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Bearing Estimation of Narrow Band Acoustic Signals Using Cardioid Beamforming Algorithm in Shallow Water  

Chang, Duk-Hong (Agency for Defense Development)
Park, Hong-Bae (School of Electrical Engineering & Computer Science, Kyungpook National University)
Na, Young-Nam (Agency for Defense Development)
Ryu, Jon-Ha (Agency for Defense Development)
Abstract
This paper suggests the Cardioid beamforming algorithm of the doublet sensors employing DIFAR (directional frequency analysis and recording) sensor signals in the frequency domain. The algorithm enables target bearing estimation using the signals from directional sensors. The algorithm verifies its applicability by successfully estimating bearings of a target projecting ten narrow-band signals in shallow water. The estimated bearings agree very well with those from GPS (global positioning system) data. Assuming the bearings from GPS data to be real values, the estimation errors are analyzed statistically. The histogram of estimation errors in each frequency have Gaussian shape, the mean and standard deviation dropping in the ranges -1.1°∼ 6.7°and 13.3∼43.6°, respectively. Estimation errors are caused by SNR (signal to noise ratio) degradation due to propagation loss between the source and receiver, daily fluctuating geo-magnetic fields, and non-stationary background noises. If multiple DIFAR systems are employed, in addition to bearing, range information could be estimated and finally localization or tracking of a target is possible.
Keywords
Cardioid beamforming; DIFAR; MRA;
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