• Journal of Biomedical Engineering Research
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• v.21 no.4
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• pp.419-431
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• 2000

In this paper, a new beamforming technique is proposed, which can completely eliminate all the artifacts caused by digital scan converter. In the proposed method, named display-pixel-based focusing(DPBF) by the authors, ultrasound waves are focused directly at the display pixels instead of sampling points on the polar coordinate. Consequently. the DPBF system does not require the digital scan converter. To verify the proposed method, we modified a commercial scanner and performed experiments with a 3.5 MHz convex array and a 7.5 MHz linear array. We also defined and measured ICRA/B(Image Coarseness Ratio) to compare the image quality quantitatively. The experimental results with in vivo and in vitro data show that the proposed method improves the ICRA/B considerably, resulting in much smoother and finer images.

• Journal of Positioning, Navigation, and Timing
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• v.11 no.3
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• pp.163-172
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• 2022

Typical anti-jamming technologies based on array antennas, Space Time Adaptive Process (STAP) & Space Frequency Adaptive Process (SFAP), are very effective algorithms to perform nulling and beamforming. However, it does not perform equally well for all types of jamming signals. If the anti-jamming algorithm is not optimized for each signal type, anti-jamming performance deteriorates and the operation stability of the system become worse by unnecessary computation. Therefore, jamming classification technique is required to obtain optimal anti-jamming performance. Machine learning, which has recently been in the spotlight, can be considered to classify jamming signal. In general, performing supervised learning for classification requires a huge amount of data and new learning for unfamiliar signal. In the case of jamming signal classification, it is difficult to obtain large amount of data because outdoor jamming signal reception environment is difficult to configure and the signal type of attacker is unknown. Therefore, this paper proposes few-shot jamming signal classification technique using meta-learning and transfer-learning to train the model using a small amount of data. A training dataset is constructed by anti-jamming algorithm input data within the GNSS receiver when jamming signals are applied. For meta-learning, Model-Agnostic Meta-Learning (MAML) algorithm with a general Convolution Neural Networks (CNN) model is used, and the same CNN model is used for transfer-learning. They are trained through episodic training using training datasets on developed our Python-based simulator. The results show both algorithms can be trained with less data and immediately respond to new signal types. Also, the performances of two algorithms are compared to determine which algorithm is more suitable for classifying jamming signals.

• The Journal of the Acoustical Society of Korea
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• v.41 no.2
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• pp.192-198
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• 2022

As an effective weapon system for anti-submarine warfare, DIrectional Frequency Analysis and Recording (DIFAR) sonobuoy detects underwater targets via beamforming with three channels composed of an omni-direcitonal and two directional channels. However, ambient noise degrades the detection performance of DIFAR sonobouy in specific direction (0°, 90°, 180°, 270°). Thus, an ambient noise redcution technique is proposed for performance improvement of acoustic target detection of DIFAR sonobuoy. The proposed method is based on OTA (Order Truncate Average), which is widely used in sonar signal processing area, for ambient noise estimation and Wiener filtering, which is widely used in speech signal processing area, for noise reduction. For evaluation, we compare mean square errors of target bearing estmation results of conventional and proposed methods and we confirmed that the proposed method is effective under 0 dB signal-to-noise ratio.

• Journal of the Institute of Convergence Signal Processing
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• v.14 no.2
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• pp.110-116
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• 2013

The amplification rate of a RF repeater is limited by the feedbacked signals from the same repeater. And an ICS (Interference Cancellation System) repeater has been developed to remove the feedbacked signals. The ICS repeater estimates the amplitudes and the phases of the feedbacked signals and removes the estimated feedback signals from the received input signal of the repeater. However, it requires lots of hardware complexity and this leads to the increase the cost of the repeater. Moreover, the ICS repeater can not solve the pilot pollution problems. To solve these problems, we have studied the implementation and adaptation of smart antenna system for RF repeaters. We have designed a smart antenna system with a switching beam structure in order to reduce the hardware and computational complexity. After analyzing the proposed smart antenna system, we found out that the amplification rate of the proposed repeater increases 23dB compare to the amplification rate of ICS repeater and the output SINR increases 6dB compare to the ICS repeater.

• The Journal of the Korea institute of electronic communication sciences
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• v.8 no.6
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• pp.907-915
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• 2013

Tire Pressure Monitoring System (TPMS) is an auxiliary safety system for recognizing the condition of tires based on the pressure and temperature data transmitted from the sensor unit installed on a tire of the vehicle. Using TPMS, a driver can frequently check the state of tires and it aids to maintain the optimum running condition of the vehicle. Since TPMS must utilize the wireless communication technique to transmit data from a sensor unit to a signal processing unit installed in the vehicle, it suffers from interference signals caused by various external electrical or electronic devices. In order to suppress high-power interference signals, we employ beamforming techniques based on the uniform linear antenna array. As the number of the antennas is increased, the performance of the interference suppression is improved. However, there is the limit of the number of antennas, installed in the center of a vehicle, because of its size. In this paper, we compare and analyze the performance of the beamformer, when reducing the interelement spacing of antennas, to increase the number of the receiving antennas. For the performance analysis of the beamformers, we consider the switching beamformer and minimum-variance distortionless-response (MVDR) beamformer for TPMS, recently proposed.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.5
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• pp.69-76
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• 2020

The sound signal radiated from an underwater source is received by the hydrophone of the system, including multi-path time-delay and multi-path signal by sea surface and bottom reflection. The system using a time-delay between received signals for the source localization shows performance degradation due to incoherence by the multi-path propagation environment and the disturbance of a marine environment. Various types of array and signal processing have been used for robust source range and bearing estimation in this environment. In this paper, we use a line array composed of doublet array and an estimated time-delay correction method for robust localization performance in a multi-path propagation environment. Three doublet arrays are located on the same line, and the time-delay between signals received on each doublet array is estimated in a two-step procedure. The estimated time-delay value is obtained by the cross-correlation function and corrected by the interaction formula between the center-frequency of received signal and the geometry of the array with respect to aperture. By this proposed procedure, the range and bearing of source from array were calculated. In order to confirm the validity of the proposed method and array, we simulated localization and estimation using the Monte-Carlo method.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.46 no.5
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• pp.95-103
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• 2009

An efficient symbol time synchronization scheme for IEEE 802.11n MIMO-OFDM based WLAN systems using cyclic shift diversity (CSD) preamble is proposed. CSD is used to prevent unintentional beamforming when the same preamble signal is transmitted through transmit antennas. However, it is difficult to find a proper starting-point of the OFDM symbol with the conventional algorithms because of time offset by multi-peaks which are result from cross-correlation of received CSD preamble with a known short training symbol. In addition, the performance of symbol time sync. is affected by AGC and packet detection position. In this paper, an optimal symbol time synch. algorithm which is composed of the boundary detection scheme between LTS and OFDM symbols, the verification scheme for enhancement of boundary detection accuracy, and the SNR-varying threshold estimation scheme is proposed. Simulation result show that the proposed algorithm has performance gains of 4.3dB in SNR compared to the conventional algorithms at the rate of 1% sync. failure probability for $2{\times}2$ MIMO-OFDM system and 18dB at 0.1% when maximum frequency offset exists. It also can be applied to $4{\times}4$ MIMO-OFDM system without any modification. Hence, it is very suitable for MIMO-OFDM WLAN systems using CSD preamble.