• The Journal of the Acoustical Society of Korea
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• v.17 no.4
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• pp.42-50
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• 1998

본 논문에서는 Gram-Schmidt 구조와 Inverse Power Method를 이용한 고유 부공간 추정 방법을 제안하고 입사각을 추정하는 문제에 적용하여 성능을 평가하였다. 그리고, 어레 이 센서들이 가운데를 중심으로 대칭으로 배열되어 있을 때, 전후방 GS 필터를 이용한 향 상된 고유 부공간 방법을 제안하였다. 그리고, 제안한 방법들을 제한조건을 갖는 gradient search 방법과 비교하였다.

• The Journal of the Korea institute of electronic communication sciences
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• v.15 no.5
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• pp.849-856
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• 2020

The Angle-of-Arrival(AOA) information for an array antenna receiver is one of the important factors for estimating the location of specific signals and detecting signals efficiently, in various situations. The AOA estimator in the satellite environment can rapidly calculate the AOA information in the wide area, utilizing a planar (grid, circular) array antenna mounted on the satellite. Since the satellite receiver has the limitation of the array antenna size, the concentric circular (ring) array (CCA or CRA) antenna structure with comparatively small size but with multiple antenna elements is more efficient than the uniform circular array (UCA) structure, for the satellite environment. In this paper, we introduce a cascade AOA estimation algorithm based on CRA, consisting of CAPON and Beamspace MUSIC. In addition, we provide computer simulation examples for verifying the estimation performance of the cascade AOA estimation algorithm based on CRA and compare it to the case of UCA.

• Journal of Advanced Navigation Technology
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• v.24 no.1
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• pp.47-52
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• 2020

Direction of arrival (DoA) estimation is a scheme of estimating the directions of targets by analyzing signals generated or reflected from the targets and is used in various fields. Artificial neural networks (ANN) is a field of machine learning that mimics the neural network of living organisms. They show good performance in pattern recognition. Although researches has been using ANNs to estimate the DoAs, there are limitationsin dealing with variations of the signal-to-noise ratio (SNR) of the target signals. In this paper, we propose a three-stage ANN algorithm for DoA estimation. The proposed algorithm can minimize the performance reduction by applying the model trained in a single SNR environment to various environments through a 'noise reduction process'. Furthermore, the scheme reduces the difficulty in learning and maintains efficiency in estimation, by employing a process of DoA shift. We compare the performance of the proposed algorithm with Cramer-Rao bound (CRB) and the performances of existing subspace-based algorithms and show that the proposed scheme exhibits better performance than other schemes in some severe environments such as low SNR environments or situations in which targets are located very close to each other.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.30 no.2
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• pp.169-172
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• 2019

Frequency-modulated continuous wave(FMCW) radars with array antennas are widely used because of their light weight and relatively high resolution. A usual approach for the joint range and angle estimation of a target using an array FMCW radar is to create a range-angle matrix with the deramped received signal, and subsequently apply two-dimensional(2D) frequency estimation methods such as 2D fast Fourier transform on the range-angle matrix. However, such frequency estimation approaches cause bias errors since the frequencies in the range-angle matrix are not independent. Therefore, we propose a new maximum likelihood-based algorithm for joint range and angle estimation of targets using array FMCW radar, and demonstrate that the proposed algorithm achieves the Cram?r-Rao bounds, both for range as well as angle estimation.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.4
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• pp.965-970
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• 2013

It is important work to extract saliency regions from an image as preprocessing for various image processing methods. In this paper, we introduce an improved method to estimate saliency value of each pixel from an image. The proposed method is an improved work of the previously studied method using color and statistical framework to estimate saliency values. At first, saliency value of each pixel is calculated using the local contrast of an image region at various scales and the most significant saliency pixel is determined using saliency value of each pixel. Then, saliency value of each pixel is again estimated using gauss weight with respect to the most significant saliency pixel and the saliency of each pixel is determined to calculate initial probability. At last, the saliency value of each pixel is calculated by Bayes' rule. The experiments show that our approach outperforms the current statistical based method.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.11C
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• pp.957-964
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• 2010

In this paper, we propose an indoor positioning algorithm based on 3 points near field angle-of-arrival estimation without side information. The conventional angle-of-arrival based positioning scheme requires the distance between the listener and the center of two points which is obtained by a received signal strength based range estimation. However, a received signal strength is affected by structure of room, placement of furniture, and characteristic of signal, these effects cause a large error to estimation of angle. In this paper, the proposed positioning scheme based on near field angle-of-arrival estimation can be used to estimate the position of listener without a prior distance information, just using time-difference-of-arrival information given from 3 points microphones. The performance of the proposed scheme is shown by cumulative distribution function of root mean squared error.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.28 no.11
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• pp.886-893
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• 2017

Recently, for detection of low-RCS targets, bistatic radar and multistatic radar have been widely employed. In this paper, we present the process of deriving the received signal modeling of the bistatic MIMO radar system and deals with the performance analysis of applying the bistatic signal to the ML arrival angle estimation algorithm. In case of the ML algorithm, as the number of the targets increases, azimuth search dimension for DOA estimation also increases, which implies that the ML algorithm for multiple targets is computationally very intensive. To solve this problem a closed-form expression of estimation error is presented for performance analysis of the algorithm.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.15 no.7
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• pp.669-676
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• 2004

In this paper, a new algorithm is proposed for resolving multiple broadband incoherent sources incident on a uniform linear array. The proposed method dose not require any initial estimates for finding the transformation matrix, while the Coherent Signal-Subspace Method(CSM) proposed by Wang and Kaveh requires preliminary estimates of multigroup source location. An effective procedure is derived for finding the enhanced spectral density matrix at the center frequency using signal enhancement approach and then constructing a common signal subspace by selecting a unitary transformation matrix which is obtained via rotation of signal subspace method. The proposed approach is found to provide superior performance relative to that obtained with the CSM method in terms of sample bias of direction-of-arrival estimates.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.8C
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• pp.769-774
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• 2005

If the angle of arrival (AOA) of a source is perturbed due to some reasons in a statistical way as in the environment of wireless mobile communications, a new model appropriate for such environment should be used instead of the point source model. In this paper, an angel-perturbed source model is proposed and an estimation method based on the eigen-decomposition tecklique is investigated under the model. The asymptotic distribution of the estimation errors is obtained to observe the statistical properties.

• 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.