Natural Hazards

, Volume 95, Issue 3, pp 569–583 | Cite as

Study on RSS/AOA hybrid localization in life detection in huge disaster situation

  • ShiYang Tang
  • XueMing ShuEmail author
  • Jun Hu
  • Rui Zhou
  • ShiFei Shen
  • SiYang Cao
Original Paper


Rescue is a tough and time-consuming task in huge disaster. After stricken by a catastrophic natural disaster, the rescue force is typically deployed under the circumstance of traffic paralysis and lack of supplies. To cope with this situation, plenty of human resource and professional equipment are required. However, both the human resource and equipment are insufficient in most situations. The rescue force needs an efficient technology for searching the survivals, such as the life detection, which can be a key factor in disaster relief. Fast and accurate locating of the survivals will guide the limited rescue resource to save more survivors. However, current life detection technology cannot meet the demand of rescue in huge disaster. A novel life detection system based on fake base station is proposed. The detection system can scan the whole disaster area and find the cell phones, which leads to the surviving owners. As the system works in different way with other traditional human localization technology, a novel RSS/AOA hybrid positioning algorithm was proposed in this paper to increase the accuracy of localization. To verify the accuracy, two simulation tests were designed. The result of the two tests illustrates that the novel algorithm is more suitable to work with the novel life detection system.


Life detection AOA RSS Disaster relief 



Supported by National Natural Science Foundation of China (71774094), National Key R&D Program of China during the 13th 5-year Plan Period (2017YFC0806607) and National Science and Technology Pillar Program during the 12th 5-year Plan Period (2015BAK12B03).


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Copyright information

© Springer Nature B.V. 2018

Authors and Affiliations

  • ShiYang Tang
    • 1
    • 3
  • XueMing Shu
    • 1
    Email author
  • Jun Hu
    • 1
  • Rui Zhou
    • 1
  • ShiFei Shen
    • 1
  • SiYang Cao
    • 2
  1. 1.Department of Engineering PhysicsTsinghua UniversityBeijingChina
  2. 2.Department of Electrical and Computer EngineeringThe University of ArizonaTucsonUSA
  3. 3.Global Energy Interconnection Research Institute Co., Ltd.BeijingChina

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