Sonar echoes from unresolved features tend to interfere with each other. When a sonar is moved through an area where features of interest are not resolved, echoes will fluctuate from ping to ping due to the interferences. These fluctuations are the subject of this paper. We classify both fish and the rough seafloor by analyzing the nature of echo fluctuations. Similar statistical techniques apply to all of the problems. We use the techniques to determine, from echo fluctuations, parameters that describe the physical situation. Fish: Two conditions are low density and high density of fish (density is defined as number of fish per unit volume), a) In the low-density case, fish are resolved and their individual echoes are distinguishable from each other. From single fish there are interferences between echoes from the anatomical features causing fluctuations. Echoes from resolved fish also fluctuate because of beampattern effects. After deconvolution (or "removal") of beam-pattern effects, echo amplitudes from resolved fish fit a Rician probability density function (pdf). b) In the high-density case, the fish are not resolved and echoes from individual fish overlap. These echoes interfere and cause the echoes to fluctuate. The Rayleigh pdf describes the instantaneous echo amplitude from a cloud or school of fish. We process echoes by picking the peak amplitude in a finite-time gate and obtain an extremal pdf. We examine both regions of density (a) and (b) and present methods we have developed to determine, from the nature of the fluctuations, properties such as fish size frequency distribution and possibly gross anatomical features, fish density, and to count occasional large fish swimming in a cloud of plankton or near the sea surface. Seafloor: Interference of echoes from individual protuberances such as rocks, nodules, and ripples causes fluctuations. The Rice pdf describes echo amplitudes from the seafloor. We combine Eckart acoustic-scattering theory for a downward-looking sonar and Rice statistics. As a result we describe echo fluctuations in terms of rms roughness of the seafloor and correlation area (product of x and y correlation distances) of the seafloor. We use boomer data to estimate seafloor microrelief as well as to predict echo fluctuations for a variety of other sonars.

Sonar echo statistics as a remote-sensing tool: Volume and seafloor

Acoustic technology is an accepted and important component of aquatic research and resource management. Despite the widespread use of echosounders, few guidelines aid in the choice of appropriate sonar system parameters for acoustic surveys. Choice of acoustic carrier frequency is analogous to the choice of spotlight colour used to illuminate a painting. Thr ee primary biological factors influence the scattering of sound by aquatic organisms: swimbladder presence, organism length, and organism behaviour. We illustrate the influence of these factors on the amplitude of backscattered echoes using a Kirchhoff-ray mode scattering model to quantify fish and zooplankton backscatter as a function of carrier frequency, fish length, and swimbladder aspect. Model results illustrate that echo amplitudes from aquatic organisms are largely dependent on the presence or absence of a swimbladder. Target strengths generally increase with increasing carrier frequency and organism length. Swimbladder angle relative to the incident sound wave affects scattering amplitudes at all frequencies. Measurements of backscatter from swimbladdered fish are relatively robust when the ratio of fish length to acoustic frequency wavelength ranges between 2 and 10. As fish length to frequency wavelength ratios increase, echo amplitudes become more dependent on aspect and peak when the swimbladder is perpendicular to the acoustic wavefront.

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Sonar systems and aquatic organisms: matching equipment and model parameters

Target strength (TS) may be estimated as a function of fish length (L) by comparing in situ acoustic measurements with the fish size distribution from trawl catches. The acoustic and fishing data are directly comparable only if they are samples from the same population, but the TS measurements depend on the detection of isolated targets which may not be representative of the ensonified population. Errors may occur through the false detection of multiple targets, and the size-dependence of schooling density means that larger fish are more likely to be detected. We show that such effects can result in the estimated TS being biased high. We describe a stochastic method for estimating the constant b in the formula TS=20 Log (L)−b, by a least-squares fitting procedure. It is assumed that the echo-amplitude has a Rayleigh distribution. The method has been applied to data from surveys of cichlids in Lake Malawi. From 33 independent measurements of Diplotaxodonspp. around 15 cm in length, b is 67.4±0.2 dB.

Interpretation of in situ target-strength data

A unified framework is presented for examining the performance of linear mode filtering algorithms. Two common mode filters, samples of the mode shapes and the pseudo-inverse of the mode shapes, are presented in this framework as a tradeoff between sensitivity to other modes and sensitivity to white noise. The maximum a posteriori mode filter is presented as an alternative which gracefully transitions between these extremes, and attains the minimum mean squared error when the modes to be estimated are well modeled as samples of a Gaussian random process. Numerical simulations in both shallow and deep water environments confirm the analytically derived properties of these mode filters.

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A unified framework for mode filtering and the maximum a posteriori mode filter

Comparison of target strength distributions and fish densities obtained with split and single beam echo sounders

The probability density function (PDF) of the peaks of the envelopes of sonar echo from live fish were measured at beam aspect. The measurements were made at 220 kHz and in a waveguide. The fish was the common shiner (Notropis cornutus) and was about 120 mm (about 18 acoustic wavelengths) long. The PDF of the echoes was approximately Rayleigh when the fish was moving gently. The backscattering cross section equaled 4.2×10−5 m2. Transformation of the PDF’s to a target strength display in decibels displaced the maximum of the PDF to the target strength equaling 10 log10 (σbs/A0)+3 dB where σbs is the mean backscattering cross section and A0=1 m2. The target strengths of the common shiner (120 mm) and the mummechog (Fundulus heteroclitus, 100 mm) were measured as a function of aspect angle. Comparison of the experimental measurements and Love’s empirical target strengths for any aspect showed that the measured target strengths at broadside aspect were about the same and the target strengths at other aspect a...

Backscattering cross sections of live fish: PDF and aspect

Our purpose was to make ’’farfield’’ sound scattering measurements in a limited space. We used a thick waveguide, about 35 acoustic wavelengths deep, and excited it in the first mode. The waveguide had pressure release surfaces on the top and bottom. To excite and receive in the first mode, we used a vertical array that was amplitude shaded to match the eigenfunction of the first mode. Experimental measurements verified that 90% of the energy was in the first mode. A pair of omnidirectional transducers were used as a probe transmitter and receiver to calibrate the system for scattering measurements. At 220 kHz, 24‐cm depth, and 100‐cm range, the cross section of the scattering region was about 6 cm high. At this range the first Fresnel zone was 10 cm wide. Scattering measurements of the target strength of a steel sphere, diameter 0.8 cm, gave −54±1 dB compared to −54 dB theoretical target strength.

Kung Huang

Papers

Backscattering cross sections of live fish: PDF and aspect

Single mode transmission and acoustic backscattering measurements in a laboratory waveguide