LAUSR

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.