WO2001018562A1 - Procede de detection de poissons a l'aide de donnees sonar - Google Patents

Procede de detection de poissons a l'aide de donnees sonar Download PDF

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Publication number
WO2001018562A1
WO2001018562A1 PCT/NO2000/000288 NO0000288W WO0118562A1 WO 2001018562 A1 WO2001018562 A1 WO 2001018562A1 NO 0000288 W NO0000288 W NO 0000288W WO 0118562 A1 WO0118562 A1 WO 0118562A1
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WIPO (PCT)
Prior art keywords
echogram
echo
filter
objects
dimension
Prior art date
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PCT/NO2000/000288
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English (en)
Inventor
Helge Balk
Torfinn Lindem
Original Assignee
Helge Balk
Torfinn Lindem
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Priority claimed from NO994327A external-priority patent/NO994327D0/no
Application filed by Helge Balk, Torfinn Lindem filed Critical Helge Balk
Priority to AU70432/00A priority Critical patent/AU7043200A/en
Priority to EP00959043A priority patent/EP1210618A1/fr
Priority to CA002383760A priority patent/CA2383760A1/fr
Publication of WO2001018562A1 publication Critical patent/WO2001018562A1/fr
Priority to NO20021069A priority patent/NO20021069L/no

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Classifications

    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
    • G01S7/52—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S15/00
    • G01S7/523—Details of pulse systems
    • G01S7/526—Receivers
    • G01S7/527—Extracting wanted echo signals
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S15/00—Systems using the reflection or reradiation of acoustic waves, e.g. sonar systems
    • G01S15/02—Systems using the reflection or reradiation of acoustic waves, e.g. sonar systems using reflection of acoustic waves
    • G01S15/06—Systems determining the position data of a target
    • G01S15/46—Indirect determination of position data
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S15/00—Systems using the reflection or reradiation of acoustic waves, e.g. sonar systems
    • G01S15/88—Sonar systems specially adapted for specific applications
    • G01S15/96—Sonar systems specially adapted for specific applications for locating fish
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
    • G01S7/52—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S15/00
    • G01S7/539—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S15/00 using analysis of echo signal for target characterisation; Target signature; Target cross-section

Definitions

  • the invention relates to a method for analysing data from single-beam, double-beam and split-beam echo sounders, preferably for the detection offish.
  • echoes from individual objects are detected and their origin determined.
  • Data in this case means digitised echo information recorded using a vertical or horizontal, stationary or mobile echo sounder in a river, a watercourse, a lake or the sea.
  • Individual objects may be fish swimming alone, but may also be objects of any other type that are the target of a study.
  • an echo sounder is only capable of measuring distance to an object in the water.
  • a short sound pulse is emitted, and the echo sounder measures the time interval between the emission of the pulse and the return of its echo. With knowledge of the speed of sound, the distance can then be calculated.
  • a continuous echo signal will be generated after the emission of a sound pulse because all changes of density in bodies of water will reflect some energy back to the echo sounder. After some time the signal emitted will be so weak that it will not be possible to measure any more echoes, and then a new sound pulse can be emitted.
  • echo sounders equipped with several listening elements having different geometric orientations are used.
  • the three-dimensional position of an object can be determined on the basis of time differences in the echo. This gives a total of five dimensions: time, intensity, distance and two angular positions.
  • Echo sounders equipped with means for determining the position of objects in the beam are often called SoNaR (Sound Navigation and Ranging), and not echo sounders.
  • SoNaR Sound Navigation and Ranging
  • a much used five-dimensional echo sounder is Simrad's EY500 split-beam sounder, which employs four listening elements.
  • Bottom echoes are one example of such objects
  • a multi-dimensional image or echogram can be generated that shows the development of the echo intensity over time within the range of the sounder
  • This image contains information about passing objects as well as information about the general level of background reflection of the waters, and it is therefore important to be able to distinguish between echoes from background and echoes from rigid objects
  • the single echo detector may start to detect echoes based on the background noise, and it may start to reject echoes from target objects. This makes its difficult for both humans and automatic methods to identify the target objects in the SED echograms. Automatic methods will tend to generate quantities of tracks based on noise echoes whilst tracks from target objects are overlooked, divided into many smaller tracks or mixed with the noise echoes. Examples of sonar echograms with good and poor noise to sound ratio are shown in Figure 8 and Figure 9. Sonar data with low signal to noise ratio is found in particular in shallow rivers where noise production is great, but also when measuring small objects and when measuring at a great distance because the sound intensity decreases by 1/R ⁇ 4 where R is distance in metres.
  • the reason echoes from target objects are rejected in the SED detector at a low signal to noise ratio is that they fail to satisfy one or more of the demands made by the detector.
  • the echo signal from fish can be rejected both because of multi-peaks, unduly long pulse duration and excessive spread in the angle measurements.
  • Fig. 1 is a schematic illustration of the principle of a standard hydroacoustic measuring method. From the echo sounder sound passes through a Time Variable Gain amplifier (TVG) which compensates for geometric loss of echo intensity. An amplitude detector is then used to remove the carrier frequency before the amp echogram can be shown. In split-beam echo sounders, a four-channel amplifier is used and also a phase detector.
  • TVG Time Variable Gain amplifier
  • Fig. 2 shows a SED echogram recorded using a horizontal, stationary echo sounder in a river.
  • the SED echogram shows many echoes from background noise. Some echoes may originate from passing fish.
  • the relatively even horizontal lines are produced as a result of stationary bottom structures. (The vertical axis is distance from the echo sounder in metres whilst the horizontal axis indicates time.)
  • Fig. 3 is a block diagram of the main elements of the new method of analysis.
  • Fig. 4 shows the principle of thresholding on cross-filtration. The result of filtrations and subsequent thresholding is also shown as 3D echograms in the attachment.
  • Fig. 5 shows example of echograms including small regions containing echoes from noise and larger regions containing echoes from fish and drifting objects.
  • Fig. 6 is a block diagram showing combined use of pulse peak and single echo detection in order to detect and evaluate tracks in a detected region. Pulse peaks are indicated by round dark dots. Single echo detection uses angle and amplitude data from the detected regions on the basis of detected pulse peaks. In this example the tracking algorithm finds that the region contains echoes from one object. The two pulse peaks that could have formed an additional track are rejected by the demand for a minimum number of echoes.
  • Fig. 7 shows an example of a detected region with pulse peaks. Only one region is shown, but it has two branches. In the middle of each branch there are pulse peaks from objects which upon subsequent analysis show a movement against the current. It is therefore highly probable that the tracks represent salmon.
  • Original data was recorded using a horizontal split-beam sounder in the river Tana in the summer of 1999. The objects passed the sounder on 19 July at 1325 hours at a distance of 31 metres. Classification to determine the origin of the objects.
  • Fig. 8 shows an example of angle data for a detected object.
  • the ellipse indicates the cross-section of the emitted ultrasonic beam, whilst the axes show angle in relation to beam centre. Calculation of direction of travel and velocity shows that this object is moving against the current at a speed of 0.59 m/sec. It is then easy to classify the object as a fish migrating upstream. +alo indicates angle to the surface whilst +ath indicates angle to the current direction.
  • Fig. 9 is an example of an echogram resulting from vertical recording of small fish in calm water. The recording was made under ice in a Norwegian lake called Semsvannet in March 1999, and is an illustration of good signal to noise ratio with calm and weak background noise.
  • Fig. 10 is an example of an echogram resulting from a horizontal recording of large fish in a river. The figure illustrates low signal to noise ratio with great variations in the background intensity.
  • Fig. 11 is an example of an echogram of two fish in the river Tana. Original 3D echogram. Horizontal echo sounder.
  • Fig. 12 is an example of an echogram of two fish in the river Tana. Data has been filtered using a median 3x7 filter to highlight objects and remove noise.
  • Fig. 13 is an example of an echogram of two fish in the river Tana. Data has been filtered using a 55x7 median filter to detect background.
  • Fig. 14 is an example of an echogram of two fish in the river Tana.
  • the threshold with the background image as threshold value.
  • Fig. 15 is an example of the processing of an echogram having a particularly poor signal/noise ratio of: A) an SED echogram; B) an amp echogram;
  • ig 16 shows an echogram as a result of median pass filtration using different filter dimensions Dimensions are given as height times width It can be seen how long, narrow filters suppress target objects, whilst medium width, short filters suppress noise whilst the useful signal is highlighted
  • Fig 17 illustrates the principle for selection of critical frequencies in the filter, in this case shown only for one dimension
  • An amp echogram contains more information than the SED echogram More echoes from fish, pulse width, pulse shape and surroundings
  • Point 1 indicates that we must reduce noise and increase the number of echoes in tracks from fish in order to be able to improve the method
  • Point 2 indicates that we should use the amplitude echogram rather than the SED echogram
  • Point 3 indicates that we can make use of certain properties in the echogram for the detection target objects
  • Point 4 indicates that we should focus on distance estimates when combining echoes
  • the method can be used for single-beam and multi-beam echo sounders (Single-beam, dual-beam and split-beam)
  • Single-beam, dual-beam and split-beam The use of multi-beam echo sounders, where relative position in the beam can be calculated, provides a greater basis for making the object analysis, but otherwise the analysis is the same for all types of sounders
  • Elements that affect the method are distance and time resolution in the amplitude echogram I e , the number of emitted sound pulses (pings) per second and the number of samples per metre This affects the choice of filter dimensions that are to be used In our tests we have mainly used about 5 shots per second and 9 cm per sample With EY500 from Simrad we can obtain as much as 3 cm depth resolution per sample This has been used in some tests, but results in slow data processing and vast amounts of data
  • Recording and registration of sonar data is done in the traditional manner in that ultrasonic signals in the volume that is to be measured are repeatedly emitted, and that echoes from reflecting objects and ultrasonic signals in the volume being measured are received, amplified and registered.
  • the distance to the source of the echo can also be calculated as an alternative to the time interval between the emission time of the ultrasonic signal and the reception time of the echo signal.
  • the signals are digitised.
  • the registration is preferably made in a two-dimensional data presentation, where distance, alternatively the echo time, constitutes one dimension, and the sequence number of the measurement, alternatively the time of measurement, constitutes the other dimension.
  • data that is stored in the elements in this two-dimensional presentation will only comprise the intensity of the received signal, but in the case of other sonar types it will also include indications of direction of the source of the received signal.
  • Low-pass filtration is important for two reasons.
  • the filtration removes noise and it reduces the problems of missing echoes in tracks.
  • the amplitude in an echogram can vary greatly from ping to ping and from sample to sample. Rapid variations are often associated with noise, and we remove this noise by filtering. A second but important reason is that we wish to fill in the missing echoes in tracks from target objects. The selection of filters with dimensions that cover several pings will ensure that a little of the echo energy from pings before and after the missing echo will be transferred to the missing echo.
  • the filter dimensions are important for a number of reasons. Because of the time aspect in the echograms, tracks are more or less horizontally oriented. I.e., vertically narrow and horizontally broad. By using filters that are broad and narrow, we will therefore be able to highlight and smooth useful tracks at the same time as we reduce background noise. Filters with the opposite orientation will reduce both useful signals and sound. (See filter examples in figs.) The best result is achieved using filter dimensions that are somewhat narrower and shorter than the tracks from the useful signals. Segmentation
  • segmentation involves separating signals from background noise Several techniques are common in the field of image processing, but we have found that segmentation based on thresholding works best for sonar data Because echograms often do not have a constant background level, we cannot use a constant threshold value The echo intensity varies both with time and with distance from the transducer and we have therefore developed a special adaptive thresholding method (adaptable thresholding)
  • a two- dimensional filter has a dimension along two normal axes in a Cartesian coordinate system
  • the size of the filter is described by the dimensioning or the number of cells along the two normal axes that are referred to
  • the filter dimension 3 x 5 will thus mean that we have a two-dimensional filter with three elements along one of the axes of dimension (y axis) and five elements along the other axis of dimension (x axis)
  • the x axis will measure increasing ping number
  • the y axis will measure sample number for echoes received after each individual ping
  • One dimension will highlight useful tracks, whilst another dimension will reduce the tracks
  • a foreground filter is composed of a low-pass filter that removes high-frequency noise without removing the useful signal that exists at lower frequencies
  • a background filter removes both high-frequency noise and useful signals, but nevertheless maintains the "background intensity" that consists of unwanted signals at frequencies below the frequencies of the useful signal, and any
  • the size of the target objects and optimum filter dimensions are now found by a manual method
  • a small, but representative set of the objects that are to be detected or removed is chosen manually from the collected echograms
  • the size of the foreground filter is adjusted so that width and height are less than or equal to width and height of the smallest of these objects
  • the size of the background filter is chosen so that it is larger than the largest of the desired objects
  • the term "larger than” in this case is used to mean higher or wider, or higher and wider
  • For echograms from horizontally placed echo sounders in a shallow river we have obtained particularly good results when we have used a foreground filter of 1 x 3 (height x width) and a background filter of 1 x 99
  • the echogram resolution was then 9 cm per sample and 5 pings per second These values are used in the counting test shown
  • typical filter sizes could be: foreground filter: height - 1 to 5 samples, width - 1 to 11 pings; background filter, height - 1 to 55 samples, width - 1 to 99 pings.
  • a two-dimensional filter has two critical frequencies, one along each coordinate axis. This provides plenty of scope for finding filter sizes that give critical frequencies capable of maintaining background and unwanted echo signals at the same time as it is able to remove useful signals.
  • a 1 x 99 filter is used as background filter. This filter removes echoes from fish because it is considerably wider than the fish echo tracks.
  • background and unwanted echoes from stones and other stationary objects are kept because these echo tracks are considerably shorter and wider than the height and width of the background filter.
  • regions which may contain echoes from target objects. Besides the target objects, we may still also have regions containing noise and regions containing echoes from unwanted objects such as the bottom, boats, wakes or the like.
  • regions containing noise and regions containing echoes from unwanted objects such as the bottom, boats, wakes or the like.
  • By studying the appearance of the detected regions we are able to say a great deal about the origin of the regions and thus remove regions where there is a low probability of their containing echoes from target objects.
  • Many properties of a region's shape can be calculated; e.g., area, height/width ratio, centre of gravity, branches, rotation and frequency ranges for the outline. For horizontal sonar recordings using a stationary echo sounder in a river, four main types of regions are found.
  • regions containing residual background noise are: a) regions containing residual background noise; b) regions containing echoes from moving objects such as fish and drifting objects, c) regions containing echoes from stationary objects such as stones on the bottom, and d) regions containing echoes from the wake of boats. These differ greatly from one another as regards many of the said parameters, and when fish are of interest we can in a relatively easy manner remove regions of the type a, c and d In this way we increase the probability of the remaining regions containing fish or drifting objects
  • Regions containing a number offish will often be wider and have a more branched contour than regions containing echoes from a single object
  • Pulse peak detection to form dense tracks suitable for tracking Single echo detection to find the angular position and measurement intensity correction tracking.
  • an automatic analysis may cause problems owing to interference and masking effects between objects.
  • the object closest to the echo sounder can more or less shield objects located behind it.
  • An alternative strategy would then be to store the position of such multiple object regions and then evaluate them manually afterwards.
  • pulse peak detection should be combined with a low-pass filter that is vertically oriented. I.e., that it has a greater extension in the distance domain that in the time domain. This reduces the number of pulse peaks from random objects.
  • pulse peak detection should normally be carried out on the track and not on the basis of single pings. In the case of certain types of data, pulse peak detection has been found to give too many peaks within a detected region.
  • One possible solution may be to draw in criteria associated with single echo detection such as pulse duration.
  • Pulse peak detection gives denser tracks and therefore a better basis for joining echoes to give tracks than single echo detection.
  • a river we will often find tracks from fish where not a single echo is accepted by the single echo detector. Nevertheless we obtain excellent tracks with the aid of pulse peak detection. When using the traditional method these tracks would be overlooked.
  • the classification involves an evaluation of the objects as regards one or more calculated properties in order to determine the object type.
  • other data relating to the objects such as, for example, data indicating the movement pattern of the objects in the volume covered by the echo sounder or sonar, will be evaluated against criteria of a similar type during the classification. All properties that are calculated in the shape and region analysis can be used to determine the origin of the detected individual objects. In rivers in particular, the direction of travel and velocity in relation to water current will be important criteria.
  • Single beam Calculation of time/distance angle to find velocity and direction
  • Split beam Analysis of angles of the pulse peaks to find velocity and direction.
  • the echo sounder is slightly angled relative to the objects that pass by, the objects that pass one way will give tracks at positive angles, whilst objects that pass the other way will give tracks at negative angles.
  • This method can be used for all types of echo sounders.
  • the angle measurement is likely to be more unreliable than the distance measurement, both because of the way in which the echo sounder detects the angles and because of physical conditions around one of the sonar recordings.
  • the echo sounder In vertical measurements from a boat the echo sounder will be apt to change angle so that passing fish will "jump and dance" around in the beam.
  • the echo sound In a river the echo sound will be affected by the turbulence of the water at the same time as the actual echo sounder will vibrate in the water current.

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  • Engineering & Computer Science (AREA)
  • Radar, Positioning & Navigation (AREA)
  • Remote Sensing (AREA)
  • Physics & Mathematics (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • General Physics & Mathematics (AREA)
  • Acoustics & Sound (AREA)
  • Measurement Of Velocity Or Position Using Acoustic Or Ultrasonic Waves (AREA)

Abstract

L'invention concerne un procédé de détection d'objets, des poissons de préférence, à l'aide de données sonar. Des signaux d'écho provenant de mesures sonar répétées sont numérisés et reproduits dans une présentation de données bidimensionnelle où la distance de l'écho, alternativement la durée du signal, constitue la première dimension, et où le numéro de mesure, alternativement le temps de la mesure, constitue la deuxième dimension. Une fois obtenu le format désiré de la présentation de données, un filtrage bidimensionnel, une fixation d'un seuil adaptif, et un traitement morphologique sont appliqués afin de produire un échogramme présentant moins de bruits et une détection plus fiable des objets désirés. Une analyse de formes supplémentaire permet d'améliorer la détection.
PCT/NO2000/000288 1999-09-06 2000-09-05 Procede de detection de poissons a l'aide de donnees sonar WO2001018562A1 (fr)

Priority Applications (4)

Application Number Priority Date Filing Date Title
AU70432/00A AU7043200A (en) 1999-09-06 2000-09-05 Fish detection method using sonar data
EP00959043A EP1210618A1 (fr) 1999-09-06 2000-09-05 Procede de detection de poissons a l'aide de donnees sonar
CA002383760A CA2383760A1 (fr) 1999-09-06 2000-09-05 Procede de detection de poissons a l'aide de donnees sonar
NO20021069A NO20021069L (no) 1999-09-06 2002-03-04 Fremgangsmåte ved fiskedeteksjon fra sonardata

Applications Claiming Priority (4)

Application Number Priority Date Filing Date Title
NO19994327 1999-09-06
NO994327A NO994327D0 (no) 1999-09-06 1999-09-06 Forbedret fiskedeteksjonssannsynlighet i data fra sonar med delt strÕle
NO20003543 2000-07-10
NO20003543A NO20003543L (no) 1999-09-06 2000-07-10 FremgangsmÕte ved fiskedeteksjon fra sonardata

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WO2001018562A1 true WO2001018562A1 (fr) 2001-03-15

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PCT/NO2000/000288 WO2001018562A1 (fr) 1999-09-06 2000-09-05 Procede de detection de poissons a l'aide de donnees sonar

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EP (1) EP1210618A1 (fr)
AU (1) AU7043200A (fr)
CA (1) CA2383760A1 (fr)
NO (1) NO20003543L (fr)
WO (1) WO2001018562A1 (fr)

Cited By (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP2093546A1 (fr) * 2008-02-22 2009-08-26 Siemens Milltronics Process Instruments Inc. Procédé de localisation d'un écho souhaité à partir d'échos non désirés dans un système de mesure de niveau de temps de vol
WO2010102170A1 (fr) * 2009-03-06 2010-09-10 Johnson David A Dispositif pour trouver des poissons
CN103376145A (zh) * 2012-04-24 2013-10-30 克洛纳测量技术有限公司 用于确定介质的填充深度的方法和对应的装置
GB2523561A (en) * 2014-02-27 2015-09-02 Sonardyne Internat Ltd Underwater environment reference map enhancement apparatus, underwater intruder detection system, method of processing a reference map and method of detecting
CN106019263A (zh) * 2016-07-13 2016-10-12 东南大学 基于多亮点回波模型的目标径向速度测量方法
CN110568444A (zh) * 2018-06-05 2019-12-13 艾尔默斯半导体股份公司 通过反射超声波检测障碍物的方法

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CN113484867B (zh) * 2021-06-25 2023-10-20 山东航天电子技术研究所 一种基于成像声呐封闭空间下鱼群密度探测方法

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Cited By (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP2093546A1 (fr) * 2008-02-22 2009-08-26 Siemens Milltronics Process Instruments Inc. Procédé de localisation d'un écho souhaité à partir d'échos non désirés dans un système de mesure de niveau de temps de vol
WO2010102170A1 (fr) * 2009-03-06 2010-09-10 Johnson David A Dispositif pour trouver des poissons
US8164983B2 (en) 2009-03-06 2012-04-24 Johnson David A Fish finder
CN103376145A (zh) * 2012-04-24 2013-10-30 克洛纳测量技术有限公司 用于确定介质的填充深度的方法和对应的装置
GB2523561A (en) * 2014-02-27 2015-09-02 Sonardyne Internat Ltd Underwater environment reference map enhancement apparatus, underwater intruder detection system, method of processing a reference map and method of detecting
GB2523561B (en) * 2014-02-27 2016-03-02 Sonardyne Internat Ltd Underwater Environment Reference Map Enhancement and Intruder Detection
CN106019263A (zh) * 2016-07-13 2016-10-12 东南大学 基于多亮点回波模型的目标径向速度测量方法
CN110568444A (zh) * 2018-06-05 2019-12-13 艾尔默斯半导体股份公司 通过反射超声波检测障碍物的方法

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NO20003543L (no) 2001-03-07
CA2383760A1 (fr) 2001-03-15
EP1210618A1 (fr) 2002-06-05
NO20003543D0 (no) 2000-07-10
AU7043200A (en) 2001-04-10

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