No abstract

No abstract

The use of acoustical techniques in oceanography is well known. Traditional applications have concentrated on long range, low frequency propagation. More recently, due a convergence of both technology and national interests, consideration of the possibilities for creating high frequency, real time, multi-dimensional imaging systems (2 and 3-D) has emerged. Unfortunately, due to a lack of experimental investigation, the propagation issues related to these frequencies are relatively unknown. Our group in underwater acoustic imaging applied to ocean exploration and oceanography has been taking high frequency acoustic pictures in the ocean for almost a decade. Our first experiences were in using the traditional types of ocean going sonars such as side scans. More recently we have been developing a 3-dimensional multibeam imaging system for tracking small animals in the sea. As part of this effort we have been looking a t both the spatial and temporal correlation scales for the propagation of high frequency sound.

An algorithm to isolate multiple targets reflecting multiple correlated signals arriving at a receiver is described. The algorithm stems from a specific application, an active high-frequency, three-dimensional imaging system that is used to image zooplankton [Jaffe et al., ‘‘FTV: A Sonar for Tracking Macrozooplankton in 3-dimensions’’ (to appear in Deep Sea Research)]. The signals that are transmitted are designed to have flat cross-correlation properties. The receiver algorithm exploits this property of the transmitted signal set and works by iteratively isolating progressively weaker targets at each iteration step. An important feature of the structure is the ability to adapt the threshold of the detectors of different signals to targets of various strengths. The algorithm leads to a receiver structure which is a modification of the classical parallel matched filter bank to detect targets and estimate their parameters. Experiments were performed in a tank to test the receiver structure. Various objects were suspended in known configurations and then two signals were transmitted at them. The algorithm was successfully able to isolate the targets and estimate their positions and strengths. [Work supported by NSF Grant No. OCE 9421876.]

No abstract