• Title/Summary/Keyword: adaptive beamforming.

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Implementation and Performance Analysis of the Adaptive Beamformer with Subarray Architecture (부배열 합성을 이용한 적응적 빔형성기의 구현 및 성능 분석)

  • Jang, Youn-Hui;Hong, Dong-Hee;Choi, Seong-Hee
    • The Journal of Korean Institute of Electromagnetic Engineering and Science
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    • v.24 no.4
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    • pp.448-458
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    • 2013
  • In this paper, we present the performance and the experimental results of the adaptive beamformer in the radar system with the planar active array. The study of the adaptive beamformer has already been performed in several literatures, but it is difficult to find the results or examples those are implemented in the actual radar system. Here we employ the adaptive beamformer to the practical radar system with subarray architecture. The performance of beamformer will be demonstrated by modeling and simulation and finally the far-field experimental results.

Sequential LS Algorithms for Smart Antennas (스마트안테나용 S-LS 알고리즘)

  • Park, Jaedon;Tuan, Le-Minh;Giwan Yoon;Kim, Jewoo
    • 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.

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Multi-Channel Speech Enhancement Algorithm Using DOA-based Learning Rate Control (DOA 기반 학습률 조절을 이용한 다채널 음성개선 알고리즘)

  • Kim, Su-Hwan;Lee, Young-Jae;Kim, Young-Il;Jeong, Sang-Bae
    • 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.

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A novel class of LMS Algorithms with exponential step size for Smart Antenna Applications (Exponential 스텝사이즈를 이용한 스마트안테나용 블라인드 LMS 알고리즘)

  • Tuan, Le-Minh;Park, Jaedon;Giwan Yoon;Kim, Jewoo
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2001.10a
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    • pp.331-335
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    • 2001
  • In this paper, we propose two novel blind LMS algorithms, called exponential step sire LMS algorithms (ES-LMS), for adaptive array antennas whose convergence speed is increased, hence they are much more capable of tracking the desired signal than the conventional LMS algorithms. Both of the algorithms require neither spatial knowledge nor reference signals since they use the finite symbol property of digital signal. Computer simulations were carried cot in CDMA environment affected by multi-path Rayleigh fading to verify the performance of the two proposed algorithms.

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Input Signal Model Analysis for Adaptive Beamformer (적응 빔형성기의 입력신호 모델 분석)

  • Mun, Ji-Youn;Hwang, Suk-Seung
    • The Journal of the Korea institute of electronic communication sciences
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    • v.12 no.3
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    • pp.433-438
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    • 2017
  • Containing an Angle-of-Arrival(: AOA) estimation and interference suppression techniques, an adaptive beamformer is one of core techniques for the Signal Intelligence(: SIGINT) which collect various intelligence utilizing cutting edge devices including the radar and satellite. It generates a beam with the directivity in a corresponding direction, to efficiently receive a signal from the specific direction, using antenna array. In this paper, we present the received signal model including interference signals and noise, which can be applied to an input of the signal intelligence satellite system equipped with the AOA estimation and the interference cancellation techniques, and analysis the characteristics of various signals, which can be included in the proposed received signal model. This proposed signal model can be directly applied to the performance evaluation for a variety of beamforming techniques. Also, we verify the spectrum characteristic of the presented received signal model in the frequency domain through computer simulation examples.

A Study on Jammer Suppression Algorithm for Non-stationary Jamming Environment (재머의 크기가 변하는 환경에서의 억제 알고리즘 연구)

  • Yoon, Ho-Jun;Lee, Kang-In;Chung, Young-Seek
    • 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.

A Beamformer for Antenna Arrays with Faulty Elements (결함 소자가 존재하는 안테나 배열을 위한 빔 형성기)

  • Kim, Gi-Man;Cha, Il-Hwan
    • The Journal of the Acoustical Society of Korea
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    • v.15 no.6
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    • pp.12-15
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    • 1996
  • An array often has faulty elements in real operation. The faulty elements, producing no output or highly reduced gain than other normal elements, cause an elevated sidelobe level and fail to reject the interference signals in an adaptive beamformer. In this paper we have presented the beamforming algorithm for arrays with faulty elements. In the ideal case, an autocorrelation matrix computed from array output data is the toeplitz. However, the inverse of the autocorrelation matrix computed from array with faulty elements can not be obtained due to deficient values of matrix. To overcome this problem, an adaptive beamforming algorithm using the average values of the diagonal terms of matrix is proposed. The computer simulations have been performed to study the performance of the presented method. We have been able to solve the degrees-of-freedom problem that is the drawback of the previous subaperture processing technique.

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A Time-Domain GSC Algorithm Based on Wavelet Filter (웨이브렛 필터 기반의 시간 영역 GSC 알고리즘)

  • Hong, Chun-Pyo;Whang, Seok-Yoon;Kim, Chang-Hoon;Yang, Jeen-Mo
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.35 no.11C
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    • pp.948-956
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    • 2010
  • Griffiths and Jim has proposed a beamforming structure called GSC algorithm, in which antenna elements are grouped into main-channel and sub-channel, and sidelobe is reduced by applying adaptive LMS algorithm. This paper proposes WLMS-GSC algorithm where the Haar and Daubechies wavelet filters are used to process array antenna output, instead of using subtractor filter. We analyze characteristics of the proposed WLMS-GSC algorithm. The WLMS-GSC has characteristic of reducing the computational requirement one-half compared to the LMS-GSC algorithm. In addition, we obtain MSE characteristics and adaptive beampattern of WLMS-GSC algorithm, and compared with the performance of LMS-GSC algorithm. The simulation results show that the WLMS-GSC algorithm proposed in this paper gives better or almost the same performance, compared to the LMS-GSC algorithm. In addition, the newly proposed structure has advantage of low computational requirements.

Enhanced Index Assignment for Beamforming with Limited-rate Imperfect Feedback (피드백 에러가 있는 빔포밍 시스템에서 개선된 인덱스 배치기법)

  • Park, Noe-Yoon;Kim, Young-Ju
    • Journal of the Institute of Electronics Engineers of Korea TC
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    • v.49 no.5
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    • pp.7-14
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    • 2012
  • The quantized beamforming systems always need the channel state information, which must be quantized into a finite set of vectors (named codebook), and feedback only sends the index representing the desired vector. Thereby it minimized the impact of feedback errors, caused by feedback overhead and delay. In this regard, index assignment (IA) methods, an exhaustive-search and group-based schemes, have been presented for minimizes the performance degradation without additional feedback bits. In this paper, we proposed enhanced group-based IA method, which used the optimal codebook design with chordal distance, having the adaptive properties in application of the existing IA methods. When the number of transmit antennas is 4 and LTE codebook is used, Monte-Carlo simulations verify that the proposed scheme has a power advantage of 0.5~1dB to obtain the same bit error rate than methods without IA, and it has 0.1~0.2 dB better performance compared with the existing IA methods over same environment.