Study of portable infrastructure-free cell phone detector for disaster relief

In disaster relief, especially in the rescue of serious disaster like great earthquake or tsunami, detecting the exact location of survivors via portable devices can greatly improve the efficiency of search and rescue work. A novel infrastructure-free cell phone positioning system based on software-defined radio, virtual base transceiver station software and its running scheme is proposed in this paper. The identification information of cell phones, receive signal strength and signal transceiver power data can be collected by this system. By using customized antennas with new positioning method, the proposed system can indicate the location of survivals trapped under debris without any operation on cell phones by survivors. With the new hybrid algorithm, search radius of the system can reach more than 1.2 km. And it is also able to implement accurate positioning by this system at the same time. Experimental results demonstrated that the system has significantly improved performance over the traditional methods.

[1]  Srdjan Capkun,et al.  GPS-free Positioning in Mobile Ad Hoc Networks , 2001, Proceedings of the 34th Annual Hawaii International Conference on System Sciences.

[2]  István Z. Kovács,et al.  Accuracy and timing aspects of location information based on signal-strength measurements in Bluetooth , 2005, 2005 IEEE 16th International Symposium on Personal, Indoor and Mobile Radio Communications.

[3]  Tutun Juhana,et al.  Mobile phone location logging into OpenBTS-based cellular network in disaster situation , 2014, 2014 8th International Conference on Telecommunication Systems Services and Applications (TSSA).

[4]  Ling Chen,et al.  Measurement of mobile radio propagation channel in ruins , 2010, 2010 IEEE International Conference on Wireless Communications, Networking and Information Security.

[5]  Jun Xu,et al.  AOA Cooperative Position Localization , 2008, IEEE GLOBECOM 2008 - 2008 IEEE Global Telecommunications Conference.

[6]  Linglong Dai,et al.  Positioning with OFDM signals for the next- generation GNSS , 2010, IEEE Transactions on Consumer Electronics.

[7]  Xiang Chu,et al.  Post-earthquake allocation approach of medical rescue teams , 2015, Natural Hazards.

[8]  A.E.S. Salazar.  Positioning Bluetooth/spl reg/ and Wi-Fi/spl trade/ systems , 2004, IEEE Transactions on Consumer Electronics.

[9]  Ismail Guvenc,et al.  An experimental study on RSS-based wireless localization with software defined radio , 2014, WAMICON 2014.

[10]  Ma Xin,et al.  Study of Personnel Positioning in Large Area based on Pseudo base Station , 2014 .

[11]  Wolfram Burgard,et al.  Improving RFID-based indoor positioning accuracy using Gaussian processes , 2010, 2010 International Conference on Indoor Positioning and Indoor Navigation.

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

[13]  Guifen Gu,et al.  The survey of GSM wireless communication system , 2010, 2010 International Conference on Computer and Information Application.

[14]  Tew-Fik Mahdi,et al.  Determination of failure probabilities of flood defence systems with improved dynamic bounds method , 2010 .

[15]  Shuang-Hua Yang,et al.  Design and Implementation of Instantly Deployable Localization System in Remote Areas , 2012, 2012 IEEE International Conference on Green Computing and Communications.

[16]  David P. Pancho,et al.  A WiFi-based software for indoor localization , 2014, 2014 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE).

[17]  Reiner S. Thoma,et al.  Middle-range surveillance by UWB radar: An experimental feasibility study , 2014, 2014 IEEE International Conference on Ultra-WideBand (ICUWB).

[18]  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).