• Journal of the Society of Naval Architects of Korea
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• v.42 no.4 s.142
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• pp.299-306
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• 2005

To determine a guidance law which is suitable for Target Tracking System(TTS) of an underwater vehicle, the performance (hitting probability) of TTS were calculated with four different guidance schemes, considering underwater vehicle's manoeuvrability and characteristics of seeking equipment such as sonar To evaluate the performance of TTS with each guidance law, numerous target-tracking simulations of underwater vehicle were performed under the condition of target's various motion scenario. Furthermore, the effect of sonar characteristics to the performance of guidance law in TTS was studied by changing parameters of sonar such as frequency of ping and detecting error of target. The pursuit-tail guidance law showed the best performance among four different guidance laws. Complex motion of target from straight line to turning circle and zigzag movement, low frequency of sonar ping and large detecting error of target decreased the hitting probability.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.5
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• pp.632-637
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• 2008

In real system application, the propeller shaft rate (PSR) estimation algorithm for the feature extraction of the sonar target operates with the following problems: it requires both accurate and efficient the fundamental finding method because it is essential and difficult to distinguish harmonic family composed of the fundamental and its harmonics from the multiple spectral lines in the frequency spectrum-based sonar target classification, and further, it requires an easy design procedure in terms of its structures and parameters. To solve these problems, an evolutionary PSR estimation algorithm using an expert knowledge and the evolution strategy, is proposed. To verify the performance of the proposed algorithm, a sonar target PSR estimation is performed. Simulation results show that the proposed algorithm effectively solves the problems in the realtime system application.

• Fisheries and Aquatic Sciences
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• v.14 no.3
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• pp.218-225
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• 2011

Dual frequency identification sonar (DIDSON) is an imaging sonar that has been used for numerous fisheries investigations in a diverse range of freshwater and marine environments. The main purpose of DIDSON is fish counting, fish sizing, and fish behavioral studies. DIDSON records video-quality data, so processing power for handling the vast amount of data with high speed is a priority. Therefore, a semiautomated analysis of DIDSON data for fish counting, sizing, and fish behavior in Echoview (fisheries acoustic data analysis software) was accomplished using testing data collected on the Rakaia River, New Zealand. Using this data, the methods and algorithms for background noise subtraction, image smoothing, target (fish) detection, and conversion to single targets were precisely illustrated. Verification by visualization identified the resulting targets. As a result, not only fish counts but also fish sizing information such as length, thickness, perimeter, compactness, and orientation were obtained. The alpha-beta fish tracking algorithm was employed to extract the speed, change in depth, and the distributed depth relating to fish behavior. Tail-beat pattern was depicted using the maximum intensity of all beams. This methodology can be used as a template and applied to data from BlueView two-dimensional imaging sonar.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.11
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• pp.2569-2574
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• 2012

HMS(Hull Mount Sonar) equipment mounted on PCC(Patrol Combat Corvette) is suitably designed for active mode, and the specific character of sensor or system is not appropriate for the frequency range to detect a torpedo. In this article, in order to implement the function of detecting torpedoes with HMS of existing PCC, I will analyze the feature of input signals each PCCs and design a circuit to compensate reversely for the input signal in certain frequency. And also, I will suggest the most adequate torpedo defense system suitable for the special operating environment and the characteristic of naval vessels, implementing functions such as AGC of input signal and fixing the frequency range of different input signals per different warships.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.53 no.10
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• pp.703-713
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• 2004

This paper presents the new obstacle avoidance method that is composed of vision and sonar sensors, also a navigation algorithm is proposed. Sonar sensors provide poor information because the angular resolution of each sonar sensor is not exact. So they are not suitable to detect relative direction of obstacles. In addition, it is not easy to detect the obstacle by vision sensors because of an image disturbance. In This paper, the new obstacle direction measurement method that is composed of sonar sensors for exact distance information and vision sensors for abundance information. The modified splitting/merging algorithm is proposed, and it is robuster for an image disturbance than the edge detecting algorithm, and it is efficient for grouping of the obstacle. In order to verify our proposed algorithm, we compare the proposed algorithm with the edge detecting algorithm via experiments. The direction of obstacle and the relative distance are used for the inputs of the fuzzy controller. We design the angular velocity controllers for obstacle avoidance and for navigation to center in corridor, respectively. In order to verify stability and effectiveness of our proposed method, it is apply to a vision and sonar based mobile robot navigation system.

• Journal of Ocean Engineering and Technology
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• v.34 no.4
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• pp.277-284
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• 2020

Underwater acoustics, which is the study of phenomena related to sound waves in water, has been applied mainly in research on the use of sound navigation and range (SONAR) systems for communication, target detection, investigation of marine resources and environments, and noise measurement and analysis. The main objective of underwater acoustic remote sensing is to obtain information on a target object indirectly by using acoustic data. Presently, various types of machine learning techniques are being widely used to extract information from acoustic data. The machine learning techniques typically used in underwater acoustics and their applications in passive SONAR systems were reviewed in the first two parts of this work (Yang et al., 2020a; Yang et al., 2020b). As a follow-up, this paper reviews machine learning applications in SONAR signal processing with a focus on active target detection and classification.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.4 no.2
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• pp.135-141
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• 2004

This paper proposes a new heuristic search technique for obstacle avoidance of autonomous underwater vehicles equipped with a looking ahead obstacle avoidance sonar. We suggest the fuzzy relation between the sonar sections and the properties of real world environment. Bandler and Kohout's fuzzy relational method are used as the mathematical implementation for the analysis and synthesis of relations between the partitioned sections of sonar over the real-world environmental properties. The direction of the section with optimal characteristics would be selected as the successive heading of AUVs for obstacle avoidance. For the technique using in this paper, sonar range must be partitioned into multi equal sections; membership functions of the properties and the corresponding fuzzy rule bases are estimated heuristically. With the two properties Safety, Remoteness and sonar range partitioned in seven sections, this study gives the good result that enables AUVs to navigate through obstacles in the optimal way to goal.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.46 no.3
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• pp.273-281
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• 2013

The movement patterns of fish aggregations swimming freely near artificial reefs on August 24, 2006, at Suyeong Man, Busan, Korea, were acoustically investigated and analyzed. Acoustic surveys were conducted using a 70kHz split-beam echo sounder, 330 kHz side-scan sonar and a 310 kHz imaging sonar. Algorithms for tracking the movement of fish aggregations swimming in response to artificial reefs were developed. The travel direction and the swimming speed for two aggregations of fish were estimated from the trajectory orientations of echo responses recorded by the imaging sonar.The first group was floating just above the reef structure, while remaining in the midwater column, and the second group was swimming through and around artificial reefs near the seabed. The mean swimming speed was estimated to be 0.40 m/s for the midwater fish aggregation and 0.17 m/s for the bottom aggregation close to artificial reefs. These results suggest that the swimming behavior of fish aggregations passing close to artificial reefs near the seabed displayed a slower moving pattern than fish floating just above the reef structure in the midwater column.

• Proceedings of the IEEK Conference
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• 2002.07c
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• pp.1499-1502
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• 2002

A method for acquiring an environmental map by integrating distance data obtained by sonars of a moving robot with web interface is proposed. Sonar data contains outliers in some cases such as ultrasonic beam is projected onto a corner of an object. Therefore, the influence of the outliers should be reduced by detecting outliers. In our method, the outliers are detected by two ways: (i) a method considering geometrical .elation among the observed surface and the projected ultrasonic beau, and (ii) a method considering consistency with data obtained by other sonars. By measurement by the sonar, the distance from the sonar to the obstacle is obtained. Assuming the two dimensional space we can know that the inside of the sector, whose renter coincide with the sonar and whose radius is equal to the obtained distance, is the free area, and a part of the arc of this sector is the obstacle area. The generation of the environmental map is done by integrating the free area and the obstacle area obtained by each measurement by the sonars. Before the integration, the outliers detection is done by two ways mentioned above. Experimental results show that obtained maps obtained by our methods with outliers defection are much better than those by a method without outliers detection.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2002.05a
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• pp.159-162
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• 2002

This paper deals with target positioning performance according to active sonar formation and measurement error. Generally, active sonar can be categorized into Monostatic, Bistatic and Multistatic cases and their error characteristics are different each other. In this paper, on the assumption that each receiver has two kinds of measurements； sum of distances, and a angle between receiver and target, we suggest least square(LS) method that combines the two measurements in Multistatic formation, and compare Multistatic case with Monostatic and Bistatic cases. Experimental results show that target positioning RMSE in Multistatic sonar is superior to those in Monostatic and Bistatic sonar by approximately 57％.