Abstract

Inverse beamforming (IBF) has been very successful in detecting signals of very low levels in measured ocean data and during real-time at-sea experiments. The large performance gains for IBF are attributed to the Fourier integral method (FIM) beamforming solution [J. H. Wilson, J. Acoust. Soc. Am. 73, 1648–1656 (1983); A. Nuttall and J. H. Wilson, ibid. 90, 2004–2019 (1991)], to the inverse beamforming integral equation, to a new data thresholding technique called the eight nearest-neighbor peak picker (ENNPP), and to a postprocessing technique called the three-dimensional M of N tracker. Collectively, FIM, the ENNPP, and M of N tracker are referred to as IBF and Outpost SUNRISE data and they are used to determine the minimum detectable level (MDL) for three signal processing methods: conventional beamforming (CBF) using the LOFARGRAM display, CBF using the ENNPP and M of N tracker, and FIM using the ENNPP and M of N tracker (i.e., IBF). IBF was derived based on the environmental acoustic (EVA) properties of measured ambient noise and those EVA properties are in stark contrast to the ideal signal and noise conditions normally assumed in classical detection theory [M. Barkat, Signal Detection and Estimation (Artech House, London, 1991)]. Outpost SUNRISE noise data were chosen for the MDL evaluation because the shipping, wind, propagation, and other environmental supporting parameters were well measured during the exercise, typical of an exercise conducted by the advanced environmental acoustic support (AEAS) program. It is shown that the IBF MDLs are over 10 dB lower than those for CBF with the ENNPP and M of N tracker, and for CBF with high quality beam LOFARGRAM displays. A subsequent paper will compare IBF to other widely used high-resolution beamforming methods and the IBF theoretical gains are discussed in a companion paper [J. Wilson, J. Acoust. Soc. Am. 98, 3240–3251 (1995)] where EVA issues are illustrated by FRAZ surfaces from Outpost SUNRISE.

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