Earticle

오늘날 드론의 대중화와 드론 관련 산업의 확장 등으로 인하여 드론 보급이 민 군에 걸쳐 증가하였고, 이와 더불어 보안, 안전사고, 치안‧안보 위협 등의 우려도 함께 커지고 있다. 드론은 크기가 작고 반사도가 낮은 재질로 되어 있어 일반적인 센서로는 탐지가 어려운 것으로 알려져 왔다. 이에, 드론으로 인해 발생하는 사건 및 사고를 예방하기 위해서는 드론의 탐지와 위험 요소에 대응할 수있는 기술에 대한 연구가 선행되어야 한다. 본 논문에서는 드론 탐지 기법을 분류하였다. 또한 CW 레이다를 기반으로 한 드론 탐지실험을 통해, 마이크로 도플러의 패턴을 분석하여 드론 탐지의 가능성을 제시한다.

Recently, acccording to price decline and miniaturization of drone, it is increased dramatically that drone usage in various category including military and private sectors. In accordance with popular usage, There is a increasing risk of safety accident, national security and public privacy problem. Hence there is a high demand for study and analysis applicable to the related technology and anti-drone method including drone detection and jamming. In general, it is extremely difficult to detect and recognize drones using conventional sensors. In this paper, we classify drone detection technology and Drone detection experiments are performed using CW RADAR to obtain and analyze micro-doppler pattern. This preliminary study aims to provide fundamental theory on radar drone detection and experimental test results such that in-depth anti-drone technology can be established in future.

Objective: To assess the effect of vitamin D administration on the skin blood flow response to occlusion and heat. Design: Cross-sectional study. Methods: Twenty age matched subjects; 10 who had diabetes and 10 who were controls were administered 4,000 IU of vitamin D3 for 3 weeks at breakfast. The function of the endothelial cells was evaluated in 2 ways; first, the response to 4 minutes of vascular occlusion of the skin was measured with a laser Doppler flow meter. Second, the skin blood flow response to local heat at 42 degrees C for 6 minutes was examined. Results: The results of the experiments showed that the blood flow response to heat was reduced after 3 weeks administration of vitamin D in the subjects with diabetes and in the control subjects (p<0.05). The response to occlusion was not significantly different within each group before and after vitamin D administration, but the group with diabetes had a significantly lower blood flow response to occlusion than did the controls (p<0.05). Conclusions: Acute doses of vitamin D may impair nitric oxide production and reduce blood flow to tissue during stressors in people with diabetes.

본 논문에서는 서포트 벡터 머신(Support Vector Machine: SVM) 기법을 사용하여 드론과 조류의 움직임을 고려하여 생성된 마이크로 도플러 신호를 분석하여 드론과 조류를 구별하는 시뮬레이션 연구를 제시하였다. 두 개체의 스펙트로그램에서 얻은 시간-주파수 특징은 분류를 위해 평균 스펙트럼 프로파일로 변환된다. SVM 분류기는 신호의 스펙 트로그램을 활용하여 학습되며, 드론과 조류의 동작 매개변수(드론 속도, 드론 블레이드 회전, 조류 날갯짓)의 변동성을 종합적으로 고려하여 분석되었다. 제안된 방법은 드론 블레이드 회전 속도 2,000rpm(±25% 잡음)과 본체 속도 8m/s(±50% 잡음)를 기반으로 한 학습 신호를 사용하여 블레이드 회전 속도가 1,600rpm 정도로 낮은 경우에도 거의 100%의 분류 정확도를 보였다. 블레이드 회전으로 인한 도플러 주파수가 본체 이동에 의한 도플러 주파수보다 상당히 높기 때문에 본체 속도가 분류 성능에 미치는 영향은 무시할 수 있다. 본 연구 결과는 소형 드론을 구별하는 데 있어 SVM 기반 분류 기술의 효과를 제시하였으며, 이 방법의 계산 효율성 측면에서 실시간 감시 시나리오에 매우 적합할 것으로 판단된다.

In this paper, a simulation study for distinguishing between drones and birds by analyzing simulated radar micro-Doppler signatures using a Support Vector Machine (SVM) classifier is presented. Time-frequency features obtained from spectrograms are condensed into average spectral profiles for classification purposes. The SVM classifier is trained using these spectrogram-based features, incorporating variability in drone and bird motion parameters to improve its generalization capability. Results show that with training signals based on a drone rotor speed of 2,000rpm(±25% noise) and body speed of 8m/s(±50% noise), the classifier achieved nearly 100% accuracy for test cases with rotor speeds as low as 1,600rpm. Since the Doppler frequency generated by wing rotation is significantly higher than that produced by body translation, the effect of body velocity on classification performance is negligible. The results confirm the effectiveness of the SVM-based technique in small drone discrimination, and its computational efficiency makes it well-suited for real-time surveillance scenarios.

When the micro-Doppler (MD) image of a ballistic missile is derived, the translational motion compensation (TMC) method is usually applied to the inverse synthetic aperture radar (ISAR) image, but yields poor results because of the micro-motion of the ballistic missile. This paper proposes an efficient TMC method to obtain a focused MD image of a ballistic missile engaged in complicated micro-motion. During range alignment, range profiles (RPs) are coarsely aligned by using the 1D entropy cost function of RPs as a mark, then the coarsely-aligned RPs are fine-aligned by using the minimum 2D entropy of the MD image. During phase adjustment, the gradient of the phase error is appropriately weighted and added to the previous phase error to further fine-tune the aligned RPs. In simulations using the point scatterer model and the measured data from the real missile model, the proposed method provided better image focus than the existing method.

Micro-Doppler (MD) shift caused by the micro-motion of a ballistic missile (BM) can be very useful to identify it. In this paper, the MD signatures of three scale-model BMs are investigated using a portable measurement system. The measurement system consists of an X-band 2-by-2 phase comparison mono-pulse radar, and a mechanical device that can impart controlled spinning and coning motions simultaneously to a model to yield the MD signature that replicates the characteristic of each target and the corresponding micro-motion. The coning motion determined the overall period of MD, and the spinning motion increased its amplitude. MD was also dependent on aspect angle. The designed system is portable, and can implement many micro-motions; it will contribute to analysis of MD in various situations.

In this study, the feasibility of spectral domain optical Doppler tomography for measuring blood flow characteristics in a micro-tube was demonstrated through several experiments. The use of an SD-ODT system in blood flow measurement can provide high resolution images (5 microns resolution). We prepared three capillary tubes to reveal the effect of different concentrations of hematocrit ratio (HR). One tube serves as the control. The two other tubes contained different concentrations of HR (5%, 25%). Three different capillary tube inlet flow velocities were tested in the present study. The Reynolds number (Re) which is based on the capillary tube inner diameter ranges from Re=6 to 48. We calculated a Doppler shift of the power spectrum of the temporal interference fringes with Kasai autocorrelation function to achieve the velocity profile of the flow. As a result, SD-ODT systems could not detect the cell depletion layer in the present study due to the limitation of spatial resolution. Nevertheless, these systems were proven to be capable of observing the RBCs of blood.

도착시간(Time of arrival : TOA)을 이용한 삼변측량법은 레이다 시스템에서 단일목표물의 위치를 추정할 때 일반적으로 사용되는 기법으로 다중 목표물의 경우에는 각 목표물에 대응되는 측정치를 구별할 수가 없으므로 활용이 어려운 단점이 있다. 본 연구에서는 이러한 측정치와 목표물 간 관계의 모호성을 없애고자 최근 레이다 분야에서 활발히 연구되고 있는 마이크로 도플러를 통해 각 목표물의 마이크로 모션을 측정하여 각 목표물의 측정치를 구별하는데 활용하였고, 구별된 측정치로 각 목표물에 대해 삼변측량법을 적용할 수 있게 하였다. 목표물은 모탄에서 분리되는 자탄을 고려하였으며 시뮬레이션 결과를 통해 제안한 알고리즘을 검증하였다.

Trilateration technique using time of arrival(TOA) is generally used for single target position estimation in radar system. However, trilateration technique has limitation in case of multiple targets, since it is difficult to distinguish the measurements corresponding to the respective targets. In this study, to eliminate ambiguity of relation between measurements and targets, micromotion of each target is measured by micro Doppler which is actively studied in radar industry nowadays and these information are used to distinguish measurements used at trilateration technique. Resultingly, the trilateration technique is applied successfully for each target. The targets are considered as multiple submissiles separated from the missile. Simulation results shows the performance of the proposed algorithm.

There are increasing demands to provide early warning against intruding drones and cope with potential threats. Commercial anti-drone systems are mostly based on simple target detection by radar reflections. In real scenario, however, it becomes essential to obtain drone radar signatures so that hostile targets are recognized in advance. We present experimental test results that micro-Doppler radar signature delivers partial information on multi-rotor platforms and exhibits limited performance in drone recognition and classification. Afterward, we attempt to generate high resolution profile of flying drone targets. To this purpose, wide bands radar signals are employed to carry out inverse synthetic aperture radar(ISAR) imaging against moving drones. Following theoretical analysis, experimental field tests are carried out to acquire real target signals. Our preliminary tests demonstrate that high resolution ISAR imaging provides effective measures to detect and classify multiple drone targets in air.