DOA-Estimations-Based 3D Geolocations Using Factor Graphs

This paper proposes direction of arrival (DOA)-estimation-based three-dimensional (3D) positioning techniques using factor graphs. The multiple signal classification (MUSIC), root-MUSIC, and estimation of signal parameters via rotational invariance techniques (ESPRIT) algorithms are used to estimate the DOA of the signals received by multiple sensors. A factor graph (FG) detector updates and refines the measured DOA for obtaining the target positions. Since only the mean and the variance of the DOA are needed for the factor graph process, the burden of the data transmission of the uplink from the sensors to the fusion center and the complexity of the positioning is reduced significantly. The effectiveness of the proposed method is demonstrated through simulations. No matter which DOA estimation method is used, MUSIC, root-MUSIC, or ESPRIT, FG algorithms achieve higher positional accuracy compared to the linear least square (LS) positioning solution in terms of the root mean square error (RMSE).