This paper is a tutorial which describes "main stream" sonar digital signal processing functions along with the associated implementation considerations. The attempt is to promote further cross-fertilization of ideas among digital signal processing applications in sonar, radar, speech, communications, seismology, and other related fields.

Digital signal processing for sonar

: By ambient noise we mean the prevailing, sustained unwanted background of sound at some spot in the ocean. It excludes momentary, occasional sounds, such as the noise of a close-by passage of a ship or of an occasional rain squall. It is the background of noise, typical of the location and depth where a measuring hydrophone is located, against which a signal," such as the sound of a submarine or the echo from a target, must be detected. Ambient noise also excludes all forms of self-noise, such as the noise of current flow around the measurement hydrophone and its supporting structure, and obviously must exclude all forms of electrical noise. Thus, ambient noise is what is left over, so to speak, after identifiable, occasional noise sources are accounted for.

Ambient noise in the sea

Though referred to as noise, the ambient ocean soundscape carries valuable information about the physical ocean environment. To study this information, Kuperman and Ingenito introduced a model for spatial coherence in a depth stratified ocean arising from the vertically directive diffuse acoustic noise produced by bubbles distributed throughout the surface. Here the model is adapted to incorporate horizontal directivity as well, making it possible to include additional noise contributions from directive features such as storms, biologics, shipping, and wave breaking. As an analytic approach, the model can serve as a computationally light complement to existing methods.

A model for the spatial coherence of arbitrarily directive noise in the depth-stratified ocean

: In order to overcome the challenges that an anisotropic noise field poses for underwater target tracking, we conduct an onboard estimation of the horizontal noise directionality in the real-time processing suite of an autonomous underwater vehicle (AUV) towing a horizontal line array. The estimation of the noise directionality is a precursor to another adaptive behavior: optimizing tracking capability of a towed array by choosing a particular heading that minimizes the detection level in the target's direction. In each distinct simulated anisotropic noise field, the AUV successfully calculates the optimal towed array headings based on the real-time estimation of the horizontal noise directionality. The findings reveal a clear advantage over the conventional broadside beam tracking method, with some limitations due predominantly to the noise field itself.

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Target Tracking Onboard an Autonomous Underwater Vehicle: Determining Optimal Towed Array Heading in an Anisotropic Noise Field

For many reasons, the three-dimensional (3-D) arrival structure of the undersea ambient noise field is of interest to the research and development community. One reason is that the arrival structure can be used to estimate the beam noise of an array, which may be required to estimate the performance of the array as an operational Navy asset or a scientific measurement tool. Another reason is that there are clues inherent in the vertical arrival structure that relate to the nature of the acoustic propagation along the azimuths of the noise sources. Similarly, there are also clues in the horizontal arrival structure of the undersea ambient noise field that relate to the azimuthal distribution of the noise sources. Both of these classes of clues are important in the verification and validation of undersea ambient noise models. The ideal measurement tool to measure the 3-D arrival structure of the noise field is a high-resolution volumetric array sonar system. Unfortunately, such a system is not generally available. However, towed horizontal line arrays are available and can be used, even though they are far from ideal. The beam patterns of a line array are conically symmetric about the axis of the array. When the axis of a horizontal line array is tilted slightly from an elevation angle of 0°, the vertical character of the beam cones can be used to discriminate between various vertical arrival angles. Combined with measurements made on several different towed array headings, an estimate of the 3-D directionality of the noise field can be obtained. An algorithm that uses such a technique on single-line towed array data to generate an estimate of the 3-D directionality of the noise field is described herein. Some results using measured data from a recent noise measurement exercise are presented and discussed.

Three-dimensional noise field directionality estimation from single-line towed array data

A new approach to undersea ambient noise field horizontal directionality estimation from towed line array data is presented. This new technique includes the effects of the three‐dimensional array response and the noise field vertical arrival structure during the estimation process. It is sufficiently general to include the angle of array tilt from the horizontal and does not require noise field stationarity as do most previous methods. The vertical dimension is included in the estimation process through a transformation of the noise field from a spherical coordinate system to a conical coordinate system of the array with an arbitrary tilt angle. The three‐dimensional pseudostationary noise field estimate ? (ϑ,φ) which results is then integrated over the vertical (φ) to obtain the horizontal directionality estimate ? (ϑ). The results indicate significant improvement in ? (ϑ) when the array tilt and noise vertical arrival structure are accounted for.

R. A. Wagstaff

Papers

Horizontal directionality estimation considering array tilt and noise field vertical arrival structure