Abstract
In this paper, we propose an extended recursive Cramér-Rao lower bound (ER-CRLB) method as a fundamental tool to analyze the performance of wireless indoor localization systems. According to the non-parametric estimation method, the Fisher information matrix of the ER-CRLB is divided into two parts: the state matrix and the auxiliary matrix, which builds a general framework to consider all the possible factors that may influence the estimation performance. Based on this idea, ER-CRLB can fully model the estimation process in the complicated indoor environment, e.g., the sequential position state propagation, target-anchor geometry effect, the NLOS identification, and the related prior information, which are demonstrated in the comprehensive simulations.
Y. Zhao—This work was supported by the China National Basic Research Program (973 Program, No. 2015CB352400), National Nature Science Foundation of China (Grand No. 61501443, U1401258), Science and Technology Planning Project of Guangdong Province (2015B010129011), and the Research Program of Shenzhen (JSGG20150512145714248).
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References
Arulampalam, M., Maskell, S., Gordon, N., Clapp, T.: A tutorial on particle filters for online nonlinear/non-gaussian bayesian tracking. IEEE Trans. Signal Process. 50(2), 174–188 (2002)
Axel, K.: Location-Based Services: Fundamentals and Operation. Wiely, Chichester (2005)
Hillebrandt, T., Will, H., Kyas, M.: Quantitative and spatial evaluation of distance-based localization algorithms. In: Krisp, J.M. (ed.) Progress in Location-Based Services. LNGC, pp. 173–194. Springer, Heidelberg (2013)
Horn, R.A., Johnson, C.R.: Matrix analysis. Cambridge University Press, New York (2012)
Mao, G., Fidan, B., Anderson, B.: Wireless sensor network localization techniques. Comput. Netw. 51(10), 2529–2553 (2007)
Qi, Y.: Wireless Geolocation in a Non-Line-Of-Sight Environment. Ph.D. thesis, Princeton University (2003)
Shen, Y., Win, M.Z.: Fundamental limits of wideband localization part i: a general framework. IEEE Trans. Inf. Theor. 56(10), 4956–4980 (2010)
Tichavsky, P., Muravchik, C., Nehorai, A.: Posterior cramer-rao bounds for discrete-time nonlinear filtering. IEEE Trans. Signal Process. 46(5), 1386–1396 (1998)
Tseng, P.H., Feng, K.T.: Geometry-assisted localization algorithms for wireless networks. IEEE Trans. Mobile Comput. 12(4), 774–789 (2013)
Yang, Y., Zhao, Y., Kyas, M.: A non-parametric modeling of time-of-flight ranging error for indoor network localization. In: 2013 IEEE Global Communications Conference (GLOBECOM), pp. 189–194. IEEE (2013)
Zhao, Y., Yang, Y., Kyas, M.: 2d geometrical performance for localization algorithms from 3d perspective. In: 2013 International Conference on Indoor Positioning and Indoor Navigation (IPIN), pp. 1–10, October 2013
Zuo, L., Niu, R., Varshney, P.K.: Conditional posterior cramér-rao lower bounds for nonlinear sequential bayesian estimation. IEEE Trans. Signal Process. 59(1), 1–14 (2011)
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Zhao, Y., Fan, X., Xu, CZ. (2016). Performance Analysis for High Dimensional Non-parametric Estimation in Complicated Indoor Localization. In: Yang, Q., Yu, W., Challal, Y. (eds) Wireless Algorithms, Systems, and Applications. WASA 2016. Lecture Notes in Computer Science(), vol 9798. Springer, Cham. https://doi.org/10.1007/978-3-319-42836-9_27
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DOI: https://doi.org/10.1007/978-3-319-42836-9_27
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