Download or read book Development of an Airborne Vision Based Ground Target Localization and Tracking System Based on Angle of Arrival Estimation Method for a Fixed Wing UAV written by and published by . This book was released on 2023 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Airborne Monocular Vision Based Target Detection and Localization with Angle of Arrival Estimation Method written by and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Vision Based Estimation and Tracking Using Multiple Unmanned Aerial Vehicles written by Mingfeng Zhang and published by . This book was released on 2013 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Cooperative Multi sensor Data Fusion to Geo localize Ground Moving Targets Using an Aerial Sensor and a Human as an Additional Sensor written by Azima Motaghi and published by . This book was released on 2014 with total page 85 pages. Available in PDF, EPUB and Kindle. Book excerpt: The ability to track targets using Unmanned Aerial Vehicles (UAVs) has a wide range of civilian and military applications. For example, for military personnel, it is critical to track and locate a variety of objects, including the movement of enemy vehicles. For civilian applications, we can easily find UAVs performing tasks related to land survey, weather forecasting, search and rescue missions, and monitoring farm crops. This study presents a novel method for determining the locations of moving ground-based targets using UAVs and human operators. In previous research, Sharma et al. [1] developed a vision-based target tracking algorithm. They used a Kalman-filter to estimate the target's position and velocity. An information-filter was used to control the sensor. Targets were geo-localized using the pixel locations of the targets in an image. The measurements of the UAV position, altitude, and camera pose angle along with the information embedded in the image provide the required input to an estimator to geo-locate ground targets. Using the highly sophisticated skills of humans for sensing environments, we are interested in integrating the abilities of human operators as a part of sensor network. The main contribution of this thesis is a cyber-physical system developed for reducing the localization errors of targets observed by either UAVs or humans working cooperatively. In particular, in the process of developing the system, we developed (1) an Extended Kalman Filter (EKF) based algorithm to estimate the positions of multiple targets, (2) a human sensor model using neural networks, and (3) a weighted filter to fuse local target estimations from multiple UAVs. Human sensor inputs were utilized to improve the geo localization accuracy of target position estimates. This technique requires operators to be equipped with an Android device; providing operators an easy access to Google map and Global Positioning System (GPS); such that they can specify a target's position on the map. Each sensor, UAVs or human operators, exchanges data through a Wi-Fi sensor network. A central station is used to collect the information observed by independent sensors for data fusion and combines them to generate more accurate estimates that would not be available from any single UAV or a human operator. The capability of the system was demonstrated using simulation results and Android hardware.

Download or read book Vision Based Control and Target Range Estimation for Small Unmanned Aerial Vehicle written by and published by . This book was released on 2005 with total page 41 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the tracking of a moving ground target by small unmanned air vehicle (UAV) via camera vision, the target position and motion cannot be measured directly. Two different types of filters were assessed for their ability to estimate target motion, namely target velocity, directional heading on flat ground and distance from the UAV to target. The first filter is a nonlinear deterministic filter with stability guarantee. The second filter is based on nonlinear Kalman Filter technique. The application and performance of these two filters are presented, for simulated vision based target tracking.

Download or read book Vision based Target Localization from a Small Fixed wing Unmanned Air Vehicle written by Joshua David Redding and published by . This book was released on 2005 with total page 58 pages. Available in PDF, EPUB and Kindle. Book excerpt: Unmanned air vehicles (UAVs) are attracting increased attention as their envelope of suitable tasks expands to include activities such as perimeter tracking, search and rescue assistance, surveillance and reconnaissance. The simplified goal of many of these tasks is to image an object for tracking or information-gathering purposes. The ability to determine the inertial location of a visible, ground-based object without requiring a priori knowledge of its exact location would therefore prove beneficial.

Download or read book Real time Implementation of an Asynchronous Vision based Target Tracking System in an Unmanned Aerial Vehicle written by and published by . This book was released on 2007 with total page 141 pages. Available in PDF, EPUB and Kindle. Book excerpt: Currently, small unmanned aerial vehicles developed by NPS have been able to locate and track stationary and moving targets on the ground. New methods of continuous target tracking are always being developed to improve speed and accuracy, ultimately aiding the user of the system. This thesis describes one such method, utilizing an open loop filter as well as an external correction source: Perspective View Nascent Technologies (PVNT). While the PVNT correction can theoretically improve the accuracy from 20-30 meters to 1-2 meters, it does have a disadvantage in that the target position updates are delayed anywhere from 1-10 seconds. In order to account for the delay, an asynchronous filter is used to update the target position data given the external position correction from PVNT. Two cases have been tested including the general filter and one that utilizes a road model in the calculations. While an earlier thesis developed the basic simulation for the system, this thesis discusses improvements and corrections to the simulation model as well as the necessary steps for real-time implementation.

Download or read book Performance Analysis for a Vision Based Target Tracking System of a Small Unmanned Aerial Vehicle written by and published by . This book was released on 2005 with total page 69 pages. Available in PDF, EPUB and Kindle. Book excerpt: This thesis analyzes performance of the vision-based target-tracking system developed at the Naval Postgraduate School using the Monte Carlo method. Specifically, sensitivities of the target position estimation algorithm to various sensor errors are computed and analyzed. Furthermore, dependence of this algorithm on the performance of the target-tracking control system is established.

Download or read book Planning Methods for Aerial Exploration and Ground Target Tracking written by Per Skoglar and published by . This book was released on 2009 with total page 186 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Hardware in the Loop Implementation of Adaptive Vision Based Guidance Law for Ground Target Tracking written by Mun Lok Bernard Soh and published by . This book was released on 2008 with total page 91 pages. Available in PDF, EPUB and Kindle. Book excerpt: An adaptive guidance law of a Vision Based Target Tracking (VBTT) system was previously developed and implemented onboard a Small Unmanned Aerial Vehicle (SUAV) in order to track a ground target moving with a constant velocity. This work extends previous results by considering scenarios where the variation of target velocity, in both magnitude and direction, is used to excite the feedback control law for further robustness analysis. This provides essential insight on the sensitivity of the performance criteria indicated by the range holding capability, navigation error and the convergence speed of the guidance law. In addition, this thesis addresses the robustness of the SUAV guidance law to the generalized time delay in feedback due to, for example, data processing or communications lag. This thesis also extends the previously obtained results by introducing a multi-criteria optimization technique. The results obtained are first based on the numerical simulations implemented in SIMULINK and then in high fidelity HIL simulation environment with Piccolo Plus AP in the control loop. Initial steps in developing Vision Based HIL environment incorporating TASE gimbal, Piccolo Plus AP, Pan-Tilt unit and image processing software are presented. The work also includes motivation for the development, an overview of the existing technologies, and initial implementation of low-level driving mechanism (drivers) for the realistic representation of the real-world environment.

Download or read book Development and Implementation of New Control Law for Vision Based Target Tracking System Onboard Small Unmanned Aerial Vehicles written by Boon Chong Tay and published by . This book was released on 2006 with total page 109 pages. Available in PDF, EPUB and Kindle. Book excerpt: A new control law is being developed and implemented for the Vision Based Target Tracking (VBTT) system onboard a small unmanned aerial vehicle (SUAV). The new control law allows for coordinated SUAV guidance and vision-based target tracking of stationary and moving targets in the presence of atmospheric disturbances and measurements noise. The new control law is tested for its performance and stability in both the theoretical 6DOF simulation and the Hardware-in-the-Loop (HIL) simulation. Principal results show that realistic measures of performance of the control law are continuous and exhibit predictable degradation of performance with increase of target speed. The results are encouraging and comparable among theoretical predictions, actual hardware simulation results, and initial flight testing. The control law development, implementation, and trial processes and procedures are also examined and categorically documented in this thesis as future reference on the subject development, as well as for better knowledge retention, continuation and proliferation of the VBTT system.

Download or read book Tracking Ground Targets with Measurements Obtained from a Single Monocular Camera Mounted on an Unmanned Aerial Vehicle written by and published by . This book was released on 2007 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: The core objective of this research is to develop an estimator capable of tracking the states of ground targets with observation measurements obtained from a single monocular camera mounted on a small unmanned aerial vehicle (UAV). Typical sensors on a small UAV include an inertial measurement unit (IMU) with three axes accelerometer and rate gyro sensors and a global positioning system (GPS) receiver which gives position and velocity estimates of the UAV. Camera images are combined with these measurements in state estimate filters to track ground features of opportunity and a target. The images are processed by a keypoint detection and matching algorithm that returns pixel coordinates for the features. Kinematic state equations are derived that reflect the relationships between the available input and output measurements and the states of the UAV, features, and target. These equations are used in the development of coupled state estimators for the dynamic state of the UAV, for estimation of feature positions, and for estimation of target position and velocity. The estimator developed is tested in MATLAB/SIMULINK, where GPS and IMU data are generated from the simulated states of a nonlinear model of a Navion aircraft. Images are also simulated based upon a fabricated environment consisting of features and a moving ground target. Target observability limitations are overcome by constraining the target vehicle to follow ground terrain, defined by local features, and subsequent modification of the target's observation model. An unscented Kalman filter (UKF) provides the simultaneous localization and mapping solution for the estimation of aircraft states and feature locations. Another filter, a loosely coupled Kalman filter for the target states, receives 3D measurements of target position with estimated covariance obtained by an unscented transformation (UT). The UT uses the mean and covariance from the camera measurements and from the UKF estimated aircraft states and feature locations to determine the estimated target mean and covariance. Simulation results confirm that the new loosely coupled filters are capable of estimating target states. Experimental data, collected from a research UAV, explores the effectiveness of the terrain estimation techniques required for target tracking.

Download or read book Nonlinear Estimation for Vision based Air to air Tracking written by Seung-Min Oh and published by . This book was released on 2007 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Unmanned aerial vehicles (UAV's) have been the focus of significant research interest in both military and commercial areas since they have a variety of practical applications including reconnaissance, surveillance, target acquisition, search and rescue, patrolling, real-time monitoring, and mapping, to name a few. To increase the autonomy and the capability of these UAV's and thus to reduce the workload of human operators, typical autonomous UAV's are usually equipped with both a navigation system and a tracking system. The navigation system provides high-rate ownship states (typically ownship inertial position, inertial velocity, and attitude) that are directly used in the autopilot system, and the tracking system provides low-rate target tracking states (typically target relative position and velocity with respect to the ownship). Target states in the global frame can be obtained by adding the ownship states and the target tracking states. The data estimated from this combination of the navigation system and the tracking system provide key information for the design of most UAV guidance laws, control command generation, trajectory generation, and path planning.

Download or read book Advances in Unmanned Aerial Vehicles written by Kimon P. Valavanis and published by Springer Science & Business Media. This book was released on 2008-02-26 with total page 552 pages. Available in PDF, EPUB and Kindle. Book excerpt: The past decade has seen tremendous interest in the production and refinement of unmanned aerial vehicles, both fixed-wing, such as airplanes and rotary-wing, such as helicopters and vertical takeoff and landing vehicles. This book provides a diversified survey of research and development on small and miniature unmanned aerial vehicles of both fixed and rotary wing designs. From historical background to proposed new applications, this is the most comprehensive reference yet.

Download or read book Counter Unmanned Aircraft System CUAS Capability for Battalion and Below Operations written by National Academies of Sciences, Engineering, and Medicine and published by National Academies Press. This book was released on 2018-03-29 with total page 49 pages. Available in PDF, EPUB and Kindle. Book excerpt: The development of inexpensive small unmanned aircraft system (sUAS) technologies and the growing desire of hobbyists to have more and more capability have created a sustained sUAS industry, however these capabilities are directly enabling the ability of adversaries to threaten U.S. interests. In response to these threats, the U.S. Army and other Department of Defense (DoD) organizations have invested significantly in counter-sUAS technologies, often focusing on detecting radio frequency transmissions by sUASs and/or their operators, and jamming the radio frequency command and control links and Global Positioning System signals of individual sUASs. However, today's consumer and customized sUASs can increasingly operate without radio frequency command and control links by using automated target recognition and tracking, obstacle avoidance, and other software-enabled capabilities. The U.S. Army tasked the National Academies of Sciences, Engineering, and Medicine to conduct a study to address the above concerns. In particular, the committee was asked to assess the sUAS threat, particularly when massed and collaborating; assess current capabilities of battalion-and- below infantry units to counter sUASs; identify counter-sUAS technologies appropriate for near- term, mid-term, and far-term science and technology investment; consider human factors and logistics; and determine if the Department of Homeland Security could benefit from DoD efforts. This abbreviated report provides background information on the full report and the committee that prepared it.

Download or read book Video Stabilization and Target Localization Using Feature Tracking with Small UAV Video written by David Linn Johansen and published by . This book was released on 2006 with total page 98 pages. Available in PDF, EPUB and Kindle. Book excerpt: Unmanned Aerial Vehicles (UAVs) equipped with lightweight, inexpensive cameras have grown in popularity by enabling new uses of UAV technology. However, the video retrieved from small UAVs is often unwatchable due to high frequency jitter. Beginning with an investigation of previous stabilization work, this thesis discusses the challenges of stabilizing UAV based video. It then presents a software based computer vision framework and discusses its use to develop a real-time stabilization solution. A novel approach of estimating intended video motion is then presented. Next, the thesis proceeds to extend previous target localization work by allowing the operator to easily identify targets rather than relying solely on color segmentation to improve reliability and applicability in real world scenarios. The resulting approach creates a low cost and easy to use solution for aerial video display and target localization.

Download or read book Dynamic Modeling and Vision Based Mobile Target Tracking in UAVs Using Wide FOV Cameras written by Mohsen Majnoon and published by . This book was released on 2016 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Control of unmanned aerial vehicles is a very active topic in research with lots of applications ranging from civilian to military. To control a UAV, its attitude is often controlled using gyroscopes, but to control its position, inertial sensors together with GPS are often used. However, obtaining accurate current position is difficult using inertial sensors because of the integration drift. GPS on the other hand is not functional in indoor applications since it cannot connect to GPS satellites. Since vision has been proved to be an inexpensive and consistent source of relative position information, vision-based control is getting more popular in UAVs recently, but then again, using vision in outdoor applications is challenging as the target can move fast and out of the vision sensor field of view. So, in order to keep the target inside the field of view, two algorithms are being developed and tested via simulation in this research. Using pan/tilt/zoom cameras or multi camera systems, the target is guaranteed to stay in vision system field of view and hence, the vision based pose estimation can provide the control system with proper relative position. Two case studies - vision-based mobile-target tracking of a quadrotor using a multi-camera vision sensor and vision-based mobile-target tracking of a tilting rotor aircraft equipped with a zooming camera - are presented in this research to show the applicability of these methods in UAV control.