2016; 10 (7): 1186-1190. doi: 10.1049/iet-rsn.2015.0437
[14] Series S. Comparison of Time-Difference-of-Arrival and Angle-of-Arrival Methods of Signal Geolocation, 2011.
[15] Sha’ameri AZ, Shehu YA, Asuti W. Performance analysis of a minimum configuration multilateration system for airborne emitter position estimation. Defence S and T Technical Bulletin 2015; 8 (1): 27-41
[16] Çeli̇k G, Çelebi H, Partal HP, Zeydan E, Karatepe IA et al. An experimental study of indoor RSS-based RF fingerprinting localization using GSM and Wi-Fi signals. Turkish Journal of Electrical Engineering& Computer Sciences 2017; 25 (4): 2727-2736. doi: 10.3906/elk-1601-94
[17] Werner J, Wang J, Hakkarainen A, Gulati N, Patron D et al. Sectorized antenna-based DoA estimation and localization: Advanced algorithms and measurements. IEEE Journal on Selected Areas in Communications 2015; 33 (11): 2272-2286. doi: 10.1109/JSAC.2015.2430292
[18] Şahin S, Baba A, Sonmez T. Optimal fusion of multiple GNSS signals against spoofing sources. Turkish Journal of Electrical Engineering & Computer Sciences 2017; 25 (4): 3289-3299. doi: 10.3906/elk-1604-123
[19] Boashash B. Time-Frequency Signal Analysis and Processing: A Comprehensive Reference. San Diego, CA, USA: Academic Press, 2015.
[20] Kanaa A, Sha’ameri AZ. A robust parameter estimation of FHSS signals using time–frequency analysis in a noncooperative environment. Physical Communication 2018; 26: 9-20. doi: 10.1016/j.phycom.2017.10.013
[21] Xiao W, Xiao XC, Tai HM. Rank-1 ambiguity DOA estimation of circular array with fewer sensors. In: IEEE 2002 45th Midwest Symposium on Circuits and Systems; Tulsa, OK, USA; 2002. pp. 29-32. doi: 10.1109/MWSCAS.2002.1186962
[22] Flieller A, Larzabal P, Clergeot H. Study of ambiguities in array manifold: A general framework. In: IEEE Proceedings of 8th Workshop on Statistical Signal and Array Processing; New York, NY, USA; 1996. pp. 574- 577. doi: 10.1109/SSAP.1996.534942
[23] Tan KC, Goh SS, Tan EC. A study of the rank-ambiguity issues in direction-of-arrival estimation. IEEE Transactions on Signal Processing 1996; 44 (4): 880-887. doi: 10.1109/78.492541
[24] Yarima SM, Sha’ameri AZ, Yaro AS. Position estimation error and condition number correlative analysis of a multiangulation system. In: 7th International Graduate Conference on Engineering, Science and Humanity; Johor Bahru, Malaysia; 2018. pp. 338-340.
[25] Yan F, Jin M, Qiao X. Low-complexity DOA estimation based on compressed MUSIC and its performance analysis. IEEE Transactions on Signal Processing 2013; 61 (8): 1915-1930. doi: 10.1109/TSP.2013.2243442
[26] Goldsmith A. Wireless Communications. New York, NY, USA: Cambridge University Press, 2005.
[27] Wang C, Qi F, Shi G, Ren J. A linear combination-based weighted least square approach for target localization with noisy range measurements. Signal Processing 2014; 94: 202-211. doi: 10.1016/j.sigpro.2013.06.005
[28] Sand S, Dammann A, Mensing C. Positioning in Wireless Communications Systems. Chichester, UK: John Wiley & Sons, 2014.
[29] Kuçku K. Horizontal dilution of precision-based ultra-wideband positioning technique for indoor environments. Turkish Journal of Electrical Engineering & Computer Sciences 2014; 22 (5): 1307-1322. doi: 10.3906/elk-1301-20
[30] Strang G. Introduction to Linear Algebra, 4th ed. Wellesley, MA, USA: Wellesley-Cambridge Press, 2009.
[31] Hogben L. Handbook of Linear Algebra. Ames, IA, USA: Chapman and Hall/CRC, 2013.
[32] Abdurrazzaq A, Mohd I, Junoh AK, Yahya Z. A hybrid of tropical-singular value decomposition method for salt and pepper noise removal. Turkish Journal of Electrical Engineering & Computer Sciences 2019; 27 (3): 1667-79.
[33] Lay CD. Linear Algebra and Its Application. 3rd ed. Boston, MA, USA: Addison-Wesley Pearson Education Inc., 2012. doi: 10.1136/gut.44.2.e290
[34] Malaysian Communications and Multimedia Commission (MCMC). Use of Frequencies for Unmanned Aircraft Systems, 2015.
[35] SELEX Sistemi Integrati. ADS-B Subsystem: Standard E5010015201SDD, 2014.
[36] Civil Aviation Act 1969. P.U.(A), Civil Aviation Regulation 2016. Attorney General’s Chambers of Malaysia.
[37] Straw RD. The ARRL Antenna Book. 21st ed. Newington, CT, USA: ARRL Inc., 2007.
[38] Datasheet Prolink PHA1010 v100. AP/CPE/Bridge/Repeater.
[39] Yaro AS, Sha’ameri AZ. Effect of path loss propagation model on the position estimation accuracy of a 3-dimensional minimum configuration multilateration system. International Journal of Integrated Engineering 2018; 10 (4): 1-20.
[40] Kamal SM, Adam AA, Ajagun AS. Performance evaluation of correlative interferometry for angle of arrival estimation. Journal of Emerging Trends in Engineering and Applied Sciences 2015; 6 (1): 43-48.