Received signal strength difference–based tracking estimation method for arbitrarily moving target in wireless sensor networks

The surveillance system, which is mainly used for detecting and tracking moving targets, is one of the most significant applications of wireless sensor networks. Up to present, received signal strength indicator is the most common measuring mean for estimating the distance in sensor networks. However, in the presence of noise, it is impossible to gain the accurate distance based on received signal strength indicator. In this article, we propose a new tracking scheme based on received signal strength difference, which is the difference value of received signal strength indicators between two neighboring sampling steps. Supposing the noise has a certain degree of correlation in a certain time interval, received signal strength difference can effectively reduce the negative impact from noise. The tracking algorithm based on received signal strength difference is built: The sensor nodes collectively estimate a possible zone of the target via the signs of received signal strength difference. Next, the possible zone is further immensely shrunk to the refined zone via the absolute values of received signal strength difference. Finally, we determine the target’s final location by choosing the reference dot with the minimum norm in the refined zone. The simulation results demonstrate that the proposed tracking method achieves higher localization accuracy than the typical received signal strength indicator–based scheme. The received signal strength difference–based method also has good generality and robustness with respect to the noises with different deviation values and the target following arbitrarily state model.

[1]  T. Aaron Gulliver,et al.  Range-Based Localization in Wireless Networks Using Density-Based Outlier Detection , 2010, Wirel. Sens. Netw..

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

[3]  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).

[4]  Shing-Tsaan Huang,et al.  ALRD: AoA Localization with RSSI Differences of Directional Antennas for Wireless Sensor Networks , 2012, International Conference on Information Society (i-Society 2012).

[5]  Matthew B. Dwyer,et al.  Sensing through the continent: Towards monitoring migratory birds using cellular sensor networks , 2012, 2012 ACM/IEEE 11th International Conference on Information Processing in Sensor Networks (IPSN).

[6]  Xiaojun Cao,et al.  Ubiquitous WSN for Healthcare: Recent Advances and Future Prospects , 2014, IEEE Internet of Things Journal.

[7]  Sajal K. Das,et al.  A survey on sensor localization , 2010 .

[8]  Meng Joo Er,et al.  Range-free wireless sensor networks localization based on hop-count quantization , 2012, Telecommun. Syst..

[9]  Waldemar Gerok,et al.  TDOA assisted RSSD localization in UWB , 2012, 2012 9th Workshop on Positioning, Navigation and Communication.

[10]  Emanuele Goldoni,et al.  Experimental analysis of RSSI-based indoor localization with IEEE 802.15.4 , 2010, 2010 European Wireless Conference (EW).

[11]  Xing Wei,et al.  A New Localization Technique Based on Network TDOA Information , 2006, 2006 6th International Conference on ITS Telecommunications.

[12]  Hyunjae Woo,et al.  Reliable anchor node based range-free localization algorithm in anisotropic wireless sensor networks , 2013, The International Conference on Information Networking 2013 (ICOIN).

[13]  Linqing Gui,et al.  Improvement of range-free localization technology by a novel DV-hop protocol in wireless sensor networks , 2015, Ad Hoc Networks.

[14]  Sema Oktug,et al.  Three Dimensional Localization in Wireless Sensor Networks Using the Adapted Multi-Lateration Technique Considering Range Measurement Errors , 2009, 2009 IEEE Globecom Workshops.

[15]  Wei Hong,et al.  Design and implementation of a smart mini-base station for the Internet of Things , 2015, 2015 Asia-Pacific Microwave Conference (APMC).

[16]  Bernhard Hofmann-Wellenhof,et al.  GPS - Global Positioning System. Theory and practice. , 1997 .

[17]  Shuyuan Li,et al.  Blind RSSD-Based Indoor Localization with Confidence Calibration and Energy Control , 2016, Sensors.

[18]  Ian F. Akyildiz,et al.  Wireless sensor networks: a survey , 2002, Comput. Networks.

[19]  Noël Crespi,et al.  Semantic Context-Aware Service Composition for Building Automation System , 2014, IEEE Transactions on Industrial Informatics.

[20]  Cheng-Long Chuang,et al.  High-Precision RSSI-based Indoor Localization Using a Transmission Power Adjustment Strategy for Wireless Sensor Networks , 2012, 2012 IEEE 14th International Conference on High Performance Computing and Communication & 2012 IEEE 9th International Conference on Embedded Software and Systems.

[21]  B. Widrow,et al.  Adaptive noise cancelling: Principles and applications , 1975 .

[22]  Brian D. O. Anderson,et al.  Wireless sensor network localization techniques , 2007, Comput. Networks.

[23]  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).

[24]  Sanjay Jha,et al.  Trajectory Approximation for Resource Constrained Mobile Sensor Networks , 2014, 2014 IEEE International Conference on Distributed Computing in Sensor Systems.

[25]  David E. Culler,et al.  Calibration as parameter estimation in sensor networks , 2002, WSNA '02.

[26]  H.T. Friis,et al.  A Note on a Simple Transmission Formula , 1946, Proceedings of the IRE.

[27]  Jagruti Sahoo,et al.  DuRT: Dual RSSI Trend Based Localization for Wireless Sensor Networks , 2013, IEEE Sensors Journal.

[28]  Simone Morosi,et al.  Radio Context Awareness and Applications , 2013, J. Sensors.

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

[30]  Cecilia Mascolo,et al.  Evolution and sustainability of a wildlife monitoring sensor network , 2010, SenSys '10.

[31]  Reza Olfati-Saber,et al.  Collaborative target tracking using distributed Kalman filtering on mobile sensor networks , 2011, Proceedings of the 2011 American Control Conference.

[32]  P.K. Varshney,et al.  Target Location Estimation in Sensor Networks With Quantized Data , 2006, IEEE Transactions on Signal Processing.

[33]  Fabrice Valois,et al.  Is RSSI a Good Choice for Localization in Wireless Sensor Network? , 2012, 2012 IEEE 26th International Conference on Advanced Information Networking and Applications.

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

[35]  Pooja B. Patil,et al.  Monitoring System for Prisoner with GPS using Wireless Sensor Network (WSN) , 2014 .

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

[37]  Pavel Loskot,et al.  A High-Resolution Sensor Network for Monitoring Glacier Dynamics , 2014, IEEE Sensors Journal.

[38]  Xiang Ji,et al.  Sensor positioning in wireless ad-hoc sensor networks using multidimensional scaling , 2004, IEEE INFOCOM 2004.

[39]  Azzedine Boukerche,et al.  Localization systems for wireless sensor networks , 2007, IEEE wireless communications.

[40]  Shigeng Zhang,et al.  A locality-based range-free localization algorithm for anisotropic wireless sensor networks , 2016, Telecommun. Syst..

[41]  Seth J. Teller,et al.  The cricket compass for context-aware mobile applications , 2001, MobiCom '01.

[42]  Dharmendra Sharma,et al.  Accuracy of Location Identification with Antenna Polarization on RSSI , 2009 .

[43]  Bernard Uguen,et al.  High-frequency surface wave radar based on a sea floating antenna concept , 2009 .

[44]  B. Hofmann-Wellenhof,et al.  Global Positioning System , 1992 .

[45]  Sangwoo Lee,et al.  Range-free localization with isotropic distance scaling in wireless sensor networks , 2013, The International Conference on Information Networking 2013 (ICOIN).