Localization Algorithms in a Wireless Sensor Network Using Distance and Angular Data

The applications of positioning in wireless sensor networks include patient monitoring, asset tracking, and intelligent transportation including air traffic control. Popular methods are: received-signal-strength (RSS); time-of-arrival (TOA); time-difference-of-arrival (TDOA); and angle-of-arrival (AOA). Estimation is based on nonlinear equations constructed from measurements and knowledge of the anchor node geometry. In this thesis, anchor-based line-of-sight TOA and AOA are reviewed, and new techniques, namely DAOA (differential-angle-of-arrival) and hybrid TOA/DAOA are proposed for rotating laser implementation. For the TOA approach, a nonlinear Least Square Estimator (LSE) is applied to one- and two-dimensional systems, then the equations are linearized and solved by unconstrained/constrained LSE. This LSE procedure is also used for AOA. For DAOA, all the anchors are placed on a circle in order to simplify the solution, and then LSE is used to estimate an unlocalized node. The statistical accuracy of these methods, from simulation, is presented graphically for simple read-and-use application.