• The Journal of the Korea institute of electronic communication sciences
• /
• v.13 no.4
• /
• pp.713-720
• /
• 2018

The Signal Intelligence (SIGINT) system based on Angle-of-Arrival(AOA) estimation, interference suppression, and transmission beamforming techniques is a cutting edge technology for efficiently collecting various signal information. In this paper, we present the efficient structure of a satellite system consisted of an AOA estimator, an adaptive beamformer, a signal processing and D/B unit, and a transmission beamformer, for collecting signal information. For accurately estimating AOAs of various signals, efficiently suppressing interference or jamming signals, and efficiently transmitting the collected information or data, we employ Multiple Signal Classification (MUSIC), Minimum Variance Distortionless Response (MVDR), and Minimum Mean Square Error (MMSE) algorithms, respectively. Also, we evaluate and analysis the performance of the presented satellite system through the computer simulation.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.13 no.6
• /
• pp.1207-1212
• /
• 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 Positioning, Navigation, and Timing
• /
• v.9 no.1
• /
• pp.7-13
• /
• 2020

As a countermeasure against the threat of jamming which can disrupt operation of the Global Positioning System (GPS) receivers, various kinds of technique to estimate the Direction-Of-Arrivals (DOAs) of incoming jamming signals have been widely studied, and among them, the MUltiple SIgnal Classification (MUSIC) algorithm is known to provide very high resolution. However, since the previous studies regarding the MUSIC algorithm does not consider the orientation of each antenna element of antenna arrays, there is a possibility that DOA estimation performance degrades in the case of a misaligned antenna array whose antenna elements are not oriented along the same direction. As an effort to solve this problem, there exists a previous work which presents an MUSIC-based method for DOA estimation. However, the error between the real and measured values of each antenna orientation is not taken into consideration. Therefore, in this paper, the effect of the aforementioned error on the DOA estimation performance in the case of a misaligned antenna array is analyzed by simulations.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.37 no.6
• /
• pp.48-59
• /
• 2000

Eigendecomposition based direction-of-arrival(DOA) estimation algorithm such as MUSIC(multiple signal classification) is known to perform well and provide high resolution in white noise environment. However, its performance degrades severely when the noise process is not white. In this paper we consider the DOA estimation problem in a colored noise environment as a problem of extracting periodic signals from noise, and we take the problem to the wavelet domain. Covariance matrix of multiscale components which are obtained by taking wavelet decomposition on the noise has a special structure which can be approximated with a banded sparse matrix. Compared with noise the correlation between multiscale components of narrowband signal decays slowly, hence the covariance matrix does not have a banded structure. Based on this fact we propose a DOA estimation algorithm that transforms the covariance matrix into wavelet domain and removes noise components located in specific bands. Simulations have been carried out to analyze the proposed algorithm in colored noise processes with various correlation properties.

• The Journal of the Acoustical Society of Korea
• /
• v.24 no.5
• /
• pp.294-300
• /
• 2005

Generally, traditional approaches to track the target position are to estimate ranges and bearings by 2-D MUSIC (MUltiple 519na1 Classification) method. and to associate estimates of 2-D MUSIC made at different time points with the right targets by JPDA (Joint Probabilistic Data Association) filter in the near field. However, the disadvantages of these approaches are that these have the data association Problem in tracking multiple targets. and that these require the heavy computational load in estimating a 2-D range/bearing spectrum. In case multiple targets are adjacent. the tracking performance degrades seriously because the estimate of each target's Position has a large error. In this paper, we proposed a new tracking algorithm using Position innovations extracted from the senor output covariance matrix in the near field. The proposed algorithm is demonstrated by the computer simulations dealing with the tracking of multiple closing and crossing targets.

• Journal of Electrical Engineering and Technology
• /
• v.8 no.2
• /
• pp.288-294
• /
• 2013

The diagnosis of motor failures using an on-line method has been the aim of many researchers and studies. Several spectral analysis techniques have been developed and are used to facilitate on-line diagnosis methods in industry. This paper discusses the first application of a motor flux spectral analysis to the identification of broken rotor bar (BRB) faults in induction motors using a multiple signal classification (MUSIC) technique as an on-line diagnosis method. The proposed method measures the leakage flux in the radial direction using a radial flux sensor which is designed as a search coil and is installed between stator slots. The MUSIC technique, which requires fewer number of data samples and has a higher detection accuracy than the traditional fast Fourier transform (FFT) method, then calculates the motor load condition and extracts any abnormal signals related to motor failures in order to identify BRB faults. Experimental results clearly demonstrate that the proposed method is a promising candidate for an on-line diagnosis method to detect motor failures.

• Journal of the Institute of Convergence Signal Processing
• /
• v.4 no.3
• /
• pp.1-6
• /
• 2003

It is difficult to detect and to track the moving targets like tanks and diesel vehicles due to the variety of terrain and moving of targets. It is possible to be happened the aliasing conditions as the difficulty of antenna deployment in the complex environment like the battle fields. In this paper, we study the problem of detecting and tracking of moving targets which are emitting wideband signals under severe spatial aliasing conditions because of the sparse arrays. We developed a direction of arrival(DOA) estimation algorithm based on subband MUSIC(Multiple Signal Classification) method which produces high-resolution estimation. In this algorithm, the true bearings are invariant regardless of changes of frequency bands while the aliased false bearings vary. As a result, the proposed algorithm overcomes the aliasing effects and improves the localization performance in sparse passive arrays.

• Smart Structures and Systems
• /
• v.24 no.2
• /
• pp.173-182
• /
• 2019

Due to the degradation of beamforming properties at angles close to $0^{\circ}$ to $180^{\circ}$, linear array does not have a complete $180^{\circ}$ inspection range but a smaller one. This paper develops a improved sensor array with two additional sensors above and below the linear sensor array, and presents time difference and two dimensional multiple signal classification (2D-MUSIC) based impact localization for omni-directional localization on composite structures. Firstly, the arrival times of impact signal observed by two additional sensors are determined using the wavelet transform and compared, and the direction range of impact source can be decided in general, $0^{\circ}$ to $180^{\circ}$ or $180^{\circ}$ to $360^{\circ}$. And then, 2D-MUSIC based spatial spectrum formula using uniform linear array is applied for locate accurate position of impact source. When the arrival time of impact signal observed by two additional sensors is equal, the direction of impact source can be located at $0^{\circ}$ or $180^{\circ}$ by comparing the first and last sensor of linear array. And then the distance is estimated by time difference algorithm. To verify the proposed approach, it is applied to a quasi-isotropic epoxy laminate plate and a stiffened composite panel. The results are in good agreement with the actual impact occurring position.

• The Journal of the Acoustical Society of Korea
• /
• v.39 no.3
• /
• pp.179-190
• /
• 2020

In this paper, we estimated the Direction of Arrival (DOA) using Conventional BeamForming (CBF), adaptive beamforming and compressive beamforming. Minimum Variance Distortionless Response (MVDR) and Multiple Signal Classification (MUSIC) are used as the adaptive beamforming, and grid-free compressive sensing is applied for the compressive sensing beamforming. Theoretical background and limitations of each technique are introduced, and the performance of each technique is compared through simulation and real experiments. The real experiments are conducted in the presence of reflected signal, transmitting a sound using two speakers and receiving acoustic data through a linear array consisting of eight microphones. Simulation and experimental results show that the adaptive beamforming and the grid-free compressive beamforming have a higher resolution than conventional beamforming when there are uncorrelated signals. On the other hand, the performance of the adaptive beamforming is degraded by the reflected signals whereas the grid-free compressive beamforming still improves the conventional beamforming resolution regardless of reflected signal presence.

• Journal of Positioning, Navigation, and Timing
• /
• v.11 no.2
• /
• pp.91-98
• /
• 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.