Robust localization over obstructed interferences for inbuilding wireless applications

Location-awareness can be applied to the various consumer applications. A received signal strength (RSS) based localization system is relatively inexpensive and simple to be implemented without additional hardware supports. However, the radio signals are strongly affected by the obstructed interferences. This is a difficult problem for the RSS based localization systems to be implemented in real world. To solve this problem, we propose a practical and robust localization algorithm in the obstructed environments. The proposed algorithm uses the Maximum Likelihood Estimation (MLE) based on the position probability grid. In addition, the proposed algorithm detects and compensates the large measurement error using the Min-Max algorithm. We evaluated the performance of the proposed algorithm in the obstructed environments. Performance results show that the proposed algorithm outperforms other algorithms on the obstructed environments.

[1]  Gianluca Mazzini,et al.  Localization in sensor networks with fading and mobility , 2002, The 13th IEEE International Symposium on Personal, Indoor and Mobile Radio Communications.

[2]  Theodore S. Rappaport,et al.  Wireless communications - principles and practice , 1996 .

[3]  Tarek F. Abdelzaher,et al.  Range-free localization schemes for large scale sensor networks , 2003, MobiCom '03.

[4]  Deborah Estrin,et al.  GPS-less low-cost outdoor localization for very small devices , 2000, IEEE Wirel. Commun..

[5]  Alfred O. Hero,et al.  Relative location estimation in wireless sensor networks , 2003, IEEE Trans. Signal Process..

[6]  Ying Zhang,et al.  Localization from mere connectivity , 2003, MobiHoc '03.

[7]  Mani B. Srivastava,et al.  Dynamic fine-grained localization in Ad-Hoc networks of sensors , 2001, MobiCom '01.

[8]  Alfred O. Hero,et al.  Distributed weighted-multidimensional scaling for node localization in sensor networks , 2006, TOSN.

[9]  B. R. Badrinath,et al.  Ad hoc positioning system (APS) , 2001, GLOBECOM'01. IEEE Global Telecommunications Conference (Cat. No.01CH37270).

[10]  Mihail L. Sichitiu,et al.  Localization of wireless sensor networks with a mobile beacon , 2004, 2004 IEEE International Conference on Mobile Ad-hoc and Sensor Systems (IEEE Cat. No.04EX975).

[11]  King Lun Yiu.  Ad-hoc positioning system , 2008 .

[12]  Mani B. Srivastava,et al.  The n-Hop Multilateration Primitive for Node Localization Problems , 2003, Mob. Networks Appl..

[13]  Mihail L. Sichitiu,et al.  Localization in Wireless Sensor Networks: A Probabilistic Approach , 2003, International Conference on Wireless Networks.

[14]  B. R. Badrinath,et al.  Ad hoc positioning system (APS) using AOA , 2003, IEEE INFOCOM 2003. Twenty-second Annual Joint Conference of the IEEE Computer and Communications Societies (IEEE Cat. No.03CH37428).

[15]  L. El Ghaoui,et al.  Convex position estimation in wireless sensor networks , 2001, Proceedings IEEE INFOCOM 2001. Conference on Computer Communications. Twentieth Annual Joint Conference of the IEEE Computer and Communications Society (Cat. No.01CH37213).

[16]  R.L. Moses,et al.  Locating the nodes: cooperative localization in wireless sensor networks , 2005, IEEE Signal Processing Magazine.

[17]  Mani B. Srivastava,et al.  The bits and flops of the n-hop multilateration primitive for node localization problems , 2002, WSNA '02.

[18]  Hari Balakrishnan,et al.  6th ACM/IEEE International Conference on on Mobile Computing and Networking (ACM MOBICOM ’00) The Cricket Location-Support System , 2022 .

[19]  John Krumm,et al.  Location-aware computing comes of age , 2004, Computer.

[20]  B. R. Badrinath,et al.  DV Based Positioning in Ad Hoc Networks , 2003, Telecommun. Syst..