• The Journal of the Acoustical Society of Korea
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• v.36 no.6
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• pp.394-400
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• 2017

This paper shows the extension of SpSF (Sparse Spectrum Fitting) algorithm, which is one of covariance matrix fitting-based DOA (Direction-of-Arrival) estimation algorithms, from the time domain to the frequency domain, and presents that SpSF can be implemented in the frequency domain. The superiority of the SpSF algorithm has been demonstrated by comparing DOA estimation performance with the performance of Conventional DOA estimation algorithm in the frequency domain for sinusoidal incident signals.

• The Journal of the Acoustical Society of Korea
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• v.39 no.3
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• pp.191-199
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• 2020

Currently, studies on the estimation algorithm based on compressive sensing are actively underway, but to the best of our knowledge, no study on the performance of the Sparse Spectrum Fitting (SpSF) algorithm in nonuniform sensor arrays has been made. This paper deals with the derivation of the compressive sensing based covariance fitting algorithm extended to the frequency domain. In addition, it shows the performance of directon-of-arrival estimation of the frequency domain SpSF algorithm in non-uniform linear sensor array system and the sensor array failure situation.

• The Journal of the Acoustical Society of Korea
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• v.39 no.1
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• pp.38-46
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• 2020

LOw Frequency Analysis Recording (LOFAR) and Demodulation of Envelop Modulation On Noise (DEMON) grams are bearing-time-frequency plots of underwater acoustic signals, to visualize features for passive sonar. Those grams are characterized by tonal components, for which conventional data coding methods are not suitable. In this work, a novel LOFAR/DEMON gram compression algorithm based on binary map and prediction methods is proposed. We first generate a binary map, from which prediction for each frequency bin is determined, and then divide a frame into several macro blocks. For each macro block, we apply intra and inter prediction modes and compute residuals. Then, we perform the prediction of available bins in the binary map and quantize residuals for entropy coding. By transmitting the binary map and prediction modes, the decoder can reconstructs grams using the same process. Simulation results show that the proposed algorithm provides significantly better compression performance on LOFAR and DEMON grams than conventional data coding methods.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.3
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• pp.285-294
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• 2012

Using bearing measurement only, target motion state is not directly obtained so that TMA (Target Motion Analysis) is needed for this situation. TMA is a nonlinear estimation technique used in passive SONAR systems. Also it is the one of important techniques for underwater combat management systems. TMA can be divided to two parts: batch estimation and sequential estimation. It is preferable to use sequential estimation for reducing computational load as well as adaptively to target maneuvers, batch estimation is still required to attain target initial state vector for convergence of sequential estimation. Selection of batch time interval which depends on observability is critical in TMA performance. Batch estimation in general utilizes predetermined batch time interval. In this paper, we propose a new method called the BTIS (Batch Time Interval and Initial State Estimation). The proposed BTIS estimates target initial status and determines the batch time interval sequentially by using a bank of GMM-TS (Gaussian Mixture Measurement-Track Splitting) filters. The performance of the proposal method is verified by a Monte Carlo simulation study.

• 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.30 no.2
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• pp.63-72
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• 2011

Since the detection probability is critically dependent on the target strength (TS) in active sonar and on the radiated noise level (RNL) in passive sonar, the acoustic materials for echo reduction (ER) and transmission loss (TL) are widely used for the stealth of underwater targets. In this paper, a measurement system based on the small water tank, for the frequency range of greater than 30 kHz, is developed and verified using reference targets. In order to design the water tank and the geometry of test samples, a program is developed to calculate the arrival time of interfering signals due to the reflection from water tank walls and also due to the diffraction from the edge of the test samples. Considering all the interfering signals, an optimal experimental configuration for water tank and test samples is designed and used throughout the experiment. Next, the signal processing algorithms to estimate ER and TL are developed based on the measured propagation loss reflecting the geometric spreading characteristics of the transducer. Finally, a set of reference targets such as aluminium plate and perfectly reflecting plate are used in a small water tank to verify the developed measurement system.

• The Journal of the Acoustical Society of Korea
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• v.32 no.2
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• pp.138-146
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• 2013

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.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.29 no.7
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• pp.560-565
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• 2018

The SPICE (Sparse Iterative Covariance-based Estimation) algorithm estimates the azimuth angle by applying a sparse recovery method to the covariance matrix in the time domain. In this paper, we show how the SPICE algorithm, which was originally formulated in the time domain, can be extended to the frequency domain. Furthermore, we demonstrate, through numerical results, that the performance of the proposed algorithm is superior to that of the conventional frequency domain algorithm.

• The Journal of the Acoustical Society of Korea
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• v.15 no.5
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• pp.118-124
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• 1996

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.

• 제어로봇시스템학회:학술대회논문집
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• 1999.10a
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• pp.149-152
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• 1999

The aim of the work described in this paper is to develop a complex underground acoustic system which detects and localizes the origin of an underground hammering sound using an array of hydrophones located about loom underground. Three different methods for the sound localization will be presented, a time-delay method, a power-attenuation method and a hybrid method. In the time-delay method, the cross correlation of the signals received from the way of sensors is used to calculate the time delays between those signals. In the power-attenuation method, the powers of the received signals provide a measure of the distances of the source from the sensors. In the hybrid method, both informations of time-delays and power-ratios are coupled together to produce better performance of position estimation. A new acoustic imaging technique has been developed for improving the hybrid method. For each method the sound localization is carried out in three dimensions underground. The minimum distance between the true and estimated origins of the source is 28 m for a search area of radius 250m.