선배열 센서를 이용한 근거리 다중 표적 위치 추적 알고리즘

황수복,김진석,김현식,박명호,남기곤,Hwang Soo-Bok,Kim Jin-Seok,Kim Hyun-Sik,Park Myung-Ho,Nam Ki-Gon 한국음향학회 2005 한국음향학회지 Vol.24 No.5

Generally, traditional approaches to track the target position are to estimate ranges and bearings by 2-D MUSIC (MUltiple 519na1 Classification) method. and to associate estimates of 2-D MUSIC made at different time points with the right targets by JPDA (Joint Probabilistic Data Association) filter in the near field. However, the disadvantages of these approaches are that these have the data association Problem in tracking multiple targets. and that these require the heavy computational load in estimating a 2-D range/bearing spectrum. In case multiple targets are adjacent. the tracking performance degrades seriously because the estimate of each target's Position has a large error. In this paper, we proposed a new tracking algorithm using Position innovations extracted from the senor output covariance matrix in the near field. The proposed algorithm is demonstrated by the computer simulations dealing with the tracking of multiple closing and crossing targets.

상호상관 행렬을 이용한 선배열 빔형성 기법 연구

황수복,이성은 한국음향학회 2001 韓國音響學會誌 Vol.20 No.7

Passive sonar system forms the various beams in any desired directions to obtain the improvement in Signal-to-Noise (S/N) ratio, bearing detection and localization of targets, and the attenuation of interferences from other directions. The improvement of beamforming is very important to detect modern underwater targets as noise reduction technology leads to considerably low-level acoustic emissions in the long range in complex environmental sea. In this paper, we proposed the spatial cross correlation beamforming (SCCBF) algorithm using cross correlation matrix of individual hydrophone pairs of linear array sensors. By the theoretical analysis and simulation, the proposed SCCBF is demonstrated that its performances compared to conventional beamforming (CBF) output can be obtain above 3dB of array gain and about half of beam width represented the bearing accuracy in target detection. Also, this paper presents sea test result of linear passive sonar system that the proposed algorithm implemented.

대역 분할 처리를 통한 데몬 처리 성능 향상 기법

정명준,황수복,이승우,김진석,Cheong, Myoung Jun,Hwang, Soo Bok,Lee, Seung Woo,Kim, Jin Seok 한국음향학회 2013 한국음향학회지 Vol.32 No.2

Passive sonars employ DEMON (Detection of Envelope Modulation on Noise) processing to extract propeller information from the radiated noise of underwater targets. Conventional DEMON processing improves SNR(Signal to Noise Ratio) characteristic by Welch method. The conventional Welch method overlaps several different time domain DEMON outputs to reduce the variance. However, the conventional methods have high computational complexity to get high SNR with correlated acoustic signals. In this paper, we propose new DEMON processing method that divides acoustic signal into several frequency bands before DEMON processing and averages each DEMON outputs. Therefore, the proposed method gathers independent acoustic signal faster than conventional method with low computational complexity. We prove the performance of the proposed method with mathematical analysis and computer simulations.

Underwater Flight Vehicle의 지능형 심도 제어에 관한 연구

김현식,황수복,신용구,최중락 한국군사과학기술학회 2001 한국군사과학기술학회지 Vol.4 No.2

In Underwater Flight Vehicle depth control system, the followings must be required. First, It needs a robust performance which can get over the nonlinear characteristics due to hull shape. Second, It needs an accurate performance which has the small overshoot phenomenon and steady state error to avoid colliding with ground surface and obstacles. Third, It needs a continuous control input to reduce the acoustic noise. Finally, It needs an effective interpolation method which can reduce the dependency of control parameters on speed. To solve these problems, we propose a Intelligence depth control method using Fuzzy Sliding Mode Controller and Neural Network Interpolator. Simulation results show the proposed control scheme has robust and accurate performance by continuous control input and has no speed dependency problem.

토널 신호 간섭에 강인한 데몬 처리 기법

김진석,황수복,이철목,Kim, Jin-Seok,Hwang, Soo-Bok,Lee, Chul-Mok 한국음향학회 2012 한국음향학회지 Vol.31 No.6

Passive sonars employ DEMON(Detection of Envelope Modulation on Noise) processing to extract propeller information from the radiated noise of underwater targets. However, the conventional DEMON processing suffers from the interference of tonal signals because it extracts propeller signals and some types of tonal signals as well. If there are some tonals in the frequency band for DEMON processing, the conventional DEMON processing may additionally extract frequency informations originated from the interaction between different tonals. In this paper, we propose a modified DEMON processing, which can eliminate the interference of the tonals. The proposed algorithm removes tonals in DEMON processing band before demodulation processing, hence results the robustness to the interference of the tonals. Some numerical simulations demonstrate the improved performance of the proposed algorithm against the conventional algorithm.

협대역 다중 주파수선의 자동 탐지 및 추출 기법 연구

이성은,황수복 한국음향학회 2000 韓國音響學會誌 Vol.19 No.8

수동 소나 시스템에서는 수중 소음원에 대한 신호처리 과정을 수행하여 토널 및 주파수선의 신호 성분으로부터 신호 세기 대역폭, 토널 개수, 토널간의 상호 관계둥의 다양한 특징인자를 분석, 비교하여 표적을 식별하게 되며, 표적 식별율을 향상시키기 위해서는 무엇보다도 주파수선의 신호 성분만을 정밀하게 탐지하고 추출하여야 한다. 그러나 수중신호의 스펙트로그램상에 형성되는 협대역 주파수선은 토널의 신호 세기와 바다 자체의 전달 특성 둥으로 인하여 미약하게 탐지되거나 불규칙하게 끊어져서 불연속적으로 나타날 뿐 아니라 임펄스성의 주변잡음 성분과 복합적으로 존재하므로 주파수선의 신호 성분만을 정밀하게 탐지하고 추출하기가 매우 어렵다. 본 논문에서는 신호 세기가 미약한 경우나 높은 주변잡음이 복합되어 있는 경우에도 정밀하게 주파수선의 신호 성분만을 탐지, 추출한 수 있는 협대역 다중 주파수선의 자동 탐지 및 추출을 위한 기법을 제안하였으며, 실제 수중표적 신호를 적용하여 제안된 알고리즘이 매우 유용함을 보인다.

소량 및 불균형 능동소나 데이터세트에 대한 딥러닝 기반 표적식별기의 종합적인 분석

김근환,황용상,신성진,김주호,황수복,추영민 한국음향학회 2023 한국음향학회지 Vol.42 No.4

In this study, we comprehensively analyze the generalization performance of various deep learning-based active sonar target classifiers when applied to small and imbalanced active sonar datasets. To generate the active sonar datasets, we use data from two different oceanic experiments conducted at different times and ocean. Each sample in the active sonar datasets is a time-frequency domain image, which is extracted from audio signal of contact after the detection process. For the comprehensive analysis, we utilize 22 Convolutional Neural Networks (CNN) models. Two datasets are used as train/validation datasets and test datasets, alternatively. To calculate the variance in the output of the target classifiers, the train/validation/test datasets are repeated 10 times. Hyperparameters for training are optimized using Bayesian optimization. The results demonstrate that shallow CNN models show superior robustness and generalization performance compared to most of deep CNN models. The results from this paper can serve as a valuable reference for future research directions in deep learning-based active sonar target classification.

자동 연상 기억장치 신경망을 이용한 음향 표적의 신호 주파수선 탐지

이성은,황수복,남기곤,김재창,Lee, Sung-Eun,Hwang, Soo-Bok,Nam, Ki-Gon,Kim, Jae-Chang 한국음향학회 1996 韓國音響學會誌 Vol.15 No.5

Signal frequency lines generated from the acoustic targets are of particular importance for target detection and classification in passive sonar systems. The underwater noise consists of a mixture of ambient noise and radiated noise of targets. Detction of exact signal frequency lines depends on signal detection threshold and variation of ambient noise. In this paper, a detection method of signal frequency lines for acoustic targets using autoassociative memory (ASM) neural network, which is not sensitive to variation of signal detection threshold and ambient noise, is proposed. It is confirmed by simulation and application of real acoustic targets that the proposed method shows good performance for detection of signal frequency lines.

확장 칼만필터를 이용한 수중 표적의 불안정 주파수선 추출 기법

이성은,황수복,남기곤,김재창,Lee, Sung-Eun,Hwang, Soo-Bok,Nam, Ki-Gon,Kim, Jae-Chang 한국음향학회 1996 韓國音響學會誌 Vol.15 No.6

In passive sonar system, frequency lines generated by underwater target are very important for detection, tracking and classification. In this paper, the extraction method of unstable frequency line from the time samples of the radiated noise of underwater target is studied. As unstable frequency line is time varying, an extended Kalman filter algorithm which is desirable for nonlinear system is applied to extract unstable frequency line. The proposed method shows good extraction of unstable frequency line by application of simulated signal and real target.

예인선배열 센서를 이용한 전방위 표적방위 탐지기 구현

이성은,천승용,황수복,이형욱 한국군사과학기술학회 2002 한국군사과학기술학회지 Vol.5 No.1

Passive sonar system forms the various beams in any desired directions to obtain the improvement in Signal-to-Noise(S/N) ratio, bearing detection and localization of targets, and the attenuation of interferences from other directions. Detection of modern underwater targets is becoming increasingly difficult as noise reduction technology leads to considerably low-level acoustic emissions. Therefore, the improvement of beamforming is very important to detect modern underwater targets at the long range in the complex environmental sea. Also, to react to the fast attack mobiles such as torpedoes, port and starboard discrimination is required to be performed very quickly. In this paper, we proposed the implementation of omnidirectional target bearing detector without port and starboard ambiguity to detect effectively the low-level underwater targets. The port and starboard discrimination is performed by cardioid processing and the improvement of beamforming utilizes the cross correlation matrix of individual hydrophone pairs of linear array sensors. The sea test result shows that the system implemented is good for the detection of the low-level underwater targets.