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

• IEMEK Journal of Embedded Systems and Applications
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• v.12 no.5
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• pp.267-275
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• 2017

Time of difference of arrival (TDOA) method using passive sonar sensor array has normally been used to estimate the location of a concealed moving target in underwater environment. Particle filter has been introduced for effective target estimation for non-Gaussian and nonlinear systems. In this paper, we propose a GPU-based acceleration of target position estimation using particle filter and propose efficient embedded system and software architecture. For the TDOA measurement from the passive sonar sensor, we use the generalized cross correlation phase transform (GCC-PHAT) method to obtain the correlation coefficient of the signal using FFT and we try to accelerate the calculation of GCC-PHAT based TDOA measurements using FFT with GPU CUDA. We also propose parallelization method of the target position estimation algorithm using the GPU CUDA to update the state of each particle for the target position estimation using the measured values. The target estimation algorithm was verified using Matlab and implemented using GPU CUDA. Then, we realized the proposed signal processing acceleration system using NVIDIA Jetson TX1 as the target board to analyze in terms of the execution time. The execution time of the algorithm is reduced by 55% to the CPU standalone-operation on the target board. Experiment results show that the proposed architecture is a feasible solution in terms of high-performance and area-efficient architecture.

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

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.48 no.4
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• pp.47-52
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• 2011

Constant false alarm rate (CFAR) is an automatic detection algorithm for active sonar system. Among several CFAR algorithms, ordered statistics (OS) CFAR has the best performance over cell averaging (CA), smallest of (SO), greatest of (GO) algorithms at non-homogeneous environments. However, OS CFAR has the disadvantage of bad detection performance in multiple target conditions. We suggest an ordered statistics ratio (OSR) CFAR algorithm that is robust to multiple target environments. The proposed and conventional schemes are compared with computer simulations.

• The Journal of the Acoustical Society of Korea
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• v.12 no.4
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• pp.14-20
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• 1993

본 논문에서는 주변 소음을 감소시키고 표적원의 방사음으로부터 tonal 성분을 추출하기 위한 방법으로서 잡음 정규화 기법에 대하여 연구하였다. 지금까지 알려진 기법들을 정리하였으며, ATW, 최빈치 필터등의 새로운 기법을 도입, 적용하여 그 성능을 평가하였다. 그리고 tonal 성분을 검출하기 위한 임계값 결정을 위해 오경보확률과 검출확률을 시뮬레이션을 통해 구하였다.

• Proceedings of the Korea Information Processing Society Conference
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• 2004.05a
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• pp.629-632
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• 2004

수중 표적을 식별하기 위해서는 표적이 방사하는 소음의 특징을 미리 알고 있어야 한다. 소음의 특징은 스펙트럼상의 상이한 주파수나 특징적 패턴을 형성하는데 수중에서 표적을 구별하는 주요 성분이다. 이 논문에서는 이런 표적의 고유 식별 정보를 모델링하고 구축하는 수중 음향 분석 시스템을 설계, 구현하였다. 이로써 표적관련 음파 특징 정보를 수치화하고 체계적으로 구축해 정밀분석의 토대를 마련하였다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.5
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• pp.1083-1088
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• 2013

Detection and classification of undersea mines in shallow waters using active sonar returns is a difficult task due to complexity of underwater environment. Support vector machine(SVM) is a binary classifier that is well known to provide a global optimum solution. In this paper, classification experiments of sonar returns from mine-like objects and non-mine-like objects are carried out using the SVM, and classification performance is analyzed and presented with discussions depending on parameter values of SVM kernel functions.

• The Journal of the Acoustical Society of Korea
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• v.22 no.7
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• pp.562-572
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• 2003

A matched-target model inversion method was developed for a passive sonar to estimate the position of moving targets. Based on the well known matched-field processing in underwater acoustics, the method finds target position by matching the measured target directions and frequencies with the corresponding values of the proposed target model. For the efficient and accurate estimations, the parameter searching was accomplished using a hybrid optimizing method, which first starts with a global optimization such as generic algorithm or simulated annealing then applies a local optimization of a simple down hill algorithm. The suggested method was testified using simulations for three different moving scenarios. The simulation results showed that the method is robust in convergence, even under the situation of over 5 times standard deviation of Gaussian distribution of measured error, and is practical in calculation time as well.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.5
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• pp.174-180
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• 2015

In this paper, we propose the passive sonar signal processing technique for estimating target information using proximity sensor. This algorithm is performed by single sensor which is constituted underwater sensor network and has a hierarchical structure. The estimated parameter is the velocity, the depth, the distance and bearing at CPA situations and we can improve the accuracy of signal processing techniques through having a hierarchical structure. We verify the performance of the proposed method by computer simulation and then we check the result that 20% error can be occurred in maximum detectable range. We also confirm that proposed method has the reliability in the actual sea environment through the sea experiment.

• The Journal of the Acoustical Society of Korea
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• v.8 no.4
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• pp.29-38
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• 1989

Detection of an underwater target by acoustic wave raises various difficulties due to unpredictable noise interference which originates from clutter, reverberation, and variations of medium characteristics with time and location. The SNR and the range resolution of conventional SONAR systems using a matched filter are generally poor, since the latter is optimum only in the additive white noise case. Furthermore, it cannot compensate for variations of the detection level which are responsible for the resultant detection errors. In this paper, the unpredictable interferences are compensated for by using an adaptive filter. It recursively estimates the channel impulse response based on the received echo signal. In the low noise environments, the estimated impulse response is close to the true one, providing a good range resolution, and a matched filter is used subsequently for the purpose of detection. It is shown through computer simulation that good performance can be achieved via the two steps of filtering. Also, the detection level remains unchanged without any additional provisions. Finally, we present the characteristics of the employed adaptive filter parameters.