• Title/Summary/Keyword: 비행체 탐지

Search Result 26, Processing Time 0.028 seconds

Sequence Based Anomaly Detection System for Unmanned Aerial Vehicle (시퀀스 유사도 기반 무인 비행체 이상 탐지 시스템)

  • Seo, Kang Uk;Kim, Huy Kang
    • Journal of the Korea Institute of Information Security & Cryptology
    • /
    • v.32 no.1
    • /
    • pp.39-48
    • /
    • 2022
  • In this paper, we propose an anomaly detection system (ADS) to detect anomalies of the in-vehicle network for unmanned aerial vehicle (UAV). The proposed ADS detects the anomalies by measuring the similarity of status messages sequences periodically sent by the UAV to the ground control system. We defined three types of malicious message injection attacks that can be performed on the in-vehicle network of UAV and simulated those attack techniques in the Pixhawk4 quadcopter. The proposed ADS can detect abnormal sequences with accuracy of higher than 96%.

An Image Processing Algorithm for Detection and Tracking of Aerial Vehicles in Short-Range (무인항공기의 근거리 비행체 탐지 및 추적을 위한 영상처리 알고리듬)

  • Cho, Sung-Wook;Huh, Sung-Sik;Shim, Hyun-Chul;Choi, Hyoung-Sik
    • Journal of the Korean Society for Aeronautical & Space Sciences
    • /
    • v.39 no.12
    • /
    • pp.1115-1123
    • /
    • 2011
  • This paper proposes an image processing algorithms for detection and tracking of aerial vehicles in short-range. Proposed algorithm detects moving objects by using image homography calculated from consecutive video frames and determines whether the detected objects are approaching aerial vehicles by the Probabilistic Multi-Hypothesis Tracking method(PMHT). This algorithm can perform better than simple color-based detection methods since it can detect moving objects under complex background such as the ground seen during low altitude flight and consider the characteristics of vehicle dynamics. Furthermore, it is effective for the flight test due to the reduction of thresholding sensitivity against external factors. The performance of proposed algorithm is verified by applying to the onboard video obtained by flight test.

Real-time Anomaly Detection System Using HITL Simulation-Based UAV Packet Data (HITL 시뮬레이션 기반 무인비행체 패킷 데이터를 활용한 실시간 이상 탐지 시스템)

  • Daekyeong Park;Byeongjin Kim
    • Convergence Security Journal
    • /
    • v.23 no.2
    • /
    • pp.103-113
    • /
    • 2023
  • In recent years, Unmanned Aerial Vehicles (UAV) have been widely used in various industries. However, as the depend ence on UAV increases rapidly, concerns about the security and safety of UAV are growing. Currently, various vulnerabili ties such as stealing the control right of the UAV or the right to communicate with the UAV in the web application are being disclosed. However, there is a lack of research related to the security of UAV. Therefore, in this paper, a study was conducted to determine whether the packet data was normal or abnormal by collecting packet data of an unmanned aerial vehicle in a HITL(Hardware In The Loop) simulation environment similar to the real environment. In addition, this paper proposes a method for reducing computational cost in the modeling process and increasing the ease of data interpretation, a machine learning-based anomaly detection model that detects abnormal data by learning only normal data, and optimized hyperparameter values.

A Study on Attitude Estimation of UAV Using Image Processing (영상 처리를 이용한 UAV의 자세 추정에 관한 연구)

  • Paul, Quiroz;Hyeon, Ju-Ha;Moon, Yong-Ho;Ha, Seok-Wun
    • Journal of Convergence for Information Technology
    • /
    • v.7 no.5
    • /
    • pp.137-148
    • /
    • 2017
  • Recently, researchers are actively addressed to utilize Unmanned Aerial Vehicles(UAV) for military and industry applications. One of these applications is to trace the preceding flight when it is necessary to track the route of the suspicious reconnaissance aircraft in secret, and it is necessary to estimate the attitude of the target flight such as Roll, Yaw, and Pitch angles in each instant. In this paper, we propose a method for estimating in real time the attitude of a target aircraft using the video information that is provide by an external camera of a following aircraft. Various image processing methods such as color space division, template matching, and statistical methods such as linear regression were applied to detect and estimate key points and Euler angles. As a result of comparing the X-plane flight data with the estimated flight data through the simulation experiment, it is shown that the proposed method can be an effective method to estimate the flight attitude information of the previous flight.

The Obstacle Avoidance and Target Searching in the Small Chaotic UAV (소형 카오스 무인비행체에서의 장애물 회피 밀 목표물 탐색)

  • Bae, Young-Chul
    • Proceedings of the KIEE Conference
    • /
    • 2005.07d
    • /
    • pp.2849-2851
    • /
    • 2005
  • 본 논문에서는 소형 카오스 무인 비행체에서의 장애물 회피 기법과 목표물 탐지 기법을 제안하였다. 장애물은 불안정한 VDP(van der Pol) 방정식을 이용하였으며 목표물은 안정한 VDP 방정식을 이용하였다. UAV가 장애물과 목표물에 접근하게 되면 불안정 또는 안정한 VDP 방정식이 UAV를 밀어내거나 끌어들임으로서 장애물을 피해가거나 목표물 탐색할 수 있는 알고리즘을 제시하고 컴퓨터 시뮬레이션으로 그 결과를 검증하였다.

  • PDF

Research on Optimal Deployment of Sonobuoy for Autonomous Aerial Vehicles Using Virtual Environment and DDPG Algorithm (가상환경과 DDPG 알고리즘을 이용한 자율 비행체의 소노부이 최적 배치 연구)

  • Kim, Jong-In;Han, Min-Seok
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
    • /
    • v.15 no.2
    • /
    • pp.152-163
    • /
    • 2022
  • In this paper, we present a method to enable an unmanned aerial vehicle to drop the sonobuoy, an essential element of anti-submarine warfare, in an optimal deployment. To this end, an environment simulating the distribution of sound detection performance was configured through the Unity game engine, and the environment directly configured using Unity ML-Agents and the reinforcement learning algorithm written in Python from the outside communicated with each other and learned. In particular, reinforcement learning is introduced to prevent the accumulation of wrong actions and affect learning, and to secure the maximum detection area for the sonobuoy while the vehicle flies to the target point in the shortest time. The optimal placement of the sonobuoy was achieved by applying the Deep Deterministic Policy Gradient (DDPG) algorithm. As a result of the learning, the agent flew through the sea area and passed only the points to achieve the optimal placement among the 70 target candidates. This means that an autonomous aerial vehicle that deploys a sonobuoy in the shortest time and maximum detection area, which is the requirement for optimal placement, has been implemented.

Hough Transform Based Projecton Method for Target Tracking in Image Suquences (투사 및 허프 변환 방식에 의한 연속 영상상의 비행체 궤적 추적)

  • 최재호;곽훈성
    • The Journal of Korean Institute of Communications and Information Sciences
    • /
    • v.19 no.11
    • /
    • pp.2094-2105
    • /
    • 1994
  • This paper contains a Hough transform based projection method derived from Radon transform for tracking dim unresolved(sub-pixel) moving targets that move along straight line parths across a time sequential image data. In contrast to several recently presented Hough transform methods using a compressed image referred to as the track map our proposed technique utilizing a set of projections taken along arbitrary orientations effectively increases the changes of target detection, and creates a robust track estimation environment by incorporating all the available knowledge obtained from the projections. Moreover, in order to quantitatively assess the estimation capability of the projection-based Hough transform algorithm, the analytical bounds on the Hough space parameter errors introduced by image space noise contamination are derived. The simulation yielded promising results of estimating the track parameters even under low signal to noise rations when our technique was tested against the time sequential sets of real infrared image data referred to as the HiCamps.

  • PDF

A Study on the Improvement of Searching Performance of Autonomous Flight UAVs Based on Flocking Theory (플로킹 이론 기반 자율정찰비행 무인항공기의 탐색성능 향상에 관한 연구)

  • Kim, Dae Woon;Seak, Min Jun;Kim, Byoung Soo
    • Journal of the Korean Society for Aeronautical & Space Sciences
    • /
    • v.48 no.6
    • /
    • pp.419-429
    • /
    • 2020
  • In conducting a mission to explore and track targets using a number of unmanned aerial vehicles(UAVs), performance for that mission may vary significantly depending on the operating conditions of the UAVs such as the number of operations, the altitude, and what future flight paths each aircraft decides based on its current position. However, studies on the number of operations, operating conditions, and flight patterns of unmanned aircraft in these surveillance missions are insufficient. In this study, several types of flight simulations were conducted to detect and determine targets while multiple UAVs were involved in the avoidance of collisions according to various autonomous flight algorithms based by flocking theory, and the results were presented to suggest a more efficient/effective way to control a number of UAVs in target detection missions.

Object Detection and 3D Position Estimation based on Stereo Vision (스테레오 영상 기반의 객체 탐지 및 객체의 3차원 위치 추정)

  • Son, Haengseon;Lee, Seonyoung;Min, Kyoungwon;Seo, Seongjin
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
    • /
    • v.10 no.4
    • /
    • pp.318-324
    • /
    • 2017
  • We introduced a stereo camera on the aircraft to detect flight objects and to estimate the 3D position of them. The Saliency map algorithm based on PCT was proposed to detect a small object between clouds, and then we processed a stereo matching algorithm to find out the disparity between the left and right camera. In order to extract accurate disparity, cost aggregation region was used as a variable region to adapt to detection object. In this paper, we use the detection result as the cost aggregation region. In order to extract more precise disparity, sub-pixel interpolation is used to extract float type-disparity at sub-pixel level. We also proposed a method to estimate the spatial position of an object by using camera parameters. It is expected that it can be applied to image - based object detection and collision avoidance system of autonomous aircraft in the future.