The Community for Technology Leaders
RSS Icon
Issue No.12 - Dec. (2012 vol.11)
pp: 1983-1993
Chen Feng , University of Toronto, Toronto and Beijing Jiaotong University, Beijing
Wain Sy Anthea Au , University of Toronto, Toronto
Shahrokh Valaee , University of Toronto, Toronto
Zhenhui Tan , Beijing Jiaotong University, Beijing
The recent growing interest for indoor Location-Based Services (LBSs) has created a need for more accurate and real-time indoor positioning solutions. The sparse nature of location finding makes the theory of Compressive Sensing (CS) desirable for accurate indoor positioning using Received Signal Strength (RSS) from Wireless Local Area Network (WLAN) Access Points (APs). We propose an accurate RSS-based indoor positioning system using the theory of compressive sensing, which is a method to recover sparse signals from a small number of noisy measurements by solving an \ell_1-minimization problem. Our location estimator consists of a coarse localizer, where the RSS is compared to a number of clusters to detect in which cluster the node is located, followed by a fine localization step, using the theory of compressive sensing, to further refine the location estimation. We have investigated different coarse localization schemes and AP selection approaches to increase the accuracy. We also show that the CS theory can be used to reconstruct the RSS radio map from measurements at only a small number of fingerprints, reducing the number of measurements significantly. We have implemented the proposed system on a WiFi-integrated mobile device and have evaluated the performance. Experimental results indicate that the proposed system leads to substantial improvement on localization accuracy and complexity over the widely used traditional fingerprinting methods.
Mobile handsets, Mobile radio mobility management, Compressed sensing, Wireless LAN, Mobile communication, WLANs, Indoor positioning, fingerprinting, compressive sensing, clustering, radio map
Chen Feng, Wain Sy Anthea Au, Shahrokh Valaee, Zhenhui Tan, "Received-Signal-Strength-Based Indoor Positioning Using Compressive Sensing", IEEE Transactions on Mobile Computing, vol.11, no. 12, pp. 1983-1993, Dec. 2012, doi:10.1109/TMC.2011.216
[1] I.F. Akyildiz, W. Su, Y. Sankarasubramaniam, and E. Cayirci, “A Survey on Sensor Networks,” IEEE Comm. Magazine, vol. 40, no. 8, pp. 102-114, Aug. 2002.
[2] L. Popov, “iNav: A Hybrid Approach to WiFi Localization and Tracking of Mobile Devices,” thesis, Computer Science and Eng., MIT, 2008.
[3] A. Hatami and K. Pahlavan, “A Comparative Performance Evaluation of RSS-Based Positioning Algorithms Used in WLAN Networks,” Proc. IEEE Wireless Comm. and Networking Conf., vol. 4, pp. 2331-2337, Mar. 2005.
[4] G. Sun, J. Chen, W. Guo, and K.J.R. Liu, “Signal Processing Techniques in Network-Aided Positioning: A Survey of State-of-the-Art Positioning Designs,” IEEE Signal Processing Magazine, vol. 22, no. 4, pp. 12-23, July 2005.
[5] A. Kushki, K.N. Plataniotis, and A.N. Venetsanopoulos, “Kernel-Based Positioning in Wireless Local Area Networks,” IEEE Trans. Mobile Computing, vol. 6, no. 6, pp. 689-705, June 2007.
[6] C. Feng, W.S.A. Au, S. Valaee, and Z.H. Tan, “Compressive Sensing Based Indoor Positioning Using RSS of WLAN Access Points,” Proc. IEEE INFOCOM, pp. 1-9, Mar. 2010.
[7] X. Li and K. Pahlavan, “Super-Resolution TOA Estimation with Diversity for Indoor Geolocation,” IEEE Trans. Wireless Comm., vol. 3, no. 1, pp. 224-234, Jan. 2004.
[8] A.S. Paul and E.A. Wan, “Wi-Fi Based Indoor Localization and Tracking Using Sigma-Point Kalman Filtering Methods,” Proc. IEEE/ION Position Location and Navigation Symp. (PLANS '08), pp. 646-659, May 2008.
[9] A. Goldsmith, Wireless Communications, first ed. Cambridge Univ., 2005.
[10] P. Bahl and V.N. Padmanabhan, “RADAR: An In-Building RF-Based User Location and Tracking System,” Proc. IEEE INFOCOM, vol. 2, pp. 775-784, 2002.
[11] K. Kaemarungsi and P. Krishnamurthy, “Modeling of Indoor Positioning Systems Based on Location Fingerprinting,” Proc. IEEE INFOCOM, vol. 2, pp. 1012-1022, Mar. 2004.
[12] “Ekahau,” http:/, 2006.
[13] B. Li, J. Salter, A.G. Dempster, and C. Rizos, “Indoor Positioning Techniques Based on Wireless LAN,” Proc. First IEEE Int'l Conf. Wireless Broadband and Ultra Wideband Comm., Mar. 2006.
[14] J. Ma, X. Li, X. Tao, and J. Lu, “Cluster Filtered KNN: A WLAN-Based Indoor Positioning Scheme,” Proc. Int'l Symp. World of Wireless, Mobile and Multimedia Networks, pp. 1-8, June 2008.
[15] R. Singh, L. Macchi, C. Regazzoni, and K. Plataniotis, “A Statistical Modelling Based Location Determination Method Using Fusion in WLAN,” Proc. Int'l Workshop Wireless Ad-Hoc Networks, 2005.
[16] E.J. Candes and M.B. Wakin, “An Introduction to Compressive Sampling,” IEEE Signal Processing Magazine, vol. 25, no. 2, pp. 21-30, Mar. 2008.
[17] J. Romberg, “Imaging via Compressive Sampling,” IEEE Signal Processing Magazine, vol. 25, no. 2, pp. 14-20, Mar. 2008.
[18] A. Akl and S. Valaee, “Accelerometer-Based Gesture Recognition via Dynamic Time Wrapping, Affinity Propagation, and Compressive Sensing,” Proc. IEEE Int'l Conf. Audio Speech and Signal Processing (ICASSP), pp. 2270-2273, Mar. 2010.
[19] S.S. Chen, D.L. Donoho, and M.A. Saunders, “Atomic Decomposition by Basis Pursuit,” SIAM J. Scientific Computing, vol. 20, no. 1, pp. 33-61, Aug. 1998.
[20] E.J. Candes, M.B. Wakin, and S. Boyd, “Enhancing Sparsity by Reweighted $\ell_1$ Minimization,” J. Fourier Analysis and Applications, vol. 14, no. 5, pp. 877-905, Dec. 2008.
[21] C. Feng, S. Valaee, and Z.H. Tan, “Multiple Target Localization Using Compressive Sensing,” Proc. IEEE GlobeCom, pp. 1-6, Dec. 2009.
[22] C. Feng, W.S.A. Au, S. Valaee, and Z.H. Tan, “Orientation-Aware Indoor Localization Using Affinity Propagation and Compressive Sensing,” Proc. IEEE Third Int'l Workshop Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP), pp. 261-264, Dec. 2009.
[23] S. Nikitaki and P. Tsakalides, “Localization in Wireless Networks via Spatial Sparsity,” Proc. Conf. Record of the 44th Asilomar Conf. Signals, Systems and Computers (ASILOMAR '10), pp. 236-239, Nov. 2010.
[24] B.J. Frey and D. Dueck, “Clustering by Passing Messages Between Data Points,” Science, vol. 315, no. 1, pp. 972-976, Feb. 2007.
[25] E. Gokcay and J. Principe, “Information Theoretic Clustering,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 24, no. 2, pp. 158-172, Feb. 2002.
[26] M.A. Youssef, A. Agrawala, and A.U. Shankar, “WLAN Location Determination via Clustering and Probability Distributions,” Proc. First IEEE Int'l Conf. Pervasive Computing and Comm., pp. 143-155, Mar. 2003.
[27] J. Shawe-Taylor and N. Cristianini, Kernel Methods for Pattern Analysis. Cambridge Univ., July 2004.
[28] E.J. Candes and J. Romberg, “Sparsity and Incoherence in Compressive Sampling,” Inverse Problems, vol. 23, no. 3, pp. 969-985, June 2007.
[29] E.J. Candes and T. Tao, “Near Optimal Signal Recovery from Random Projections: Universal Encoding Strategies?” vol. 52, no. 12, pp. 5406-5425, Dec. 2006.
[30] R.G. Baraniuk, M.A. Davenport, R.A. Devore, and M.B. Wakin, “A Simple Proof of the Restricted Isometry Property for Random Matrices,” Constructive Approximation, vol. 28, pp. 253-263, 2008.
[31] Y. Zhang, “Theory of Compressive Sensing via $\ell_1$ Minimization: A Non-Rip Analysis and Extensions,” Technical Report TR08-11, Rice CAAM Dept., 2008.
[32] E.J. Candes, J. Romberg, and T. Tao, “Stable Signal Recovery from Incomplete and Inaccurate Measurements,” Comm. Pure and Applied Math., vol. 59, pp. 1207-1223, 2006.
[33] C.B. Li, “An Efficient Algorithm for Total Variation Regularization with Applications to the Single Pixel Camera and Compressive Sensing,” master's thesis, Rice Univ., pp. 4-6, Sept. 2009.
[34] M. Lustig, D. Donoho, and J.M. Pauly, “Sparse MRI: The Application of Compressed Sensing for Rapid MR Imaging,” Magnetic Resonance in Medicine, vol. 58, pp. 1182-1195, Oct. 2007.
[35] “OpenNetCF, Smart Device Framework,” http://www.opennetcf. com/cf/productssdf.ocf , 2010.
[36] “DotNetMatrix, Simple Matrix Library for .NET,” , 2010.
[37] M. Youssef and A. Agrawala, “The Horus WLAN Location Determination System,” Proc. Third Int'l Conf. Mobile Systems, Applications, and Services, pp. 205-218, 2005.
[38] C. Rohrig and F. Kunemund, “Estimation of Position and Orientation of Mobile Systems in a Wireless LAN,” Proc. 46th IEEE Conf. Decision and Control, pp. 4932-4937, Dec. 2007.
19 ms
(Ver 2.0)

Marketing Automation Platform Marketing Automation Tool