DIFAR sonobuoy bearing estimation using the fast orthogonal search algorithm

The acoustic environment in the ocean contains numerous narrowband and broadband sources which conflict to introduce uncertainty in bearing estimates used to detect submerged targets. The detection and localization of a target of interest in the presence of noise is the key element of anti-submarine warfare. The DIFAR sonobuoy is the most effective tool for this purpose.; A DIFAR sonobuoy is comprised of 3 receiving elements which can be used to extract directional information from an incoming acoustic signal. High-resolution beamforming techniques, including the Maximum Likelihood Adaptive Beamformer (MLAB), have been previously applied to real DIFAR data [Desrochers, 1999] to provide successful direction estimates of two sources in the same frequency bin. MLAB uses the Fast Fourier Transform (FFT) to compute a cross-spectral matrix that is used to estimate the bearing of acoustic targets.; It has been shown that Fast Orthogonal Search (FOS) technique can yield a higher frequency resolution with a lower variance on the estimate than the FFT algorithm. This thesis applies the FOS algorithm in place of the FFT in both the arctangent bearing estimator and ML Beamformer.; Using FOS to create a spectral estimate for DIFAR sonobuoy data has shown an improvement in the detection of narrowband sources. A better spectral estimate in the presence of noise leads to an improved bearing estimate calculated using both a simple arctangent bearing estimator and the Maximum Likelihood Adaptive Beamformer.