학술논문

Maximum-Likelihood Sensor Node Localization Using Received Signal Strength in Multimedia With Multipath Characteristics
Document Type
Periodical
Source
IEEE Systems Journal Systems Journal, IEEE. 12(1):506-515 Mar, 2018
Subject
Components, Circuits, Devices and Systems
Computing and Processing
Soil
Wireless sensor networks
Distance measurement
Multimedia communication
Optimization
Fertilizers
Hybrid network architecture
maximum likelihood optimization
node localization
path-loss model
precision agriculture
sensitivity analysis
triangulation
wireless sensor networks (WSN)
Language
ISSN
1932-8184
1937-9234
2373-7816
Abstract
Sensors are key to situation awareness and response and need to maintain time and position information to tag their measurement data. While local clocks can be used for time stamping, geotagging can be challenging for sensors with no access to GPS, such as the underground environment in precision agriculture. We study the problem of sensor node localization for a hybrid wireless sensor network for precision agriculture, with satellite nodes located above ground and sensor nodes located underground. This application is quite unique in possessing multimedia and multipath features. We use received signal strength of signals transmitted between neighboring sensor nodes and between satellite nodes and sensor nodes as a means to perform the ranging measurement. The localization problem is formulated as that of estimating the parameters of the joint distribution of the received signal strength at all nodes in the network. First, we arrive at path loss and fading models for various multimedia and multipath communication scenarios in our network to model the received signal strength in terms of the propagation distance and, hence, the participating nodes’ location coordinates. We account for various signal degradation effects such as fading, reflection, transmission, and interference between two signals arriving along different paths. Then, we formulate a maximum-likelihood optimization problem to estimate the nodes’ location coordinates using the derived statistical model. We also present a sensitivity analysis of the estimates with respect to soil permittivity and magnetic permeability.