The hydro–acoustic technology has been widely used in not only South Korea but also many foreign countries for various scientific purposes. Unfortunately acoustic data especially collected from field surveys may contain noises caused by a variety of sources. Therefore, it is exceedingly important to eliminate noises when acoustic data are analyzed to derive quantitative results. This study introduced two methods for eliminating noises easily and effectively using post–processing software. Used acoustic data were collected on the Jinhae bay and Tongyeong coast of the South Sea in April 2015. The first method, that is the Wang’s method, placed emphasis on ‘erosion filter’ to eliminate only data samples contaminated by noises. The second method (Yamandu’s method) focused on the ‘resample by number of pings’ to remove pings contained noises. To substantiate the effectiveness of two methods, the mean Sv (Volume backscattering strength), mean height and depth of the fish schools detected were compared between before and after using the noise elimination methods. In the Wang’s method the mean Sv was decreased from –52.4 dB to –52.9 dB, and in the Yamandu’s method from –52.6 dB to –53.3 dB, indicating that noises were successfully eliminated. The mean height (1.5 m) and depth (19.0 m) were same between before and after using two methods showing that the shapes of fish schools were not changed.

The multi-frequency characteristics of anchovy schools were investigated using six acoustic lines collected at 38 and 120 kHz while a primary trawl survey was conducted from 14 April and 18 April of 2014 in off the coast of Tongyeong and Geo–je. Here, the frequency characteristics mean ΔMVBS that is the difference of Mean Volume Backscattering Strength at two frequencies. To use the characteristics effectively, the optimal cell size (10×2 m) was determined by examining several different cell sizes in consideration with the shapes of fish schools and the ΔMVBS pattern. By examining 6 histograms of ΔMVBS, afternoon groups were occupied more in the ΔMVBS range of –6~–4 dB than that of –4~–2 dB, comparing to morning groups. The ΔMVBS range of the morning groups was between –16.9 dB and 11.6 dB, and that of the afternoon groups –16.7 dB and 13.0 dB. The average and standard deviation were –3.9±3.6 dB in the morning and –4.1±3.4 dB in the afternoon, suggesting that morning groups were 2 dB higher than afternoon groups. The ΔMVBS range of all anchovy schools regardless of morning and afternoon was between –16.9 dB and 13.0 dB, their average ΔMVBS was –4.1±3.5 dB. The characteristics can support to identify anchovy species in the waters where multiple fish species are distributed. It is hoped that this study presents the availability and benefit of acoustic data from a primary trawl survey.