• The Journal of the Acoustical Society of Korea
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• v.38 no.4
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• pp.387-395
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• 2019

TMA (Target Motion Analysis) in passive sonar is generally conducted with the bearing only or the bearing frequency. In order to conduct TMA fast and accurately, it is essential to estimate a initial target maneuver precisely. The accuracy of TMA can be improved by using SNR (Signal to Noise Ratio) information and acoustic propagation model additionally. This method assumes that the radiated noise level of the target is known, but the accuracy of TMA can be degraded due to a mismatch between the assumed radiated noise level and the actual radiated noise level. In this paper, TMA with the acoustic propagation model, bearing measurements, and SNR information is conducted in the ocean environment of South Korea (East Sea/ Yellow Sea/ South Sea). And the performance analysis of TMA for the mismatch in the radiated noise is presented.

• The Journal of the Acoustical Society of Korea
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• v.28 no.4
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• pp.336-342
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• 2009

A conventional Closest Point of Approach (CPA) analysis allows a non-maneuvering moving source that is radiating a constant frequency tone to be located using doppler shifted frequency measurements obtained by a stationary receiver. The original frequency, relative speed of the target, time at the CPA, and range from the CPA to the sensor are estimated by the conventional CPA. However, this paper proposes a new CPA analysis that allows the motion parameters of a target to be estimated using the bearing and frequency measurements obtained by a moving receiver that has a constant velocity. The validity of the proposed estimation scheme is confirmed through a performance analysis and simulation study.

• 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 Korea Institute of Military Science and Technology
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• v.7 no.2 s.17
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• pp.22-31
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• 2004

In this paper, the measurements preprocessing algorithm for the fading of bearing and frequency measurements is proposed, which can improve the performance of BFTMA(Bearing and Frequency Target Motion Analysis). The fading and detection relation between bearing and frequency are rigorously established for measurements preprocessing, and BFTMA can be carried out the estimation of target motion by using measurements preprocessing. Batch estimation with bearing and frequency using the proposed algorithm can be applied to estimate the initial target states despite of the fading of frequency measurement. Simulation results show that BFTMA using the proposed measurements preprocessing has superior estimation performance, compared with batch estimation using only bearing measurements.

• The Journal of the Acoustical Society of Korea
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• v.23 no.3
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• pp.206-213
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• 2004

This paper presents a steering angle error compensation (SAEC) algorithm that is appropriate for rapidly moving sources. The Proposed algorithm utilizes a modal covariance matrix from multiple frequency components instead of the multiple snapshots in a narrowband SAEC, and estimates the steering error by maximizing the wideband WVDR output power using a first-order Taylor series approximation of the modal steering vector in terms of the steering error. As such, the steering error can be compensated with short observation times. Several simulations using artificial and sea trial data are used to demonstrate the Performance of the proposed algorithm.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.10
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• pp.788-796
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• 2016

Bearing and frequency measurements of TMA (Target Motion Analysis) in passive line array SONAR have lower bearing rate and frequency doppler, and are not detected or tracked continuously because of various ocean environments. This is a main reason to effect the TMA performance and it takes a long time to get TMA solutions. We propose the bearing and frequency TMA(BFTMA) using accumulative batch estimation to solve the TMA problem of line array passive SONAR. The accumulative batch estimation structure is based on MLE (Maximum Likelihood Estimation) but used accumulative measurements. The accumulative batch estimation is applied for the BFTMA with nonlinear Kalman filter to estimate the target range, speed and course. Simulation and sea data analysis were carried out to verify the performance and applicability of the proposed techniques.