• 제목/요약/키워드: Multiple Signal Classification

검색결과 133건 처리시간 0.023초

Deep Learning-Based Modulation Detection for NOMA Systems

  • Xie, Wenwu;Xiao, Jian;Yang, Jinxia;Wang, Ji;Peng, Xin;Yu, Chao;Zhu, Peng
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제15권2호
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    • pp.658-672
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    • 2021
  • Since the signal with strong power need be demodulated first for successive interference cancellation (SIC) receiver in non-orthogonal multiple access (NOMA) systems, the base station (BS) need inform the near user terminal (UT), which has allocated higher power, of the far UT's modulation mode. To avoid unnecessary signaling overhead of control channel, a blind detection algorithm of NOMA signal modulation mode is designed in this paper. Taking the joint constellation density diagrams of NOMA signal as the detection features, the deep residual network is built for classification, so as to detect the modulation mode of NOMA signal. In view of the fact that the joint constellation diagrams are easily polluted by high intensity noise and lose their real distribution pattern, the wavelet denoising method is adopted to improve the quality of constellations. The simulation results represent that the proposed algorithm can achieve satisfactory detection accuracy in NOMA systems. In addition, the factors affecting the recognition performance are also verified and analyzed.

Performance Analysis of the Anti-Spoofing Array Antenna with Eigenvector Nulling Algorithm

  • Lee, Kihoon;Song, Min Kyu;Lee, Jang Yong
    • Journal of Positioning, Navigation, and Timing
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    • 제11권3호
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    • pp.181-189
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    • 2022
  • The public open signals from Global Navigation Satellite System (GNSS) including Global positioning system (GPS) are used widely by many peoples in the world except for the public regulated restriction signals which are encrypted. Nowadays there are growing concerns about GNSS signal spoofing which can deceive the GNSS receivers by abusing these open services. To counter these spoofing threats, many researches have been studied including array antenna techniques which can detect the direction of arrival by means of Multiple Signal Classification (MUSIC) algorithm. Originally the array antenna techniques were developed to countermeasure the jamming signal in electronic warfare by using the nulling or beamforming algorithm toward a certain direction. In this paper, we study the anti-spoofing techniques using array antenna to overcome the jamming and spoofing issues simultaneously. First, we will present the theoretical analysis results of spoofing signal response of Minimum Variance Distortionless Response (MVDR) algorithm in array antenna. Then the eigenvector algorithm of covariance matrix is suggested and verified to work with the existing anti-jamming method. The modeling and simulation are used to verify the effectiveness of the anti-spoofing algorithm. Also, the field test results show that the array antenna system with the proposed algorithms can perform the anti-spoofing function. This anti-spoofing method using array antenna is very effective in the view point of solving both the jamming and spoofing problems using the same array antenna hardware.

초음파신호의 특징 파라메터 및 증거축적 방법을 이용한 콘크리트 강도 분류 (Pattern Classification of the Strength of Concrete by Feature Parameters and Evidence Accumulation of Ultrasonic Signal)

  • 김세동;신동환;이영석;김성환
    • 대한전기학회논문지:전력기술부문A
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    • 제48권10호
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    • pp.1335-1343
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    • 1999
  • This paper presents concrete pattern recognition method to identify the strength of concrete by evidence accumulation with multiple parameters based on artificial intelligence techniques. At first, zero-crossing(ZCR), mean frequency(MEANF), median frequency(MEDF) and autoregressive model coefficient(ARC) are extracted as feature parameters from ultrasonic signal of concrete. Pattern recognition is carried out through the evidence accumulation procedure using distance measured with reference parameters. A fuzzy mapping function is designed to transform the distances for the application of the evidence accumulation method. Results are presented to support the feasibility of the suggested approach for concrete pattern recognition.

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Iris Segmentation and Recognition

  • Kim, Jae-Min;Cho, Seong-Won
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • 제2권3호
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    • pp.227-230
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    • 2002
  • A new iris segmentation and recognition method is described. Combining a statistical classification and elastic boundary fitting, the iris is first segmented robustly and accurately. Once the iris is segmented, one-dimensional signals are computed in the iris and decomposed into multiple frequency bands. Each decomposed signal is approximated by a piecewise linear curve connecting a small set of node points. The node points represent features of each signal. The similarity measture between two iris images is the normalized cross-correlation coefficients between simplified signals.

Implementation of High-Resolution Angle Estimator for an Unmanned Ground Vehicle

  • Cha, SeungHun;Yeom, DongJin;Kim, EunHee
    • Journal of electromagnetic engineering and science
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    • 제15권1호
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    • pp.37-43
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    • 2015
  • We implemented a real-time radar system for an unmanned ground vehicle designed to run on unpaved or bumpy roads. The system must be able to detect slow targets in a cluttered environment and cover wide angular sections with high resolution at the same time. The system consists of array antennas, preprocessors for digital beam forming, and digital signal processors for the detection process which uses sawtooth waveforms and high-resolution estimation, and is called forward/backward spatial smoothing beamspace multiple signal classification (FBSS BS-MUSIC). We show that the sawtooth waveforms enhance the angular estimation capability of FBSS BS-MUSIC in addition to their well-known advantages of removing the ambiguity of targets and detecting slow targets with improved velocity resolution.

Computational Complexity Analysis of Cascade AOA Estimation Algorithm Based on FMCCA Antenna

  • Kim, Tae-yun;Hwang, Suk-seung
    • Journal of Positioning, Navigation, and Timing
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    • 제11권2호
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    • pp.91-98
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    • 2022
  • In the next generation wireless communication system, the beamforming technique based on a massive antenna is one of core technologies for transmitting and receiving huge amounts of data, efficiently and accurately. For highly performed and highly reliable beamforming, it is required to accurately estimate the Angle of Arrival (AOA) for the desired signal incident to an antenna. Employing the massive antenna with a large number of elements, although the accuracy of the AOA estimation is enhanced, its computational complexity is dramatically increased so much that real-time communication is difficult. In order to improve this problem, AOA estimation algorithms based on the massive antenna with the low computational complexity have been actively studied. In this paper, we compute and analyze the computational complexity of the cascade AOA estimation algorithm based on the Flexible Massive Concentric Circular Array (FMCCA). In addition, its computational complexity is compared to conventional AOA estimation techniques such as the Multiple Signal Classification (MUSIC) algorithm with the high resolution and the Only Beamspace MUSIC (OBM) algorithm.

Highly Efficient and Precise DOA Estimation Algorithm

  • Yang, Xiaobo
    • Journal of Information Processing Systems
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    • 제18권3호
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    • pp.293-301
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    • 2022
  • Direction of arrival (DOA) estimation of space signals is a basic problem in array signal processing. DOA estimation based on the multiple signal classification (MUSIC) algorithm can theoretically overcome the Rayleigh limit and achieve super resolution. However, owing to its inadequate real-time performance and accuracy in practical engineering applications, its applications are limited. To address this problem, in this study, a DOA estimation algorithm with high parallelism and precision based on an analysis of the characteristics of complex matrix eigenvalue decomposition and the coordinate rotation digital computer (CORDIC) algorithm is proposed. For parallel and single precision, floating-point numbers are used to construct an orthogonal identity matrix. Thus, the efficiency and accuracy of the algorithm are guaranteed. Furthermore, the accuracy and computation of the fixed-point algorithm, double-precision floating-point algorithm, and proposed algorithm are compared. Without increasing complexity, the proposed algorithm can achieve remarkably higher accuracy and efficiency than the fixed-point algorithm and double-precision floating-point calculations, respectively.

메시브 배열 안테나 형상에 따른 캐스케이드 도래각 추정 알고리즘의 계산 복잡도 분석 (Computational Complexity Analysis of Cascade AOA Estimation Algorithm Based on Massive Array Antenna Configuration)

  • 김태윤;황석승
    • Journal of Positioning, Navigation, and Timing
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    • 제13권3호
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    • pp.277-287
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    • 2024
  • In satellite systems, efficient communication and observation require identifying of specific signal arrival points using onboard antenna systems. When utilizing massive array antennas to estimate the angle of arrival (AOA) of signals, traditional high-performance AOA estimation algorithms such as Multiple Signal Classification (MUSIC) encounter extremely high complexity due to the numerous individual antenna elements. Although, in order to improve this computational complexity problem, the cascade AOA estimation algorithm with CAPON and beamspace-MUSIC was recently proposed, the comparison of the computational complexity of the proposed algorithm across different massive array antenna configurations has not yet been conducted. In this paper, we provide the analyzed results of the computational complexity of the proposed cascade algorithm based on various massive array antennas, and determine an optimal antenna configuration for the efficient AOA estimation in satellite systems.

Considerations for Design and Implementation of a RF Emitter Localization System with Array Antennas

  • Lim, Deok Won;Lim, Soon;Chun, Sebum;Heo, Moon Beom
    • Journal of Positioning, Navigation, and Timing
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    • 제5권1호
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    • pp.37-45
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    • 2016
  • In this paper, design and implementation issues for a network-oriented RF emitter localization system with array antenna are discussed. For hardware, the problem of array mismatch and RF/IF channel mismatch are introduced and the calibration schemes for solving those problems are also provided. For software, it is explained how to overcome the drawback of conventional MUltiple Signal Identification and Classification (MUSIC) algorithm in a point of identifying the number of received signals and problems such as Data Association Problem and Ghost Node Problem in regard to multiple emitter localization are presented with some approaches for getting around those problems. Finally, for implementation, a criterion for arranging each of sensors and a requirement for alignment of array antenna' orientation are also given.

음향 홀로-그래피에서 빔 형성을 이용한 부분 음장 분리 (Beamforming-based Partial Field Decomposition in Acoustical Holography)

  • 황의석;조영만;강연준
    • 한국소음진동공학회논문집
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    • 제11권6호
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    • pp.200-207
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    • 2001
  • In this paper, a new method for Partial field decomposition is developed that is based on the beamforming algorithm for the application of acoustical holography to a composite sound field generated by multiple incoherent sound sources. In the proposed method, source Positions are first predicted by MUSIC(multiple signal classification) algorithm. The composite sound fields can then be decomposed into each partial field by the beamforming. Results of both numerical simulations and experiments show that the method can find each partial field very accurately and effectively, and that it also has Potential to be used for application to distributed sources.

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