Earticle

본 논문에서는 재난 발생 시 지향성 스피커와 스마트 디바이스를 활용한 피난 방향 탐지 기법을 제안하고자 한다. 본 논문에서 제안하는 기법은 연기, 소음 등의 원인으로 출구 방향조차 알 수 없는 최악의 재난 환경에서 지향성 스피커로부터 송출되는 가청·비 가청 주파수 대역의 안내 방송을 스마트 디바이스로 수신함으로써, 피난 경로를 안내받을 수 있는 기법이다. 제안하는 기법의 성능평가는 대형 실내공간에서 제조사가 다른 3종류의 스마트 디바이스를 이용하여 스피커로부터 송출되는 소리 신호의 방향을 탐지하여 스피커가 설치된 출구 방향을 탐지하는 것으로 평가하였다. 또한, 거리별 신호 세기와 주파수 특성을 통한 신호 검출 실험을 수행하였다. 실험결과를 통해 스마트 디바이스가 스피커로부터 최대 20m까지 떨어져 있더라도 신호의 송출 방향 탐지가 가능함을 확인하였고, 스마트 디바이스로 8kHz와 20kHz 신호 검출을 통해 본 논문에서 제안하는 기술에 대한 가능성을 확인하였다.

This paper proposes a direction estimation scheme with directional speaker and smart device for evacuation guidance. When there is worst disaster environment filled with smoke and noisy sound, evacuee can not get any information about evacuation routes. The proposed scheme can be used for detecting evacuation routes with audible and inaudible signal from directional speaker. At this point, evacuee can get evacuee guidance by using smartphone application that the proposed scheme is applied. The performance of the proposed scheme is evaluated by experiment with three different types of smart devices in large indoor environment. The purpose of experiment is to detect the direction of transmitted signal from directional speaker. Therefore, The experiment is conducted by analyzing the strength of transmitted signal by distance. The experimental results show that even if the smart device is located up to 20m away from the speaker, it is possible to detect the sending direction of the signal. We confirmed the possibility of the proposed technology in 8kHz and 20kHz signal detection by smart device.

This paper proposes a deep learning-based Direction-of-arrival (DOA) estimation to detect interfered far-field sources. The proposed method consists of a near-field interference rejection network (NFIRnet) and a DOA estimation network (DOAnet). The NFIRnet calculates the near-field components of the covariance matrix by convolutional neural networks with the proposed complex mapper. The near-field components are rejected from the covariance matrix. The DOAnet removes the residuals of the interferences by the proposed self-spatial attention network and estimates the DOAs of the interfered far-field sources. Computer simulations demonstrated that the proposed method had better DOA estimation performance than the conventional methods.

본 연구는 GPS 음영 구간인 터널 환경에서 차량의 위치와 주행 방향을 실시간으로 추정하 기 위한 경량 위치 추정 프레임워크를 제안한다. 제안된 시스템은 단일 UWB 앵커와 차량 탑 재 IMU만을 활용하여, 복잡한 인프라 없이도 고정밀 위치 추정이 가능하도록 설계되었다. UWB CIR 신호로부터 지연 확산, 에너지, 엔트로피 등의 특징을 추출하여 NLOS 환경을 자동 감지하고, 거리 보정을 수행하였다. 또한, IMU 기반 방향 인식을 통해 전진·후진 여부를 판별 하고, 칼만 필터를 적용하여 실시간으로 위치를 갱신하였다. 실제 터널 실험을 통해 단일 앵커 구조에서도 평균 거리 오차를 15.56cm 수준으로 줄이고, 궤적의 연속성과 방향성을 안정적으 로 확보함을 입증하였다. 본 연구는 저비용·경량 구조로도 실도로 환경에서 활용 가능한 차량 위치 추정 기술을 제시하며, 지능형 교통안전 시스템 및 터널 사고 대응 시스템의 핵심 구성요 소로 활용될 수 있다.

This study proposes a lightweight vehicle localization framework designed for real-time estimation of position and driving direction in tunnel environments where GPS signals are unavailable. The proposed system utilizes only a single UWB anchor and an on-vehicle IMU, enabling high-precision positioning without relying on a complex infrastructure. Key features such as delay spread, signal energy, and entropy are extracted from the UWB CIR to automatically detect NLOS conditions and apply distance correction. Additionally, IMU-based direction estimation is employed to distinguish between forward and backward movement, and a Kalman filter is applied to continuously update the vehicle's position in real time. Through real tunnel experiments, the system demonstrates an average distance error of just 15.56 cm, even with a single-anchor setup, while maintaining trajectory continuity and directional stability. This study presents a cost-effective and lightweight localization solution suitable for real road environments, and it can serve as a core component of intelligent traffic safety and tunnel incident response systems.

소비자들을 둘러싸고 있는 여러 위험 요소 중에서도 특히 전염병과 같이 위험의 원천이 이동하는 상황에서, 위험 지각에 영향을 미치는 요소들을 규명하고, 이를 활용한 커뮤니케이션 기법을 검증하는 것은 중요한 의미가 있다. 본 연구는 광고 속 이미지의 방향성이 가지는의미, 특히 동서남북과 같은 방위가 가지는 은유적 의미를 기반으로 위험 원천의 이동 방향에 따라 소비자의 위험 지각 반응이 어떻게 달라질 수 있는지에 주목하였다. 기존의 방향 이미지에 대한 연구에 의하면, 북쪽=위쪽, 남쪽=아래쪽과 관련한 연상을 내포하고 있으며, 위에서 아래로 이동하는 것이 더 자연스럽게 받아들여지는 만큼 북쪽에서 남쪽으로 이동할 때, 그 반대 방향으로 이동할 때보다 노력, 이동거리, 시간 등과 같은 비용이 적게 소비된다고 하였다. 이를 기반으로 본 논문에서는 수월한 방향으로 위험의 원천(전염병)이 이동하는 경우, 위험 정도를 더 크게 지각할 것으로 예상하였다. 또한, 수직적 방향뿐 아니라 수평적 방향에 대하여도 서쪽=왼쪽, 동쪽=오른쪽과 관련한 연상을 내포하며, 왼쪽(과거)에서 오른쪽(미래)으로의 흐름이 더 자연스럽게 받아들여 진다는 기존 연구를 기반으로 그 반대 방향으로 이동할 때보다 위험 정도를 더 크게 지각할 것으로 제안하였다. 이를 검증하기 위해 두 가지 실험을 진행하였다. 실험 1은 수직적 방향이 위험 지각에 미치는 영향력을 확인하고자 하였다. 그 결과, 예측과 동일하게 전염병의 확산 방향이 북->남쪽인 경우, 남->북쪽일 때보다, 위험을 더 크게 지각하는 것으로 나타났다. 실험 2는 수평적 방향이 위험 지각에 미치는 영향력을 검증하여 방향성의 영향력을 일반화하는데 기여하였다. 예측한 바와 같이 전염병의 확산에 있어 더 자연스러운 이동 방향이라고 여겨지는 서->동쪽인 경우, 동->서쪽일 때보다 더 큰 위험 지각을 한 것으로 나타났다. 본 연구는 다양한 문헌에서 연구되어 온 위험 판단에 관한 연구에 있어 체계적이고 객관적인 정보보다 사소한 단서로 인한 주관적 느낌에 의해 영향을 받을 수 있음을 고찰하였다는데 학문적인 의의가 있다. 또한 위험 원천이 이동하는 상황에서, 효과적인 커뮤니케이션에 대한 세부 활용 전략 수립에 유용하게 이용될 수 있을 것으로 기대한다.

According to previous research, humans are influenced by the metaphoric relationship between vertical positions and cardinal direction (i.e., “north is up”). So consumers believe that it will take more resources(e.g., time, effort, money) to move northward than southward. This research suggest that there is relationship between cardinal direction and horizontal position (i.e., “west is left”) as well. Consumers also perceived that it may cost less to move eastward than westward because of left-to-right directionality through their reading and writing experience. Based on these results, this research examined the potential impact of cardinal direction on risk perception. The author conducted two experiments. Study 1 tested the influence of verticaldirectionality on risk estimation. The results revealed that consumers confronting an image with a prevalent direction (i.e., from north to south) perceive a higher risk for diffusion of infectious diseases than consumers with an image of the reverse direction. Study 2 undertook to theoretically replicate the findings of study 1 and examine the influence of horizontal directionality. The results also showed that consumers with fluent direction (i.e., from west to east) judged movement toward contagious disease more risky than consumers with the reverse direction. This research contributes to the risk perception literature by demonstratingthat subjective feelings such as ease of movement impact risk estimation that does not reflectobjective information. The findings of this research offer managerial implications for practitionersto plan communication strategies regarding risk issues.

교통사고 예방을 위해 경찰 및 지자체 등 정부기관에서는 교통시설 및 도로시설의 개선사 업을 추진하여 교통 위해 요소를 제거하고 편안한 도로 환경을 조성하는데 노력하고 있다. 이 를 위해 도로 및 교통시설을 개선 및 조정하며, 교통사고 잦은 지역의 개선사업이 대표적인 사업이다. 교통사고 잦은 지역의 개선사업은 담당자와 관계자의 주관에 따라 사업별, 지역별 편차가 발생하고 있으며, 우선순위 도출 등에 민원 및 주관성이 반영되어 사업의 효율성에 한 계가 발생하고 있다. 이를 위해 교통사고 잦은 곳 개선사업의 효과가 높은 대표사업을 대상으 로 도로여건, 교통여건, 사고여건 등을 종합적으로 고려하여 사업 대상지의 개선방향을 추정하 는 연구를 진행하였다. 연구결과 개선사업 추정 정확도가 88% 수준으로 분석되었으며, 개선방 향을 추정하는데 교통량, 사고율, 사고심각도 순으로 높은 관계가 있는 것으로 분석되었다.

Government agencies, such as police and local governments, strive to prevent traffic hazards and create a comfortable road environment by pormoting transportation and road facilities. To this end, roads and transportation facilities are enhanced and adjusted, and improvement projects in areas with frequent traffic accidents are carried out. Usually, improvement projects in areas with frequent traffic accidents vary by projects and region. Moreover, these projects are carried out under the supervision of a person in charge and related parties. Hence, civil complaints and subjectivity are reflected in deriving priorities for the improvement projects, limiting the efficiency of the project. To this end, a study was conducted to estimate the direction of improvement of the project target site. This study comprehensively considered road, traffic, and accident conditions of representative projects with high effectiveness in handling traffic accidents. The results of the study state that the accuracy of estimating the improvement project was around 88%. In addition, the study found that there was a strong relationship between traffic volume, accident rate, and accident severity in estimating the improvement direction.

Estimation of walking direction is important for providing detailed information about an individual’s gait. This study proposes a method for estimating walking direction using a shoe-mounted acceleration sensor. Heel contact is determined from the negative peak of the acceleration magnitude, and foot inclination is calculated for estimating the horizontal acceleration. The stepping direction of each foot is calculated through principle component analysis along the horizontal acceleration. The walking direction is estimated by averaging consecutive left- and right-step directions. The proposed method was applied to out-door straight ground walking for 658 steps, and yielded a mean difference of 0.48° with a standard deviation of 1.98°.

A new method for head posture and gaze direction estimation is proposed. Firstly, three models of head position are established and postures are judged based on triangle attribute constituted by eyes and mouth. Then pupil is located using Hough transform in eye area. With the method of horizontal and vertical projection and eye prior knowledge, the normal eye outline is fitted. Finally, gaze direction is estimated according to the position of pupil in normal state eye and head posture. The experimental results demonstrate the proposed method can accurately detect head posture and gaze direction. For considering head posture, the method has more accuracy in gaze estimation.

Difference co-array can be constructed by using Khatri-Rao (KR) product, which can increase the degrees of freedom (DOF) significantly. Combined with fourth order cumulants, the KR product can be used to constructed fourth order difference co-array. The fourth order difference co-array of a four level nested array contains a uniform linear array (ULA), however, its second order difference co-array has missing holes, which may result in the ambiguity for DOA estimation. And the method based on KR product and fourth order cumulants has two main drawbacks. First it cannot be employed to Gaussian source signals. Second it needs a large number of snapshots. In this paper, a novel approach is proposed to construct a virtual ULA based on KR product and redundancy spacing of arrays for a four level nested array. Unlike the existing method based on KR product and fourth order cumulants, the new method only uses second order statistics. And compared to the method based on KR product and second order statistics, the new method achieves higher resolution. Numerical results are provided to demonstrate the effectiveness and superior performance of the proposed algorithm.

This paper proposes a novel fast direction of arrival (DOA) estimation method for scenarios when uncorrelated and coherent signals exist simultaneously. First, using uniform transformation, we change complex matrix into real matrix, then, just by exploiting real propagator method (RPM), we can attain the uncorrelated signals DOA fastly. Second, based on new spatial difference technique, we can eliminate the effection of uncorrelated signals and make coherent signals become uncorrelated. Finally, utilizing RPM technique, coherent signals DOA can be estimated swiftly. Simulation results validate the performance improvement of the proposed algorithm.

본 논문에서는 레이더 시스템에서 단일 펄스 방식, 집적 상관 방식, 비 집적 상관 방식의 신호대 잡음비 성능에 대해서 비교 분석하였다. 그리고, 공간상에 두 목표물에 대한 방향을 추정하여 기존의 방법과 비교 분석하였다. 레이더 시스템에서 일반적으로 반사파와 전송파의 왜곡을 방지하고 감소시키기 위해서 펼스파를 이용하여 신호를 전송한다. 본 논문에서는 수신신호를 처리하는 방식으로 포락선 검파기 앞에서 처리하는 집적 상관방식과 과 포락선 검파기 뒤에서 처리하는 비 집적 상관 방식의 성능을 비교 분석하였다. 모의실험을 통하여 목표물 방향을 추정하였고, 두 목표물의 탐지 거리를 추정하여 신호대 잡음비 성능을 비교 분석하였다. 집적 상관방식의 성능이 우수함을 입증하였다.

In this paper, we analysed a performance signal to noise ratio about pulse, integration coherent, and integration non coherent system in radar system. It compared existing with proposal method in order to estimation two target direction of arrival. Generally, radar system radiate pulse wave in order to decreasing distortion of return wave and transmission wave. We analysed the performance integration coherent and integration non coherent. Integration coherent is processing system before doing envelop detection, and integration non coherent is processing system after doing envelop detection. Through simulation, we analysed a performance signal to noise ratio to estimation two target range detection and estimated target direction of arrival. We showed that integration coherent system is the most good performance.

This paper presents a non-contact measurement method of vital signal by the use of multiple-input multiple-output (MIMO) bio-radar system, configured with two antennas that are separated by a certain distance. The direction of arrival (DOA) estimation algorithm for coherent sources was applied to detect vital signals coming from different spatial angles. The proposed MIMO bio-radar system was composed of two identical transceivers sharing single VCO with a PLL. In order to verify the performance of the system, the DOA estimation experiment was completed with respect to the human target at angles varying between $-50^{\circ}$ and $50^{\circ}$ where the bio-radar system was placed at distances (corresponding to 50 cm and 95 cm) in front of a human target. The proposed MIMO bio-radar system can successfully find the direction of a human target.

Herein, we estimate the direction of arrival (DOA) of non-Gaussian signals for nested arrays (NAs) by implementing the fourth-order difference co-array (FODC) and successive methods. In particular, considering the property of the fourth-order cumulant (FOC), we first construct the FODC of the NA, which can obtain O(N⁴) virtual elements using N physical sensors, whereas conventional FOC methods can only obtain O(N²) virtual elements. In addition, the closed-form expression of FODC is presented to verify the enhanced degrees of freedom (DOFs). Subsequently, we exploit the vectorized FOC (VFOC) matrix to match the FODC of the NA. Notably, the VFOC matrix is a single snapshot vector, and the initial DOA estimates can be obtained via the discrete Fourier transform method under the underdetermined correlation matrix condition, which utilizes the complete DOFs of the FODC. Finally, fine estimates are obtained through the spatial smoothing-Capon method with partial spectrum searching. Numerical simulation verifies the effectiveness and superiority of the proposed method.

This paper deal with estimating the direction of arrival (DOA) of GNSS signal using two antennae for spoofing detection. A technique for estimating the azimuth angle of a received signal by applying the interferometer method to the GPS carrier signal is proposed. The experiment assumes two antennas placed on the earth's surface and estimates the azimuth angle when only GPS signal are received without spoofing signal. The proposed method confirmed the availability through GPS satellite placement simulation and experiments using a dual antenna GPS receiver. In this case of using dual antenna, an azimuth angle ambiguity of the received signal occurs with respect to the baseline between two antennas. For this reason, the accurate azimuth angle estimation is limits, but it can be used for deception by cross-validating the ambiguity.

Tracking of the moving object, which is realized by the computer vision, is used for military and industrial fields. It is the application technique with imply complicated processing for understanding the input images. But, in these days, the most moving object tracking algorithms have many difficult problems. A typical problem is the increase of calculation time depending on target number. For this reason, there are many studies to solve real time processing problems and errors for background environmental change. In this paper, we used optical flow which is one of moving object tracking algorithms. It represents vector of the moving object. Optical flow estimation based on the regularization method depends on iteration method but it is very sensitive the noise. We proposed a new method using the Combinatorial Hough Transform (CHT) and Voting Accumulation in order to find optimal constraint lines. Also, we used the logical operation in order to release the operation time. The proposed method can easily and accurately extract the optical flow of moving object area and the moving information. We have simulated the proposed method using the test images. This images are included the noise. Experimental results show that the proposed method get better flow and estimate accurately the moving information.

The optimization techniques are explored in the direction of arrival (DOA) estimation based on single acoustic pressure gradient vector sensor (APGVS). By analyzing the working principle and measurement errors of the APGVS, acoustic intensity approaches (AI) and the minimum variance distortionless response beamforming approach based on single APGVS (VMVDR) are deduced. The radius to wavelength ratio of the APGVS must be not bigger than 0.1 in the actual application, otherwise its DOA estimation performance will degrade significantly. To improve the robustness and estimation performance of the DOA estimation approaches based on single APGVS, two modified processing approaches based on single APGVS are presented. Simulation and lake trial results indicate that the performance of the modified approaches based on single APGVS are better than AI and VMVDR approaches based on single APGVS when the radius to wavelength ratio is not bigger than 0.1, and the two modified DOA estimation methods have excellent estimation performance when the radius to wavelength ratio is bigger than 0.1.

이 논문에서는 등간격 사각형 배열(Uniform Rectangular Array: URA)을 사용하는, 계산상 효율적인 2차원 도래각(Direction of Arrival: DoA) 추정 방법을 제안한다. 제안된 방법은 안테나에 도달한 수신 신호들간의 상관행렬 대신 그들 사이의 위상 관계에 직접적으로 기반하고 있기 때문에 직접 신호-기반 방법이라고 한다. 시뮬레이션 결과에 따르면 직접 신호-기반의 방법이 기존의 어느 방법들보다 현저히 적은 계산량으로도 평균 제곱근 오차(Root-Mean-Squared Error: RMSE)와 최대 절대 오차 측면에서 다중 신호 분류(MUltiple SIgnal Classification: MUSIC) 방법과 비교할 만한 성능을 보여준다.

This paper proposes a computationally efficient 2-D direction-of-arrival (DoA) estimation method with a uniform rectangular array (URA). This method is called the direct signal-based method in the sense that it is based directly on the phase relationships among the signals arriving at each antenna of an antenna array rather than their correlation matrix. According to the simulation results, it has be shown that the direct signal-based method, with much less computations than any existing methods, yields the performance comparable to that of the MUSIC (MUltiple SIgnal Classification) method in terms of the root-mean-squared error (RMSE) and the maximum absolute error.

We propose a method of sensing the rotation and distance of a camera by using a fisheye lens system as a vision sensor. We estimate the rotation angle of a camera with a modified correlation method by clipping similar regions to avoid symmetry problems and suppressing highlight areas. In order to eliminate the rectification process of the distorted points of a fisheye lens image, we introduce an offline process using the normalized focal length, which does not require the image sensor size. We also formulate an equation for calculating the distance of a camera movement by matching the feature points of the test image with those of the reference image.

We examine an asymptotic analysis of differentiable econometric models using the distance and direction (DD) method introduced by Cho and White (2012), in which the conventional analysis for the quasi-maximum likelihood estimation and inference can be treated as a special case. We extend their approach and revisit the conventional quasi-likelihood ratio,Wald, and Lagrange multiplier test statistics through a different perspective. This new perspective is further analyzed in a unified framework, and we exploit this to introduce new classes of test statistics.

In this paper, we describes a method of estimating traveling direction of a autonomous vehicle. For the development of autonomous vehicle, it is important to detect road lane and to reckon traveling direction. The object of a propose algorithm is to perform lane detection in real-time for standalone vision system. And we calculate efficent traveling direction to find steering angie for lateral control system. Therefore autonomous vehicle go forward the center of lane by adjusting the current steering angle using traveling direction.