  Angle of arrival (AOA) is widely used to locate a wireless signal emitter in
unmanned aerial vehicle (UAV) localization. Compared with received signal
strength (RSS) and time of arrival (TOA), it has higher accuracy and is not
sensitive to time synchronization of the distributed sensors. However, there
are few works focused on three-dimensional (3-D) scenario. Furthermore,
although maximum likelihood estimator (MLE) has a relatively high performance,
its computational complexity is ultra high. It is hard to employ it in
practical applications. This paper proposed two multiplane geometric center
based methods for 3-D AOA in UAV positioning. The first method could estimate
the source position and angle measurement noise at the same time by seeking a
center of the inscribed sphere, called CIS. Firstly, every sensor could measure
two angles, azimuth angle and elevation angle. Based on that, two planes are
constructed. Then, the estimated values of source position and angle noise are
achieved by seeking the center and radius of the corresponding inscribed
sphere. Deleting the estimation of the radius, the second algorithm, called
MSD-LS, is born. It is not able to estimate angle noise but has lower
computational complexity. Theoretical analysis and simulation results show that
proposed methods could approach the Cramer-Rao lower bound (CRLB) and have
lower complexity than MLE.
