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A Survey on Localization of Wireless Sensors

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Karthik Mohan
Karthik Mohan

The document summarizes localization techniques for wireless sensor nodes. It discusses several common localization methods including known location-based using GPS, proximity-based using signal strength, angle-based using angle of arrival, and range-based using time of arrival or time difference of arrival. It also covers some challenges with each approach like accuracy limitations and environmental factors. Finally, it provides a brief comparison of the localization techniques and their typical accuracy ranges from 1-15 meters depending on the method.

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A Survey on Localization of Wireless Sensor Nodes Masooda & Zuvairiya
Introduction What is a Wireless Sensor Network(WSN)? • A collection of sensing devices that can communicate wirelessly • Each device can sense, process, and talk to its peers • Sensor nodes can detect the the changes in the particular region or area • Sensor nodes are made up of off-the shelf materials • Each node requires GPS service Localisation is widely used to find the location of these sensor nodes
Fields of application of wireless sensor networks
Concepts and Properties of Localization Known location Proximity based Angle based Range based GPS IR, Bluetooth AoA RssI, TDoA, ToA LOCALIZATION Figure :overview of localization
Known Location Based Localization • Sensor nodes know their location in prior • Manually configuring or using a GPS • Manual configuration of the sensor node is done with the help of GPS GPS device can be effective where there are no reference nodes • available to get localized
Known Location Based Localization-GPS • Location is calculated with the help of GPS satellites • A minimum of four satellites are required to calculate the location of the GPS receiver • The distance between the GPS receiver and the GPS satellites are calculated using the time taken for the signal to reach the device • Once the distances are known, the GPS receiver uses Triangulation or Trilateration technique to determine its location
Proximity Based Localization • The WSN is divided into several clusters • Each cluster has a cluster head which is equipped with a GPS device • Using Infrared (IR), Bluetooth, etc., the nodes find out the nearness or proximity location
Angle based localization • Angle based localization uses the received signals angle or Angle of Arrival (AoA) to identify the distance • Angle of Arrival can be defined as angle between the received signal of an incident wave and some reference direction • The reference direction is called orientation, which is a fixed direction and against that the measurement of AoA is carried out • Using antenna array on each sensor node is the most common approach • Once the AoA is determined, triangulation is used to identify the location co-ordinates
Localization Using Triangulation With Orientation Information Figure :Localization using triangulation with oriented information
Range Based Localization • Localization is carried out based on the range • The range is calculated using the Received Signal Strength (RSSI) or Time of Arrival (ToA) or Time Difference of Arrival (TDoA) • In RSSI based localization the receiver sends the signal strength with reference to the sender, and sender calculates the distance based on the signal strength • ToA and TDoA use timing to calculate the range
Localization Schemes-Problems Known Location based Localization • Expensive • GPS go wrong - underground, underwater or indoor environment Proximity based Localization • Larger the range of central node smaller is the accuracy • Localization is not achievable when the central server is down Angle based Localization • The angle measurement error can vary from 1◦ to 25◦ as an effect of noise Range based Localization • Environmental changes
Performance Of Localization Schemes - Comparison Localization Techniques Used Accuracy (in meters) Limitations GPS 2 to 15 Indoor localization is not possible in many cases Proximity based 1 to 30 Depends on the range of the signal used Angle based approach 1 to 8 Require special antenna Range based approach 4 to 10 Require special hardware and time synchronization Table : Comparison of localization techniques
Summary • Introduction to localization • Localization techniques • Problems in localization schemes • Comparison of localization techniques
References I 1. R. Want, A. Hopper, V. Falcao, and J. Gibbons, “The Active Badge Location System,” ACM Trans. Information Systems, vol. 10, pp. 91 - 102, 1992. 2. J. Liu, Y. Zhang, and F. Zhao, “Robust Distributed Node Localization with Error Management,” Proc. ACM MobiHoc,2006 3. M.W. Carter, H.H. Jin, M.A. Saunders, and Y. Ye, “SpaseLoc: An Adaptive Subproblem Algorithm for Scalable Wireless Sensor Network Localization,” SIAM J. Optimization, 2006. 4. P. Bahl and V.N. Padmanabhan, “RADAR: An In-Building RFBased User Location and Tracking System,” Proc. IEEE INFOCOM, 2000. 5. D. Niculescu and B. Nath, “DV Based Positioning in Ad Hoc Networks,” J. Telecomm. Systems, vol. 22, pp. 267-280, 2003. 6. Priyantha, A. Chakraborty, and H. Balakrishnan, “The Cricket Location- Support System,” Proc. ACM MobiCom,2000.
7. R. Stoleru and J.A. Stankovic, “Probability Grid: A Location Estimation Scheme for Wireless Sensor Networks,” Proc. First IEEE Conf. Sensor and Ad Hoc Comm. and Networks (SECON 04), 2004. 8. N. Bulusu, J. Heidemann, and D. Estrin, “GPS-Less Low Cost Outdoor Localization for Very Small Devices,” IEEE Personal Comm. Magazine, vol. 7, no. 5, pp. 28-34, Oct. 2000. 9. Domenico Porcino and Walter Hirt, “Ultra-Wideband Radio Technology: Potential and Challenges Ahead,” IEEE Communications Magazine, pp. 66-74, July 2003. 10. Z. Li, W. Trappe, Y. Zhang, and B. Nath, “Robust Statistical Methods for Securing Wireless Localization in Sensor Networks,” 2005. 11. D. Liu, P. Ning, and W. Du, “Attack-Resistant Location Estimation in Sensor Networks,” 2005. 12. L. Fang, W. Du, and P. Ning, “A Beacon-Less Location Discovery Scheme for Wireless Sensor Networks,” 2005. 13. N.B. Priyantha, H. Balakrishnan, E. Demaine, and S. Teller, “Anchor-Free Distributed Localization in Sensor Networks,” 2003.
References II 14. X. Ji and H. Zha, “Sensor Positioning in Wireless Ad-Hoc Sensor Networks Using Multidimensional Scaling,” Proc.IEEE INFOCOM, 2004. 15. Murtuza Jadliwala, Sheng Zhong, Shambhu Upadhyaya, Chunming Qiao and Jean-Pierre Hubaux, “Secure Distance-Based Localization in the Presence of Cheating Beacon Nodes,” IEEE Transactions on Mobile Computing, 2010. 16. Guiling Wang, Wensheng Zhang, Jinsook Kim, Taiming Feng, Chuang Wang, “Catching Packet Droppers and Modifiers in Wireless Sensor Networks,” IEEE Transactions on Parallel and Distributed Systems, vol. 23, no. 5, pp. 835-843, May 2012. 17. Roy Want, Andy Hopper, Veronica Falcao and Jonathan Gibbons, “The active badge location system,” ACM Transactions on Information Systems (TOIS), Volume 10 Issue 1, Jan. 1992, Pages 91-102.
18. Nils Ole Tippenhauer and Srdjan Capkun, “ID-based Secure Distance Bounding and Localization,” Computer Security ESORICS 2009 Lecture Notes in Computer Science Volume 5789, pp 621-636, 2009. 19. Ravi Garg, Avinash L. Varna and Min Wu, “An Efficient Gradient Descent Approach to Secure Localization in Resource Constrained Wireless Sensor Networks,” IEEE Transactions on Information Forensics and Security, Vol. 7, No. 2, April 2012. 20. Zheng Yang and Yunhao Liu, “Quality of Trilateration: Confidence-Based Iterative Localization,” IEEE Transactions on Parallel and Distributed Systems, May 2010
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A Survey on Localization of Wireless Sensors

  • 1. A Survey on Localization of Wireless Sensor Nodes Masooda & Zuvairiya
  • 2. Introduction What is a Wireless Sensor Network(WSN)? • A collection of sensing devices that can communicate wirelessly • Each device can sense, process, and talk to its peers • Sensor nodes can detect the the changes in the particular region or area • Sensor nodes are made up of off-the shelf materials • Each node requires GPS service Localisation is widely used to find the location of these sensor nodes
  • 3. Fields of application of wireless sensor networks
  • 4. Concepts and Properties of Localization Known location Proximity based Angle based Range based GPS IR, Bluetooth AoA RssI, TDoA, ToA LOCALIZATION Figure :overview of localization
  • 5. Known Location Based Localization • Sensor nodes know their location in prior • Manually configuring or using a GPS • Manual configuration of the sensor node is done with the help of GPS GPS device can be effective where there are no reference nodes • available to get localized
  • 6. Known Location Based Localization-GPS • Location is calculated with the help of GPS satellites • A minimum of four satellites are required to calculate the location of the GPS receiver • The distance between the GPS receiver and the GPS satellites are calculated using the time taken for the signal to reach the device • Once the distances are known, the GPS receiver uses Triangulation or Trilateration technique to determine its location
  • 7. Proximity Based Localization • The WSN is divided into several clusters • Each cluster has a cluster head which is equipped with a GPS device • Using Infrared (IR), Bluetooth, etc., the nodes find out the nearness or proximity location
  • 8. Angle based localization • Angle based localization uses the received signals angle or Angle of Arrival (AoA) to identify the distance • Angle of Arrival can be defined as angle between the received signal of an incident wave and some reference direction • The reference direction is called orientation, which is a fixed direction and against that the measurement of AoA is carried out • Using antenna array on each sensor node is the most common approach • Once the AoA is determined, triangulation is used to identify the location co-ordinates
  • 9. Localization Using Triangulation With Orientation Information Figure :Localization using triangulation with oriented information
  • 10. Range Based Localization • Localization is carried out based on the range • The range is calculated using the Received Signal Strength (RSSI) or Time of Arrival (ToA) or Time Difference of Arrival (TDoA) • In RSSI based localization the receiver sends the signal strength with reference to the sender, and sender calculates the distance based on the signal strength • ToA and TDoA use timing to calculate the range
  • 11. Localization Schemes-Problems Known Location based Localization • Expensive • GPS go wrong - underground, underwater or indoor environment Proximity based Localization • Larger the range of central node smaller is the accuracy • Localization is not achievable when the central server is down Angle based Localization • The angle measurement error can vary from 1◦ to 25◦ as an effect of noise Range based Localization • Environmental changes
  • 12. Performance Of Localization Schemes - Comparison Localization Techniques Used Accuracy (in meters) Limitations GPS 2 to 15 Indoor localization is not possible in many cases Proximity based 1 to 30 Depends on the range of the signal used Angle based approach 1 to 8 Require special antenna Range based approach 4 to 10 Require special hardware and time synchronization Table : Comparison of localization techniques
  • 13. Summary • Introduction to localization • Localization techniques • Problems in localization schemes • Comparison of localization techniques
  • 14. References I 1. R. Want, A. Hopper, V. Falcao, and J. Gibbons, “The Active Badge Location System,” ACM Trans. Information Systems, vol. 10, pp. 91 - 102, 1992. 2. J. Liu, Y. Zhang, and F. Zhao, “Robust Distributed Node Localization with Error Management,” Proc. ACM MobiHoc,2006 3. M.W. Carter, H.H. Jin, M.A. Saunders, and Y. Ye, “SpaseLoc: An Adaptive Subproblem Algorithm for Scalable Wireless Sensor Network Localization,” SIAM J. Optimization, 2006. 4. P. Bahl and V.N. Padmanabhan, “RADAR: An In-Building RFBased User Location and Tracking System,” Proc. IEEE INFOCOM, 2000. 5. D. Niculescu and B. Nath, “DV Based Positioning in Ad Hoc Networks,” J. Telecomm. Systems, vol. 22, pp. 267-280, 2003. 6. Priyantha, A. Chakraborty, and H. Balakrishnan, “The Cricket Location- Support System,” Proc. ACM MobiCom,2000.
  • 15. 7. R. Stoleru and J.A. Stankovic, “Probability Grid: A Location Estimation Scheme for Wireless Sensor Networks,” Proc. First IEEE Conf. Sensor and Ad Hoc Comm. and Networks (SECON 04), 2004. 8. N. Bulusu, J. Heidemann, and D. Estrin, “GPS-Less Low Cost Outdoor Localization for Very Small Devices,” IEEE Personal Comm. Magazine, vol. 7, no. 5, pp. 28-34, Oct. 2000. 9. Domenico Porcino and Walter Hirt, “Ultra-Wideband Radio Technology: Potential and Challenges Ahead,” IEEE Communications Magazine, pp. 66-74, July 2003. 10. Z. Li, W. Trappe, Y. Zhang, and B. Nath, “Robust Statistical Methods for Securing Wireless Localization in Sensor Networks,” 2005. 11. D. Liu, P. Ning, and W. Du, “Attack-Resistant Location Estimation in Sensor Networks,” 2005. 12. L. Fang, W. Du, and P. Ning, “A Beacon-Less Location Discovery Scheme for Wireless Sensor Networks,” 2005. 13. N.B. Priyantha, H. Balakrishnan, E. Demaine, and S. Teller, “Anchor-Free Distributed Localization in Sensor Networks,” 2003.
  • 16. References II 14. X. Ji and H. Zha, “Sensor Positioning in Wireless Ad-Hoc Sensor Networks Using Multidimensional Scaling,” Proc.IEEE INFOCOM, 2004. 15. Murtuza Jadliwala, Sheng Zhong, Shambhu Upadhyaya, Chunming Qiao and Jean-Pierre Hubaux, “Secure Distance-Based Localization in the Presence of Cheating Beacon Nodes,” IEEE Transactions on Mobile Computing, 2010. 16. Guiling Wang, Wensheng Zhang, Jinsook Kim, Taiming Feng, Chuang Wang, “Catching Packet Droppers and Modifiers in Wireless Sensor Networks,” IEEE Transactions on Parallel and Distributed Systems, vol. 23, no. 5, pp. 835-843, May 2012. 17. Roy Want, Andy Hopper, Veronica Falcao and Jonathan Gibbons, “The active badge location system,” ACM Transactions on Information Systems (TOIS), Volume 10 Issue 1, Jan. 1992, Pages 91-102.
  • 17. 18. Nils Ole Tippenhauer and Srdjan Capkun, “ID-based Secure Distance Bounding and Localization,” Computer Security ESORICS 2009 Lecture Notes in Computer Science Volume 5789, pp 621-636, 2009. 19. Ravi Garg, Avinash L. Varna and Min Wu, “An Efficient Gradient Descent Approach to Secure Localization in Resource Constrained Wireless Sensor Networks,” IEEE Transactions on Information Forensics and Security, Vol. 7, No. 2, April 2012. 20. Zheng Yang and Yunhao Liu, “Quality of Trilateration: Confidence-Based Iterative Localization,” IEEE Transactions on Parallel and Distributed Systems, May 2010