• The Journal of the Acoustical Society of Korea
• /
• v.38 no.3
• /
• pp.302-307
• /
• 2019

In modern Anti-Submarine Warfare, there are various ways to locate a submarine in a two-dimensional space. For more effective tracking and attack against a submarine the depth of the target is a critical factor. However, it has been difficult to find out the depth of a submarine until now. In this paper a possible solution to the depth estimation of submarines is proposed utilizing DIFAR (Directional Frequency Analysis and Recording) sonobuoy information such as contact bearings at or prior to CPA (Closest Point of Approach) and the target's Doppler signals. The relative depth of the target is determined by applying the Pythagorean theorem to the slant range and horizontal range between the target and the hydrophone of a DIFAR sonobuoy. The slant range is calculated using the Doppler shift and the target's velocity. the horizontal range can be obtained by applying a simple trigonometric function for two consecutive contact bearings and the travel distance of the target. The simulation results show that the algorithm is subject to an elevation angle, which is determined by the relative depth and horizontal distance between the sonobuoy and target, and that a precise measurement of the Doppler shift is crucial.

• Proceedings of the Acoustical Society of Korea Conference
• /
• autumn
• /
• pp.269-272
• /
• 2000

수중 표적으로부터 수신된 신호에서, 파도와 난류 등의 영향으로 선박의 특정 기계류들의 부하변동과 도플러효과 등에 의해 야기되는 특징 주파수의 시간적 변동과 같은 음향 특징 추출은 수중음향 신호처리에서 중요한 연구분야이다. 본 연구에서는 이들의 발생기구 해석을 기초로 효과적인 분석 추적 기법을 제시한다.

• Bulletin of the Society of Naval Architects of Korea
• /
• v.51 no.2
• /
• pp.23-28
• /
• 2014

• The Journal of the Acoustical Society of Korea
• /
• v.32 no.4
• /
• pp.354-360
• /
• 2013

In this paper, it is discussed that the detection and tracking performance of the piecewise linear path underwater target is improved using clutter reduction algorithm in heavy clutter density environment. Through clutter reduction algorithm using Hough Transform, measurements which represent clutter features are removed and the performance of target tracking on the remaining measurements is demonstrated applying CMKF-L(Converted Measurement Kalman Filter with Linearization) as tracking filter. Algorithm performance test is conducted using simulation data and real sea-trial data and by applying the proposed algorithm in heavy clutter density environment, it is confirmed that the target is tracked consistently and stably with clutter rejected measurements.

• The Journal of the Acoustical Society of Korea
• /
• v.43 no.2
• /
• pp.225-233
• /
• 2024

Active sonar transmits sound waves to detect covertly maneuvering underwater objects and detects the signals reflected back from the target. However, in addition to the target's echo, the active sonar's received signal is mixed with seafloor, sea surface reverberation, biological noise, and other noise, making target recognition difficult. Conventional techniques for detecting signals above a threshold not only cause false detections or miss targets depending on the set threshold, but also have the problem of having to set an appropriate threshold for various underwater environments. To overcome this, research has been conducted on automatic calculation of threshold values through techniques such as Constant False Alarm Rate (CFAR) and application of advanced tracking filters and association techniques, but there are limitations in environments where a significant number of detections occur. As deep learning technology has recently developed, efforts have been made to apply it in the field of underwater target detection, but it is very difficult to acquire active sonar data for discriminator learning, so not only is the data rare, but there are only a very small number of targets and a relatively large number of non-targets. There are difficulties due to the imbalance of data. In this paper, the image of the energy distribution of the detection signal is used, and a classifier is learned in a way that takes into account the imbalance of the data to distinguish between targets and non-targets and added to the existing technique. Through the proposed technique, target misclassification was minimized and non-targets were eliminated, making target recognition easier for active sonar operators. And the effectiveness of the proposed technique was verified through sea experiment data obtained in the East Sea.

• The Journal of the Acoustical Society of Korea
• /
• v.19 no.8
• /
• pp.78-83
• /
• 2000

Passive sonar system is designed to classify the underwater targets by analyzing and comparing the various acoustic characteristics such as signal strength, bandwidth, number of tonals and relationship of tonals from the extracted tonals and frequency lines. First of all the precise detection and extraction of signal frequency lines is of particular importance for enhancing the reliability of target classification. But, the narrowband frequency lines which are the line formed in spectrogram by a tonal of constant frequency in each frame can be detected weakly or discontinuously because of the variation of signal strength and transmission loss in the sea. Also, it is very difficult to detect and extract precisely the signal frequency lines by the complexity of impulsive ambient noise and signal components. In this paper, the automatic detection and extraction method that can detect and extract the signal components of frequency tines precisely are proposed. The proposed method can be applied under the bad conditions with weak signal strength and high ambient noise. It is confirmed by the simulation using real underwater target data.

• The Journal of the Acoustical Society of Korea
• /
• v.42 no.4
• /
• pp.320-328
• /
• 2023

Underwater active target detection is vital for defense systems, requiring accurate detection and estimation of distance and velocity. Sequential transmission is necessary at each beam angle, but divided pulse length leads to range ambiguity. Multi-frequency transmission results in time-bandwidth product losses when bandwidth is divided. To overcome these problem, we propose a novel method using Generalized Sinusoidal Frequency Modulation (GSFM) for rapid target detection, enabling low-correlation pulses between subpulses without bandwidth division. The proposed method allows for rapid updates of the distance and velocity of target by employing GSFM with minimized pulse length. To evaluate our method, we simulated an underwater environment with reverberation. In the simulation, a linear frequency modulation of 0.05 s caused an average distance estimation error of 50 % and a velocity estimation error of 103 % due to limited frequency band. In contrast, GSFM accurately and quickly tracked targets with distance and velocity estimation errors of 10 % and 14 %, respectively, even with pulses of the same length. Furthermore, GSFM provided approximate azimuth information by transmitting highly orthogonal subpulses for each azimuth.

• Journal of the Korea Institute of Military Science and Technology
• /
• v.20 no.3
• /
• pp.369-375
• /
• 2017

One of good DF(Direction Finding) methods is based on TDOA(Time Difference of Arrival) estimation when finding underwater moving target. For small DF error, high time resolution A/D(Analog-to-digital) conversion board and long baseline are needed. But the result of sea trial about close-range and high speed moving target, spatial correlation coefficient and appeared poor properties below 0.3 when hydrophone arrangement are separated over 6 ${\lambda}$ because of underwater fading channel. And we also find out that the distance between hydrophone should be under 4 ${\lambda}$ apart to take advantage of spatial correlation coefficient gain and performance of DF in underwater moving channel environments.

• Journal of Institute of Control, Robotics and Systems
• /
• v.19 no.8
• /
• pp.694-701
• /
• 2013

This paper deals with the problem of accurately tracking a single target moving through UWSNs (Underwater Wireless Sensor Networks) by employing underwater acoustic sensors. This paper addresses the issues of estimating the states of the target, and improving energy efficiency by applying a Kalman filter in a distributed architecture. Each underwater wireless sensor nodes composing the UWSNs is battery-powered, so the energy conservation problem is a critical issue. This paper provides an algorithm which increases the energy efficiency of each sensor node through WuS (Waked-up/Sleeping) and VM (Valid Measurement) selecting schemes. Simulation results illustrate the performance of the distributed tracking filter.

• Journal of the Korea Institute of Military Science and Technology
• /
• v.18 no.5
• /
• pp.517-524
• /
• 2015

In this paper, we propose a new target tracking filter architecture using active and passive sensors in underwater environment. A passive sensor for target tracking needs a bearing measurement of target. And target tracking filter for using passive sensor has the observability problem. On the other hand, an active sensor does not have the problem associated with system observability problem because an active sensor uses bearing and range measurement. In this paper, the tracking filter algorithm that could be used in the active and passive sensor system is proposed to analyze maneuvering target and to improve target tracking performance. The proposed tracking filter algorithm is tested by a series of computer simulation runs and the results are analyzed and compared with existing algorithm.