An operational system for processing and visualizing multi-frequency acoustic data

Rolf J. Korneliussen Egil Ona Calibrated and digitized data from two or more discrete echosounder frequencies can be combined for the purpose of separating and extracting the acoustic scattering from zooplankton and fish in mixed recordings. This method is also useful for quantifying the relative contribution of each frequency to the total acoustic-backscattering when scrutinizing records in large-scale, acoustic surveys. Echosounder hardware requirements are defined which would permit the ideal extraction of such information. These include calibration, transducer specification, pulse resolution and digital representation of the signals. During this initial study a special version of the Simrad EK500 multi-frequency, split-beam echosounder and the Bergen Echo Integrator (BEI) post-processing system were used. The echosounder transmitted pulses simultaneously at four frequencies, 18, 38, 120 and 200 kHz and transferred the received signals to the post-processing system in calibrated, raw, digitized format. Methods are described for echogram manipulation and for the construction of new, synthetic, combinedfrequency [c(f)] echograms. Examples of extracted scattering information from mixed layers of fish and small scattering-organisms, such as copepods and euphausiids, are shown, and the potential of the method is discussed. 1054-3139/02/040293+21 $35.00/0 - Introduction Acoustic methods are used widely now for estimating fish abundance (Nakken and Ulltang, 1983; Jakobsson, 1983; Aglen, 1989; MacLennan & Simmonds, 1992) and echo integration at one frequency, supported by biological sampling, is the general method used (MacLennan, 1990). Scrutiny of acoustic data is generally done by analyzing and correcting echograms in digital format using a dedicated post-processing system, e.g. Bergen Echo Integrator (Foote et al., 1991; Korneliussen, 1993), BI500 (Anon., 1993a, b), EP500 (Lindem et al., 1993), EchoView (Anon., 1999) or ECHO. Within these systems echogram recordings are subject to manipulation, thresholding, error-checking and noise removal. During the scrutinizing process it is possible to re-arrange and control the depth layers for which the fish density is to be measured. A team of experienced operators interprets acoustic data by drawing lines and encircling schools on the echogram screen. Supported by data from biological and oceanographic measurements this process allows them to separate, isolate, and allocate the different acoustic structures to species and groups of scatterers. In most surveys identification and separation of one or two target species is the main goal with the rest of the recordings of less importance. Within acoustic-surveying methodology there is an incessant call for improvement in order to reduce ambiguity in the interpretation of acoustic data and thereby reduce the uncertainty of acoustic abundance estimates. Species identification was seen by MacLennan and Holliday (1996) as The grand challenge of fisheries and plankton acoustics. Considerable potential for improvement may be derived from the echogram interpretation process of Mathisen et al., 1974; Korsbrekke and Misund, 1993; Misund, 1997. An enhancement of the echogram interpretation process is desirable by utilizing multi-frequency information for species discrimination. Concurrently collected multifrequency data, combined with an improved knowledge of the backscattering properties of the observed animals, a typical species mix, and the size distribution, may be used to characterize acoustic returns and thereby improve the scrutinizing process. Multi-frequency data have been used since the late 1970s to identify and quantify the scattering from zooplankton (Greenlaw, 1977; Holliday 1977; Holliday and Pieper, 1980). Madureira et al. (1993) used 38 and 120 kHz data to discriminate between Antarctic krill and other scatterers. Stanton and his co-authors have on several occasions investigated backscattering from three different zooplankton groups; gas bearing, hard elasticshelled, and fluid-like, both experimentally (Stanton, 1994, 1998a) and theoretically (1998b) to categorize and reduce some of the great diversity in scattering by zooplankton. The models incorporate the orientation distribution of euphausiids (Chu et al., 1993). Models for acoustic classification of zooplankton have been incorporated into two algorithms by Martin et al. (1996). These were applied with reasonable success on high-frequency, broadband data. For fish the multifrequency information has been utilized only on rare occasions (Love 1971, 1977; Lvik et al., 1982; Lvik and Hovem, 1979; Foote et al., 1992; Foote et al., 1993; Simmonds et al., 1996) but seldom for stock assessment surveys. For improvements under practical survey conditions the operator of the post-processing system needs tools for analysing combined multi-frequency echograms and sequences of single frequency [s(f)] echograms. Most of the available systems were originally intended for either s(f) analysis, or sequential analysis of several frequencies, although a few examples designed for the combined analysis of two frequencies have recently appeared (Socha et al., 1996; Higginbottom et al., 2000). In some systems, layer lines and parameters for scrutiny, which are selected during s(f) analysis, can be transferred readily between echograms along the survey track (Foote et al., 1991). These can also cross frequencies (Korneliussen, 1993, 2000a), but few attempts have been made to combine the information in real-time, or near real-time, for direct presentation to the operator. A practical approach is to incorporate into the postprocessing system both the empirical relationships of frequency-dependent backscattering and, as a start, simple models of backscattering from spheres (Johnson, 1977) or cylinders (Stanton et al., 1994), to discriminate between acoustic categories. The extraction of basic differences in the acoustic-scattering properties of various size groups, or species of fish and zooplankton, from simultaneous, multi-frequency recordings, as well as synthesis of this information numerically and visually, have been investigated (Korneliussen, 1999). The main objective of the present work was to develop a system for near real-time analysis of multi-frequency acoustic data. Its focus was the need for rapid scrutiny during large-scale acoustic surveys because this is a very time-consuming task. For fish stock assessment purposes the Institute of Marine Research (IMR) Bergen, collects acoustic data continuously during about 2000 research vessel survey-days each year. Developing systems for improving survey efficiency, as well as accuracy and repeatability, is therefore of significant importance. Materials and methods System description outline of processing modules Acoustic data are recorded from one or more Simrad EK500 echosounders with vertically-directed transducer beams (Bodholt et al., 1989). Each echosounder may include three tr (...truncated)