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We investigate optimal estimation for both the position and the velocity of the ground moving target (GMT) by employing sensors composed of unmanned aerial vehicles (UAVs). The problem is the cooperative sensing by the UAVs, in terms of their location geometries to achieve optimal estimation of the GMT. Based on the Cramer-Rao bound, we are able to derive the minimum achievable error variance in estimation of the position and the velocity of the GMT, and obtain the optimal geometries of the UAV sensors via minimization of the minimum achievable error variance for unbiased estimation commanded by the Cramer-Rao bound. Our solution is complete that encompasses various situations for the GMT, and the number of UAV sensors.
The book describes a system for visual surveillance using intelligent cameras. The camera uses robust techniques for detecting and tracking moving objects. The real time capture of the objects is then stored in the database. The tracking data stored in the database is analysed to study the camera view, detect and track objects, and study object behavior. These set of models provide a robust framework for coordinating the tracking of objects between overlapping and non-overlapping cameras, and recording the activity of objects detected by the system.
An authoritative reference on cooperative decision and control of unmanned aerial vehicles.
This book discusses the potential of the Internet of Unmanned Things (IoUT), which is considered a promising paradigm resulting in numerous applications including shipment of goods, home package delivery, crop monitoring, agricultural surveillance, and rescue operations. The authors discuss how IoUT nodes collaborate with each other in ad hoc manner through a Line-of-Sight (LoS) link to exchange data packets. Also discussed is how Unmanned Arial Vehicles (UAVs) can communicate with fixed ground stations, with an air traffic controller, or through a Non-Line-of-Sight (NLoS) link with a satellite-aided controller, generally based on preloaded missions. The authors go on to cover how to tackle issues that arise with dissimilar communication technologies. They cover how various problems can appear in inter-UAV and UAV-to-X communications including energy management, lack of security and the unreliability of wireless communication links, and handover from LoS to NLoS, and vice versa. In this book, the editors invited front-line researchers and authors to submit research exploring emerging technologies for IoUT and mission-based networking and how to overcome challenges.
The fast user growth in wireless communications has created significant demands for new wireless services in both the licensed and unlicensed frequency spectra. Since many spectra are not fully utilized most of the time, cognitive radio, as a form of spectrum reuse, can be an effective means to significantly boost communications resources. Since its introduction in late last century, cognitive radio has attracted wide attention from academics to industry. Despite the efforts from the research community, there are still many issues of applying it in practice. This books is an attempt to cover some of the open issues across the area and introduce some insight to many of the problems. It contains thirteen chapters written by experts across the globe covering topics including spectrum sensing fundamental, cooperative sensing, spectrum management, and interaction among users.
Active technological development has fuelled rapid growth in the number of Unmanned Aerial Vehicle (UAV) platforms being deployed around the globe. Novel UAV platforms, UAV-based sensors, robotic sensing and imaging techniques, the development of processing workflows, as well as the capacity of ultra-high temporal and spatial resolution data, provide both opportunities and challenges that will allow engineers and scientists to address novel and important scientific questions in UAV and sensor design, remote sensing and environmental monitoring.This work features papers on UAV sensor design, improvements in UAV sensor technology, obstacle detection, methods for measuring optical flow, target tracking, gimbal influence on the stability of UAV images, augmented reality tools, segmentation in digital surface models for 3D reconstruction, detection, location and grasping objects, multi-target localization, vision-based tracking in cooperative multi-UAV systems, noise suppression techniques , rectification for oblique images, two-UAV communication system, fuzzy-based hybrid control algorithms, pedestrian detection and tracking as well as a range of atmospheric, geological, , agricultural, ecological, reef, wildlife, building and construction, coastal area coverage, search and rescue (SAR), water plume temperature measurements, aeromagnetic and archaeological surveys applications.
This book includes original, peer-reviewed research papers from the 2021 5th Chinese Conference on Swarm Intelligence and Cooperative Control (CCSICC2021), held in Shenzhen, China on January 19-22, 2022. The topics covered include but are not limited to: reviews and discussions of swarm intelligence, basic theories on swarm intelligence, swarm communication and networking, swarm perception, awareness and location, swarm decision and planning, cooperative control, cooperative guidance, swarm simulation and assessment. The papers showcased here share the latest findings on theories, algorithms and applications in swarm intelligence and cooperative control, making the book a valuable asset for researchers, engineers, and university students alike.
This book contains accepted papers presented at SOCO 2022 conference held in the beautiful and historic city of Salamanca (Spain), in September 2022. Soft computing represents a collection or set of computational techniques in machine learning, computer science, and some engineering disciplines, which investigate, simulate, and analyze very complex issues and phenomena. After a thorough peer-review process, the 17th SOCO 2022 International Program Committee selected 64 papers which are published in these conference proceedings and represent an acceptance rate of 60%. In this relevant edition, a particular emphasis was put on the organization of special sessions. Seven special sessions were organized related to relevant topics such as machine learning and computer vision in Industry 4.0; time series forecasting in industrial and environmental applications; optimization, modeling, and control by soft computing techniques; soft computing applied to renewable energy systems; preprocessing big data in machine learning; tackling real-world problems with artificial intelligence. The selection of papers was extremely rigorous to maintain the high quality of the conference. We want to thank the members of the program committees for their hard work during the reviewing process. This is a crucial process for creating a high-standard conference; the SOCO conference would not exist without their help.