Browse > Article
http://dx.doi.org/10.22156/CS4SMB.2020.10.09.015

Robust Location Estimation based on TDOA and FDOA using Outlier Detection Algorithm  

Yoo, Hogeun (Department of Computer Science and Engineering, Korea University)
Lee, Jaehoon (Department of Computer Science and Engineering, Korea University)
Publication Information
Journal of Convergence for Information Technology / v.10, no.9, 2020 , pp. 15-21 More about this Journal
Abstract
This paper presents the outlier detection algorithm in the estimation method of a source location and velocity based on two-step weighted least-squares method using time difference of arrival(TDOA) and frequency difference of arrival(FDOA) data. Since the accuracy of the estimated location and velocity of a moving source can be reduced by the outliers of TDOA and FDOA data, it is important to detect and remove the outliers. In this paper, the method to find the minimum inlier data and the method to determine whether TDOA and FDOA data are included in inliers or outliers are presented. The results of numerical simulations show that the accuracy of the estimated location and velocity is improved by removing the outliers of TDOA and FDOA data.
Keywords
Time Difference of Arrival Frequency Difference of Arrival; Location Estimation; Velocity Estimation; Data Fusion; Outlier Detection;
Citations & Related Records
연도 인용수 순위
  • Reference
1 E. Olson, J. J. Leonard & Seth Teller. (2006). Robust Range-Only Beacon Localization. IEEE Journal of Oceanic Engineering, 31(4), 949-958. DOI : 10.1109/JOE.2006.880386   DOI
2 C. Luo & J. H. McClellan. (2010). Robust geolocation estimation using adaptive RANSAC algorithm. IEEE International Conference on Acoustics Speech and Signal Processing, 3862-3865. DOI : 10.1109/ICASSP.2010.5495817
3 Y. T. Chan, W. Y. Tsui, H. C. So & P. Ching. (2006). Time-of-arrival based localization under NLOS conditions. IEEE Trans. on Vehicular Technology, 55(1), 17-24. DOI : 10.1109/TVT.2005.861207   DOI
4 F. Gustafsson. (2005). Mobile Positioning Using Wireless Networks. IEEE Signal Processing Magazine, 22(4), 41-53. DOI: 10.1109/MSP.2005.1458284   DOI
5 S. Al-Samahi, Y. Zhang & K. C. Ho. (2020). Elliptic and hyperbolic localization using minimum measurement solutions. Signal Processing 167, Article 107273. DOI : 10.1016/j.sigpro.2019.107273
6 Z. Liu, Y. Zhao, D. Hu & C. Liu. (2016). A Moving Source Localization Method for Distributed Passive Sensor Using TDOA and FDOA Measurements. International Journal of Antennas and Propagation, 2016, Article ID 8625039. DOI : 10.1155/2016/8625039
7 A. E. Spezio. (2002). Electronic warfare systems. IEEE Transactions on Microwave Theory and Techniques, 50(3), 633-644. DOI : 10.1109/22.989948   DOI
8 J. Wang, Z. Qin, Y. Bi, S. Wei & F. Luo. (2018). Target localisation in multistatic radar using BR, TDOA, and AOA measurements. IET Journal of Engineering, 2019(19), 6052-6056. DOI : 10.1049/joe.2019.0128
9 L. Yang, H. Gao, Y. Yang & G. Ru. (2019). Joint Position and Velocity Estimation of a Moving Target in Multistatic Radar by Bistatic Range, TDOA, and Doppler Shifts. International Journal of Antennas and Propagation, 2019, Article ID 4943872. DOI : 10.1155/2019/4943872
10 K. C. Ho & W. Xu. (2004). An Accurate Algebraic Solution for Moving Source Location Using TDOA and FDOA Measurements. IEEE Trans. on Signal Processing, 52(9), 2453-2463. DOI : 10.1109/TSP.2004.831921   DOI