Title : 
Optimal sensor deployment for 3D AOA target localization
         
        
            Author : 
Sheng Xu ; Dogancay, Kutluyil
         
        
            Author_Institution : 
Inst. for Telecommun. Res., Univ. of South Australia, Adelaide, SA, Australia
         
        
        
        
        
        
            Abstract : 
This paper investigates the problem of how to improve angle-of-arrival (AOA) target localization accuracy by finding an optimal AOA sensor deployment strategy in 3D space. Under the assumption of constant absolute elevation angles for the sensors, a novel and simple optimal sensor deployment criterion is proposed based on minimizing the trace of inverse Fisher information matrix. Our analysis shows that when sensor elevation angles equal ±42.2869° and twice of azimuth angles have equal angular distribution with uniform distance from the target and equal noise covariance, the lowest mean squared error is achieved. Besides, with more sensors placed closer to the target, a lower mean squared error is attained. Simulation examples are presented to verify the effectiveness of the developed optimality criterion.
         
        
            Keywords : 
direction-of-arrival estimation; matrix inversion; mean square error methods; sensor placement; 3D AOA target localization; angle-of-arrival target localization; angular distribution; constant absolute elevation angle; inverse Fisher information matrix trace minimization; mean squared error; optimal sensor deployment; Azimuth; Covariance matrices; Estimation; Kalman filters; Noise; Noise measurement; Three-dimensional displays; Angle-of-arrival localization; Cramér-Rao lower bound; Fisher information matrix; optimal sensor deployment;
         
        
        
        
            Conference_Titel : 
Acoustics, Speech and Signal Processing (ICASSP), 2015 IEEE International Conference on
         
        
            Conference_Location : 
South Brisbane, QLD
         
        
        
            DOI : 
10.1109/ICASSP.2015.7178430