Three-Dimensional Direction Finding of Radio Sources in Low SNR Environments

This paper deals with the direction-of-arrival (DOA) estimation problem in three-dimensional (3D) space in low signal-to-noise ratio (SNR) environments. The proposed solution utilizes an Isolog-3D antenna with advanced signal processing techniques for solving direction finding in 3D space (DF-3D) problem. Standard DF-3D solutions have been shown to work ineffectively in low SNR scenarios due to large power estimation errors. For solving this problem, we propose in this paper a simple but effective method for reducing DOA estimation errors. The reduction of DOA estimation errors is obtained by combining an amplitude calibration algorithm with the standard Kalman filter. The amplitude calibration helps in removing bias errors in power estimation while the Kalman filter alleviates random noises in DOA estimation. Theoretical and simulation results have been shown for demonstrating the effectiveness of the proposed solution.