Localization of multiple nodes based on correlated measurements and shrinkage estimation
作者： Naveed Salman , Lyudmila Mihaylova , A. H. Kemp
关键词: Rational quadratic covariance function 、 Algorithm 、 Covariance 、 Covariance intersection 、 Matérn covariance function 、 Invertible matrix 、 Covariance function 、 Mathematical optimization 、 Estimation of covariance matrices 、 Mathematics 、 Covariance matrix
摘要: Accurate covariance matrix estimation has applications in a wide range of disciplines. For many the estimated needs to be positive definite and hence invertible. When number data points is insufficient, sample two fold disadvantages. Firstly, although it unbiased, consists large error. Secondly, not definite. A shrinkage technique been proposed fields finance life sciences estimate that invertible contains relatively small error variance. In this paper, we introduce concept area multiple target localization wireless networks with correlated measurements. localization, use low cost received signal strength (RSS) Unlike most studies, where links between sensor nodes (SNs) targets (TNs) are independent, realistic model these correlated. Optimization location accuracy achieved by weighting each link via matrix. Simulation results show using improves algorithm.
sci-hub.se 参考文章(18)
B. Ottersten, M. Viberg, P. Stoica, A. Nehorai, Exact and Large Sample Maximum Likelihood Techniques for Parameter Estimation and Detection in Array Processing Radar Array Processing. pp. 99- 151 ,(1993) , 10.1007/978-3-642-77347-1_4
Naveed Salman, Mounir Ghogho, Andrew H. Kemp, On the Joint Estimation of the RSS-Based Location and Path-loss Exponent IEEE Wireless Communications Letters. ,vol. 1, pp. 34- 37 ,(2012) , 10.1109/WCL.2012.121411.110059
N. Patwari, J.N. Ash, S. Kyperountas, A.O. Hero, R.L. Moses, N.S. Correal, Locating the nodes: cooperative localization in wireless sensor networks IEEE Signal Processing Magazine. ,vol. 22, pp. 54- 69 ,(2005) , 10.1109/MSP.2005.1458287
Juliane Schäfer, Korbinian Strimmer, A Shrinkage Approach to Large-Scale Covariance Matrix Estimation and Implications for Functional Genomics Statistical Applications in Genetics and Molecular Biology. ,vol. 4, pp. 1- 32 ,(2005) , 10.2202/1544-6115.1175
Naveed Salman, A. H. Kemp, Mounir Ghogho, Low Complexity Joint Estimation of Location and Path-Loss Exponent IEEE Wireless Communications Letters. ,vol. 1, pp. 364- 367 ,(2012) , 10.1109/WCL.2012.12.120210
B.D. Van Veen, K.M. Buckley, Beamforming: a versatile approach to spatial filtering IEEE Assp Magazine. ,vol. 5, pp. 4- 24 ,(1988) , 10.1109/53.665
Lyudmila Mihaylova, Donka Angelova, David Bull, Nishan Canagarajah, Localization of Mobile Nodes in Wireless Networks with Correlated in Time Measurement Noise IEEE Transactions on Mobile Computing. ,vol. 10, pp. 44- 53 ,(2011) , 10.1109/TMC.2010.132
Clarence C.Y. Kwan, Estimation error in the average correlation of security returns and shrinkage estimation of covariance and correlation matrices Finance Research Letters. ,vol. 5, pp. 236- 244 ,(2008) , 10.1016/J.FRL.2008.09.001
H. Hashemi, The indoor radio propagation channel Proceedings of the IEEE. ,vol. 81, pp. 943- 968 ,(1993) , 10.1109/5.231342
N. Patwari, A.O. Hero, M. Perkins, N.S. Correal, R.J. O'Dea, Relative location estimation in wireless sensor networks IEEE Transactions on Signal Processing. ,vol. 51, pp. 2137- 2148 ,(2003) , 10.1109/TSP.2003.814469