• Journal of the Institute of Electronics Engineers of Korea SD
• /
• v.44 no.11
• /
• pp.137-141
• /
• 2007

This paper proposes a cost-effective architecture design of an angle-of-arrival (AOA) estimator based on the multiple signal identification and classification (MUSIC) algerian in UWB systems adapting Multi-band OFDM (MB-OFDM) techniques with two-receive antennas. In the proposed method, by modifying the equations of algorithm in order to remove the high computational functions, the computation power can be significantly reduced without significant performance degradation. The proposed architecture is designed and verified by Verilog HDL, and implemented into 0.13um CMOS standard cell and Xilinx FPGA circuits for the estimation of hardware complexity and computation power. From the results of the implementations, we can find that the proposed circuits reduces the hardware complexity by about 43% and the estimated computation power by about 23%, respectively, compared to the architecture employing the original MUSIC algorithm.

• Journal of Advanced Navigation Technology
• /
• v.20 no.4
• /
• pp.367-373
• /
• 2016

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 $0.7^{\circ}$ 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.

• Journal of the Korean Institute of Telematics and Electronics
• /
• v.25 no.12
• /
• pp.1522-1531
• /
• 1988

The purpose of this paper is to explain eigenstructure based spatial spectrum estimation algorithms computing better estimates than the other approaches. Also, as an approach to overcome performance degradations in a multipath environments, the notion of forward and backwark spatial smoothing is discussed. Intensive simulation results,which include the comparisons of the eigenbased spatial spectral estimation algorithms in the situations of faulty estimation of the number of signals, are presented. The simulation results have shown that overestimation of the number of signals is more desirable than underestimation in using EV (Eigen Vector) and MUSIC (Multiple Signal Classification) algorithms and that underestimation of the number of signals is better strategy than overestimation in using eigenstructure based LP(Linear Prediction) algorithms.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
• /
• 2001.11b
• /
• pp.1323-1328
• /
• 2001

The theory of NAH is based on the assumption of reflection free. However, it is not always possible to meet this condition in many practical cases. Thus, a decomposition of direct and reflected fields is needed to apply NAH to reflective condition for noise problems. In addition, the decomposition of direct and reflected field can give acoustic characteristics of reflecting surfaces. This paper presents that in this condition the decomposition can also be successfully done by MUSIC(Multiple Signal Classification) power method and beamforming method, and that numerical simulation and real experiments verify its performance.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
• /
• v.26 no.9
• /
• pp.806-813
• /
• 2015

In order to satisfy several conditions with respect to size, weight, and costs, automotive radars use an antenna consisting of a small number of receiving channels. If RELAX technique is applied to the automotive radars, angles of targets located in antenna beam can be estimated as well as the number of the targets. However, a small number of receiving channels in the antenna leads to inaccurate spectral estimation in angle domain, which in turn degrades performance of RELAX technique. Therefore, in this study, root-MUSIC technique coupled with MDL criterion is introduced to decide accurate angles of targets in antenna beam. In simulations, we show superior performance of proposed scheme using simulation results when three point targets are located in antenna beam.

• Journal of Advanced Navigation Technology
• /
• v.16 no.4
• /
• pp.649-656
• /
• 2012

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.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.12 no.12
• /
• pp.5860-5876
• /
• 2018

A single snapshot data can only provide limited amount of information so that the rank of covariance matrix is not full, which is not adopted to complete the parameter estimation directly using the traditional super-resolution method. Aiming at solving the problem, a joint time delay and angle estimation using matrix pencil method based on information reconstruction vector for orthogonal frequency division multiplexing (OFDM) signal is proposed. Firstly, according to the channel frequency response vector of each array element, the algorithm reconstructs the vector data with delay and angle parameter information from both frequency and space dimensions. Then the enhanced data matrix for the extended array element is constructed, and the parameter vector of time delay and angle is estimated by the two-dimensional matrix pencil (2D MP) algorithm. Finally, the joint estimation of two-dimensional parameters is accomplished by the parameter pairing. The algorithm does not need a pseudo-spectral peak search, and the location of the target can be determined only by a single receiver, which can reduce the overhead of the positioning system. The theoretical analysis and simulation results show that the estimation accuracy of the proposed method in a single snapshot and low signal-to-noise ratio environment is much higher than that of Root Multiple Signal Classification algorithm (Root-MUSIC), and this method also achieves the higher estimation performance and efficiency with lower complexity cost compared to the one-dimensional matrix pencil algorithm.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
• /
• v.30 no.4
• /
• pp.275-281
• /
• 2019

A synthetic aperture radar(SAR) satellite is more effective than an optical satellite for target analysis because an SAR satellite can provide two-dimensional electromagnetic scattering distribution of a target during all-weather and day-and-night operations. To conduct target analysis while considering the earth observation interval of an SAR satellite, observing a specific area as wide as possible would be advantageous. However, wider the observation area, worse is the resolution of the associated SAR satellite image. Although conventional methods for improving the resolution of radar images can be employed for addressing this issue, few studies have been conducted for improving the resolution of SAR satellite images and analyzing the performance. Hence, in this study, the applicability of conventional methods to SAR satellite images is investigated. SAR target detection was first applied to Korea Multipurpose Satellite-5(KOMPSAT-5) SAR images provided by Korea Aerospace Research Institute for extracting target responses. Extrapolation, RELAX, and MUSIC algorithms were subsequently applied to the target responses for improving the resolution, and the corresponding performance was thereby analyzed.

• Journal of Korean Society of Coastal and Ocean Engineers
• /
• v.35 no.6
• /
• pp.109-120
• /
• 2023

The High-Frequency Radar (HFR) is an equipment designed to measure real-time surface ocean currents in broad maritime areas.It emits radio waves at a specific frequency (HF) towards the sea surface and analyzes the backscattered waves to measure surface current vectors (Crombie, 1955; Barrick, 1972).The Seasonde HF Radar from Codar, utilized in this study, determines the speed and location of radial currents by analyzing the Bragg peak intensity of transmitted and received waves from an omnidirectional antenna and employing the Multiple Signal Classification (MUSIC) algorithm. The generated currents are initially considered ideal patterns without taking into account the characteristics of the observed electromagnetic wave propagation environment. To correct this, Antenna Pattern Measurement (APM) is performed, measuring the strength of signals at various positions received by the antenna and calculating the corrected measured vector to radial currents.The APM principle involves modifying the position and phase information of the currents based on the measured signal strength at each location. Typically, experiments are conducted by installing an antenna on a ship (Kim et al., 2022). However, using a ship introduces various environmental constraints, such as weather conditions and maritime situations. To reduce dependence on maritime conditions and enhance economic efficiency, this study explores the possibility of using unmanned aerial vehicles (drones) for APM. The research conducted APM experiments using a high-frequency radar installed at Dangsa Lighthouse in Dangsa-ri, Wando County, Jeollanam-do. The study compared and analyzed the results of APM experiments using ships and drones, utilizing the calculated radial currents and surface current fields obtained from each experiment.

• Journal of the Institute of Electronics and Information Engineers
• /
• v.51 no.5
• /
• pp.177-187
• /
• 2014

This paper proposes a fast subspace tracking methods, which is called GVFF FAPI, based on FAPI (Fast Approximated Power Iteration) method and GVFF RLS (Gradient-based Variable Forgetting Factor Recursive Lease Squares). Since the conventional FAPI uses a constant forgetting factor for estimating covariance matrix of source signals, it has difficulty in applying to non-stationary environments such as continuously changing DOAs of source signals. To overcome the drawback of conventioanl FAPI method, the GVFF FAPI uses the gradient-based variable forgetting factor derived from an improved means square error (MSE) analysis of RLS. In order to achieve the decreased subspace error in non-stationary environments, the GVFF-FAPI algorithm used an improved forgetting factor updating equation that can produce a fast decreasing forgetting factor when the gradient is positive and a slowly increasing forgetting factor when the gradient is negative. Our numerical simulations show that GVFF-FAPI algorithm offers lower subspace error and RMSE (Root Mean Square Error) of tracked DOAs of source signals than conventional FAPI based MUSIC (MUltiple SIgnal Classification).