Statistical Location Estimation in Container-Grown Seedlings Based on Wireless Sensor Networks

Lee, Sang-Hyun;Moon, Kyung-Il

  • Received : 2014.10.17
  • Accepted : 2014.12.05
  • Published : 2014.12.31


This paper presents a sensor location decision making method respect to Container-Grown Seedlings in view of precision agriculture (PA) when sensors involved in tree container measure received signal strength (RSS) or time-of-arrival (TOA) between themselves and neighboring sensors. A small fraction of sensors in the container-grown seedlings system have a known location, whereas the remaining locations must be estimated. We derive Rao-Cramer bounds and maximum-likelihood estimators under Gaussian and log-normal models for the TOA and RSS measurements, respectively.


Container-Grown Seedlings;Wireless Sensor Network;Sensor Position Location;Signal Strength;Time-of-Arrival;Rao-Cramer bound


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