Efficient Geo-Location Estimation System using Two-Dimensional MUSIC Algorithm

김수진,임충혁,김창환 제어·로봇·시스템학회 2011 International Journal of Control, Automation, and Vol.9 No.4

In this paper, we propose an efficient two-dimensional geo-location estimation system for mobile social security robots, where the location is obtained by direction of arrival (DOA) and time of arrival (TOA) of the radio signal. The proposed system requires only one reference signal while the conventional systems generally demand more than three reference signals. For estimating TOA and DOA information simultaneously, we employ a two-dimensional multiple signal classification (2-D MUSIC) algorithm. In addition, the performance analysis of proposed system is provided in terms of location accuracy and computational complexity by comparing it with two-dimensional Matrix Pencil (2-D MP) algorithm. The simulation results show that the proposed geo-location estimation system achieves the positioning accuracy within 3 meters in 2 kilo-meters coverage which is usable for mobile robots.

Localization and Size Estimation for Breaks in Nuclear Power Plants

Ting-Han Lin,Ching Chen,Shun-Chi Wu,Te-Chuan Wang,Yuh-Ming Ferng 한국원자력학회 2022 Nuclear Engineering and Technology Vol.54 No.1

Several algorithms for nuclear power plant (NPP) break event detection, isolation, localization, and size estimation are proposed. A break event can be promptly detected and isolated after its occurrence by simultaneously monitoring changes in the sensing readings and by employing an interquartile range-based isolation scheme. By considering the multi-sensor data block of a break to be rank-one, it can be located as the position whose lead field vector is most orthogonal to the noise subspace of that data block using the Multiple Signal Classification (MUSIC) algorithm. Owing to the flexibility of deep neural networks in selecting the best regression model for the available data, we can estimate the break size using multiple-sensor recordings of the break regardless of the sensor types. The efficacy of the proposed algorithms was evaluated using the data generated by Maanshan NPP simulator. The experimental results demonstrated that the MUSIC method could distinguish two near breaks. However, if the two breaks were close and of small sizes, the MUSIC method might wrongly locate them. The break sizes estimated by the proposed deep learning model were close to their actual values, but relative errors of more than 8% were seen while estimating small breaks’ sizes.

고 전력 간섭 환경에서의 GPS AOA 선택 알고리즘

황석승 ( Suk Seung Hwang ) 한국항행학회 2012 韓國航行學會論文誌 Vol.16 No.4

GPS(Global Positioning System)는 사용자 및 물체의 위치를 추정하기 위해 군사용과 상용으로 광범위하게 사용되고 있다. GPS는 다양한 고의적 또는 비고의적 간섭들로부터 영향을 받게 되는데, 이러한 간섭들을 제거하고 효율적인 데이터 수신을 위해 GPS의 정확한 도래각(AOA; angle-of-arrival) 추정이 필요하다. GPS의 신호전력은 잡음이나 간섭에 비해 매우 낮으므로, 역확산(despreading) 이전에 GPS 신호의 AOA를 추정하기는 매우 어려워 일반적으로 역확산 이후에 GPS의 AOA를 추정한다. 하지만, 고 출력의 간섭 존재 시 역확산 이후의 AOA 추정결과는 간섭신호의 AOA 들도 포함하고 있어, 어떤 추정 값이 GPS의 AOA 인지를 결정하여야 한다. 본 논문에서는 추정된 AOA 값들로부터 효과적으로 GPS 신호의 AOA를 선택하기 위한 알고리즘을 제안한다. 제안된 알고리즘은 역확산 이전과 이후의 AOA 들을 비교하여 정확한 GPS 신호의 AOA를 선택한다. 또한, 컴퓨터 시뮬레이션을 통해 GPS AOA 선택 알고리즘의 성능을 확인한다. The Global Positioning System (GPS) is widely utilized for commercial and military applications to estimate the location of the user or object. The GPS suffers from various intentional or unintentional interferers and it requires estimating the accurate angle-of-arrival (AOA) of the GPS signal to suppress interference signals and to efficiently detect GPS data. Since the power of GPS signal is very low comparing with the noise and interference signals, it is extremely difficult to estimate GPS AOA before despreading. Although AOA of GPS signal is usually estimated after despreading, it requires choosing the GPS AOA among results of AOA estimation because they include AOAs of interference and GPS signals when existing high-power interferers. In this paper, we propose the efficient choosing algorithm of the GPS signal among the estimated AOAs. The proposed algorithm compares the estimated results before despreading and after despreading for choosing AOA of GPS signal. Computer simulation examples are presented to illustrate the performance of the proposed algorithm.

잡음 파워 스펙트럼 밀도 추정을 이용한 서로소 배열과 프로퍼게이터 기법 기반의 향상된 도래각 추정 기법

변부근 ( Bu-guen Byun ),유도식 ( Do-sik Yoo ) 한국항행학회 2016 韓國航行學會論文誌 Vol.20 No.4

우리는 도래각 (DoA; direction of arrival) 추정 방법 중 하나인 서로소 배열 기반의 프로퍼게이터 방법을 개선시키는 알고리즘을 제안한다. 서로소 배열 기반의 프로퍼게이터 방법은 특이값 분해없이 도래각을 추정하는 방법으로 서로소 배열 기반의 MUSIC에 비하여 현저히 낮은 복잡도를 지녔으나, 다소 저하된 도래각 추정 성능을 보인다. 우리는 이러한 성능 저하의 원인 중 하나로 잡음의 파워 스펙트럼 밀도를 포함하고 있는 신호의 자기상관행렬의 대각 성분이 사용되고 있지 않음에 있음을 파악하고, 잡음의 파워 스펙트럼 밀도가 장기간에 걸쳐 추정이 가능하다는 사실에 착안하여 신호의 자기상관행렬의 대각 성분을 사용하는 도래각 추정 방법을 제안한다. 우리는 시뮬레이션을 통해 우리가 제안한 방법이 기존의 서로소 배열 기반의 프로퍼게이터 방법보다 연산량을 4배정도 증가시키지만 탐지확률 95% 기준 하에 신호대 잡음비를 1.5dB, 도래각 분해능을 0.7° 만큼 개선시켜 그 성능이 서로소 배열 기반의 MUSIC에 보다 근접함을 관찰한다. We propose an improved direction of arrival (DoA) estimation algorithm based on co-prime array and propagator method. The propagator method with co-prime array does not require singular value decomposition (SVD) requiring much less computational complexity but exhibiting somewhat worse performance in comparison with MUSIC based on co-prime array. We notice that one cause of the performance degradation was in the avoidance of the usage of the diagonal elements of the signal autocorrelation matrix that contains the noise power spectral density. So we propose an algorithm with the diagonal elements of the signal autocorrelation matrix based on the fact that the noise power spectral density can be estimated using noise observation over a long period of time. We observe, through simulations, that the proposed scheme in this paper improves the performance, with 4 times more computational requirement, by signal-to-noise ratio of 1.5dB and by DoA resolution of 0.7° at the detection probability of 95% compared with the previously introduced co-prime array propagator scheme, resulting in performance much closer to that of co-prime array-based MUSIC scheme.

Impact source localization in plate utilizing multiple signal classification

Yang, HongJun,Lee, Young Jun,Lee, Sang Kwon SAGE Publications 2013 Proceedings of the Institution of Mechanical Engin Vol.227 No.4

<P>This article proposed a multiple signal classification method based on array signal processing for impact source localization in a plate. For source localization, the direction of arrival of the wave caused by an impact on a plate and the distance between the impact position and sensor should be estimated. The direction of arrival can be estimated accurately using the multiple signal classification method; the distance can be obtained using the time delay of arrival and the group velocity of the Lamb wave in a plate. The time delay of arrival is experimentally estimated using the continuous wavelet transform for the wave. The group velocity is theoretically obtained based on the elastodynamic theory.</P>

MUSIC 스펙트럼을 이용한 잡음환경에서의 목표 신호 구간 검출

박상준,정상배 한국음성학회 2012 말소리와 음성과학 Vol.4 No.3

In this paper, a target signal detection method using multiple signal classification (MUSIC) algorithm is proposed. The MUSIC algorithm is a subspace-based direction of arrival (DOA) estimation method. Using the inverse of the eigenvalue-weighted eigen spectra, the algorithm detects the DOAs of multiple sources. To apply the algorithm in target signal detection for GSC-based beamforming, we utilize its spectral response for the DOA of the target source in noisy conditions. The performance of the proposed target signal detection method is compared with those of the normalized cross-correlation (NCC), the fixed beamforming, and the power ratio method. Experimental results show that the proposed algorithm significantly outperforms the conventional ones in receiver operating characteristics (ROC) curves.

MUSIC 알고리즘을 이용한 JEM 신호의 Chopping 주파수 추출

송원영,김형주,김성태,신인선,명로훈 한국전자파학회 2019 한국전자파학회논문지 Vol.30 No.3

Jet engine modulation(JEM) signals are widely used in the field of target recognition along with high-range resolution profile and inverse synthetic aperture radar because they provide specific information of the jet engine. To obtain the number of blades of the jet engine, the chopping frequency proportional to the number of blades must be extracted. In the conventional chopping frequency extraction method, an initial threshold value is defined and a method of detecting the chopping peak is used. However, this detection method takes time depending on the signal due to repetitive detection. Thus, in this study, we proposed to extract the chopping frequency using MUltiple SIgnal Classification(MUSIC) algorithm. We applied the MUSIC algorithm to a given JEM signal to find the chopping frequency and determine the blade number candidates. We also applied the MUSIC algorithm to other chopping frequency extractions to determine the score of the candidate groups. Unlike the conventional detection algorithm, which requires repetitive frequency detection, MUSIC algorithm quickly detects the accurate chopping frequency and reduces the calculation time.

Bluetooth 응용을 위한 MUSIC 알고리즘 기반 DoA 추정기의 설계

김종민(Jongmin Kim),오동재(Dongjae Oh),박상훈(Sanghoon Park),이승혁(Seunghyeok Lee),정윤호(Yunho Jung) 한국전기전자학회 2020 전기전자학회논문지 Vol.24 No.1

본 논문에서는 multiple signal classification(MUSIC) 알고리즘을 바탕으로 Bluetooth 저전력 응용 기술에 적용 가능하도록 설계한 각도 추정기를 제안하고, 이를 FPGA로 구현한 결과를 제시한다. MUSIC 알고리즘은 높은 정확도에 따른 많은 연산량이 요구되므로 이를 하드웨어 고속설계 하였고, 실내 시스템의 다양한 해상도의 요구에 대응하기 위해 snapshot 가변을 가능하게 설계하였다. Xilinx zynq-7000으로 구현한 결과 9,081개의 LUTs로 구현함을 확인하였고, 100MHz의 동작주파수로 동작이 가능하도록 설계하였다. In this paper, we propose an angle estimator that is designed to be applied to Bluetooth low-power application technology based on multiple signal classification (MUSIC) algorithm, and present the result of implementation in FPGA. The MUSIC algorithm is designed for H/W high-speed design because it requires a lot of calculations due to high accuracy, and the snapshot variable is designed to cope with various resolution requirements of indoor systems. As a result of the implementation with Xilinx zynq-7000, it was confirmed that 9,081 LUTs were implemented, and it was designed to operate at =the operating frequency of 100MHz.

MUSIC algorithm for location searching of dielectric anomalies from <i>S</i>-parameters using microwave imaging

Park, Won-Kwang,Kim, Hwa Pyung,Lee, Kwang-Jae,Son, Seong-Ho Elsevier 2017 Journal of computational physics Vol.348 No.-

<P><B>Abstract</B></P> <P>Motivated by the biomedical engineering used in early-stage breast cancer detection, we investigated the use of MUltiple SIgnal Classification (MUSIC) algorithm for location searching of small anomalies using <I>S</I>-parameters. We considered the application of MUSIC to functional imaging where a small number of dipole antennas are used. Our approach is based on the application of Born approximation or physical factorization. We analyzed cases in which the anomaly is respectively small and large in relation to the wavelength, and the structure of the left-singular vectors is linked to the nonzero singular values of a Multi-Static Response (MSR) matrix whose elements are the <I>S</I>-parameters. Using simulations, we demonstrated the strengths and weaknesses of the MUSIC algorithm in detecting both small and extended anomalies.</P>

Certain properties of a MUSIC-type imaging functional in inverse scattering from an open sound-hard arc

Elsevier 2017 COMPUTERS & MATHEMATICS WITH APPLICATIONS - Vol.74 No.6

<P><B>Abstract</B></P> <P>This paper concerns a mathematical formulation of the well-known MUltiple SIgnal Classification (MUSIC)-type imaging functional in the inverse scattering problem by an open sound-hard arc. Based on the physical factorization of the so-called Multi-Static Response (MSR) matrix and the structure of left-singular vectors linked to the non-zero singular values of the MSR matrix, we construct a relationship between the imaging functional and the Bessel functions of order 0 , 1 , and 2 of the first kind. We then expound certain properties of MUSIC and present numerical results for several differently chosen smooth arcs.</P>