• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.2
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• pp.239-247
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• 2018

Adaptive Beamforming (ABF) algorithm, which is a typical jammer suppression algorithm, guarantees the performance on the assumption that the jamming characteristics of the TDS (Training Data Sample) are stationary, which are obtained immediately before and after transmitting the pulse signal. Therefore, effective jammer suppression can not be expected when the jamming characteristics are non-stationary. In this paper, we propose a new jammer suppression algorithm, of which power spectrum fluctuates fast. In this case, we assume that the location of the jammer station is fixed during the processing time. By applying the MPM (Matrix Pencil Method) to the jamming signal in TDS, we can estimate jammer parameters such as power and incident angle, of which the power will vary fast in time or range bins after TDS. Though we assume that the jammer station is fixed, the estimated jammer's incident angle has an error due to the noise, which degrades the performance of the jammer suppression as the jammer power increases fast. Therefore, the jammer's incident angle should be re-estimated at each range bin after TDS. By using the re-estimated jammer's incident angle, we can construct new covariance matrix under the non-stationary jamming environment. Then, the optimum weight for the jammer suppression is obtained by inversing matrix estimation method based on the matrix projection with the estimated jammer parameters as variables. To verify the performance of the proposed algorithm, the SINR (signal-to-interference plus noise ratio) loss of the proposed algorithm is compared with that of the conventional ABF algorithm.

• Phonetics and Speech Sciences
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• v.3 no.3
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• pp.91-98
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• 2011

In this paper, a multi-channel speech enhancement method using the linearly constrained minimum variance (LCMV) algorithm and a variable learning rate control is proposed. To control the learning rate for adaptive filters of the LCMV algorithm, the direction of arrival (DOA) is measured for each short-time input signal and the likelihood function of the target speech presence is estimated to control the filter learning rate. Using the likelihood measure, the learning rate is increased during the pure noise interval and decreased during the target speech interval. To optimize the parameter of the mapping function between the likelihood value and the corresponding learning rate, an exhaustive search is performed using the Bark's scale distortion (BSD) as the performance index. Experimental results show that the proposed algorithm outperforms the conventional LCMV with fixed learning rate in the BSD by around 1.5 dB.

• Journal of Electrical Engineering and information Science
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• v.1 no.1
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• pp.156-159
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• 1996

Element failure occurs with high probability for every array used in the real world ; that is, it is a common phenomenon that there are one or more elements with no output. Element failure produces an elevated sidelobe level and fails to reject the interference signals in an adaptive beamformer. In this paper, we present the adaptive beamforming algorithm for array with element failure. The presented method minimizes the array output power subject to a set of linear constraints which maintain the frequency response in the look direction and force the weights of the inoperative elements to zero. Numerical results have been included.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2001.10a
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• pp.341-344
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• 2001

We propose a novel method to simplify the computational load of ILSP algorithm for CDMA environment. Since this method processes the block matrix by a vector sequentially, the complex matrix computation ran be avoided. The performance of the algorithm is verified by computer simulations.

• The Journal of the Korea institute of electronic communication sciences
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• v.12 no.5
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• pp.777-782
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• 2017

The Signal Intelligence (SIGINT) system based on the adaptive beamformer, comprised of the AOA estimator followed by the interference canceller, is a cutting edge technology for collecting various signal information utilizing all sorts of devices such as the radar and satellite. In this paper, we present the efficient adaptive SIGINT structure consisted of an AOA estimator and an adaptive beamformer. For estimating AOA information of various signals, we employ the Multiple Signal Classification (MUSIC) algorithm and for efficiently suppressing high-power interference signals, we employ the Minimum Variance Distortionless Response (MVDR) algorithm. Also, we provide computer simulation examples to verify the performance of the presented adaptive beamformer structure.

• The Journal of the Acoustical Society of Korea
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• v.11 no.3
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• pp.53-60
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• 1992

Many adaptive beamforming methods have been studied for interference cancellation and speech signal enhancement in telephone conference and auditorium. Main aspect of adaptive beamforming methods for speech signal processing is different from radar, sonar and seismic signal processing because desire output signal should be apt to the human ear. Considering that phase of speech is quite insensible to the human ear, Sondhi proposed a nonlinear constrained optimization technique whose constraint was on the magnitude transfer function from the source to the output. In real environment the phase response of the speech signal affects the human auditorium system. So it is desirable to design linear phase system. In this paper, linear phase beamformer is proposed and sample processing algorithm is also proposed for real time consideration Simulation results show that the proposed algorithm yields more consistent beam patterns and deep nulls to the noise direction than Sondhi's.

• The Journal of the Korea institute of electronic communication sciences
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• v.13 no.6
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• pp.1207-1212
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• 2018

The signal intelligence (SIGINT) technology is actively used for collecting various data, in a number of fields, including a military industry. In order to collect the signal information and data and to transmit/receive the collected data efficiently, the accurate angle-of-arrival (AOA) information is required and communication disturbance from the interference or jamming signal should be minimized. In this paper, we present the structure of an adaptive beam-forming satellite system based on the planar array antenna, for collecting and transmitting/receiving the signal information and data efficiently. The presented adaptive beam-forming system consists of an antenna in the form of a planar array, an AOA estimator based on the Multiple Signal Classification (MUSIC) algorithm, an adaptive Minimum Variance Distortionless Response (MVDR) interference canceler, a signal processing and D/B unit, and a transmission beamformer based on Minimum mean Square Error (MMSE). In addition, through the computer simulation, we evaluate and analyze the performance of the proposed system.

• Journal of the Korean Institute of Telematics and Electronics
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• v.25 no.10
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• pp.1263-1273
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• 1988

An adaptive nulling technique is presented to synthetically overcome the integrated problems associated with the conventional LMS array in the performances of jammer rejection, convergence rate, misadjustment, and reference signal generation. The proposed method is to remove the target signal from the array input and to eliminate the reference signal prior to minimization processing. The algorithm is constrained to the residue noise level in adaptive processor. Analysis shows effectiveness of the algorithm for coherent and/or incoherent interference rejection, wide dynamic range of convergence factor, rapid adaptation rate, and small mean square error. Simulation results confirm the theoretical prediction.

• Journal of Electrical Engineering and Technology
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• v.13 no.2
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• pp.868-874
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• 2018

In this paper, we propose a new jammer suppression algorithm that uses orthogonal waveform space projection (OWSP) processing for a multiple input multiple output (MIMO) radar system exposed to a jamming signal. Generally, a conventional suppression algorithm based on adaptive beamforming (ABF) needs a covariance matrix composed of the jammer and noise only. By exploiting the orthogonality of the transmitting waveforms of MIMO, we can construct a transmitting waveform space (TWS). Then, using the OWSP processing, we can build a space orthogonal to the TWS that contains no SOI. By excluding the SOI from the received signal, even in the case that contains the SOI and jamming signal, the proposed algorithm makes it possible to evaluate the covariance matrix for ABF. We applied the proposed OWSP processing to suppressing the jamming signal in bistatic MIMO radar. We verified the performance of the proposed algorithm by comparing the SINR loss to that of the ideal covariance matrix composed of the jammer and noise only. We also derived the computational complexity of the proposed algorithm and compared the estimation of the DOD and DOA using the SOI with those using the generalized likelihood ratio test (GLRT) algorithm.

• International Journal of Internet, Broadcasting and Communication
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• v.11 no.1
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• pp.60-68
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• 2019

In this paper, we propose the adaptive beamforming algorithm for the MIMO (Multi-Input Multi-Out)-OFDMA(Orthogonal Frequency Division Multiplexing Access)system to improve the performance. The performance of MIMO-OFDMA systems is greatly decreased in the wireless channel environment with multiusers, because the received signals are much distorted by a cochannel interference (CCI) during the space-time decoding. The proposed approach can track the DOA of each signal from the multiple antennas of the desired user without being greatly dependent on the impinging angle. And beams are directed toward the multiple transmitters of the desired user while null beams are directed toward interference directions. Therefore, we can can effectively cancel CCI and mitigate the impairment of delay spread while preserving the STC(space time code) diversity. BER performance improvement is investigated through computer simulation by applying the proposed approach to MIMO-OFDMA system in a multipath fading channel with CCI.