Trajectory optimization for high-altitude long endurance UAV maritime radar surveillance

For an unmanned aerial vehicle (UAV) carrying out a maritime radar surveillance mission, there is a tradeoff between maximizing information obtained from the search area and minimizing fuel consumption. This paper presents an approach for the optimization of a UAV's trajectory for maritime radar wide area persistent surveillance to simultaneously minimize fuel consumption, maximize mean probability of detection, and minimize mean revisit time. Quintic polynomials are used to generate UAV trajectories due to their ability to provide complete and complex solutions while requiring few inputs. Furthermore, the UAV dynamics and surveillance mission requirements are used to ensure a trajectory is realistic and mission compatible. A wide area search radar model is used within this paper in conjunction with a discretized grid in order to determine the search area's mean probability of detection and mean revisit time. The trajectory generation method is then used in conjunction with a multi-objective particle swarm optimization (MOPSO) algorithm to obtain a global optimum in terms of path, airspeed (and thus time), and altitude. The performance of the approach is then tested over two common maritime surveillance scenarios and compared to an industry recommended baseline

UAVs for the Environmental Sciences

This book gives an overview of the usage of UAVs in environmental sciences covering technical basics, data acquisition with different sensors, data processing schemes and illustrating various examples of application

Sensor-Oriented Path Planning for Multiregion Surveillance with a Single Lightweight UAV SAR

In the surveillance of interested regions by unmanned aerial vehicle (UAV), system performance relies greatly on the motion control strategy of the UAV and the operation characteristics of the onboard sensors. This paper investigates the 2D path planning problem for the lightweight UAV synthetic aperture radar (SAR) system in an environment of multiple regions of interest (ROIs), the sizes of which are comparable to the radar swath width. Taking into account the special requirements of the SAR system on the motion of the platform, we model path planning for UAV SAR as a constrained multiobjective optimization problem (MOP). Based on the fact that the UAV route can be designed in the map image, an image-based path planner is proposed in this paper. First, the neighboring ROIs are merged by the morphological operation. Then, the parts of routes for data collection of the ROIs can be located according to the geometric features of the ROIs and the observation geometry of UAV SAR. Lastly, the route segments for ROIs surveillance are connected by a path planning algorithm named the sampling-based sparse A* search (SSAS) algorithm. Simulation experiments in real scenarios demonstrate that the proposed sensor-oriented path planner can improve the reconnaissance performance of lightweight UAV SAR greatly compared with the conventional zigzag path planner

ATHENA Research Book, Volume 2

ATHENA European University is an association of nine higher education institutions with the mission of promoting excellence in research and innovation by enabling international cooperation. The acronym ATHENA stands for Association of Advanced Technologies in Higher Education. Partner institutions are from France, Germany, Greece, Italy, Lithuania, Portugal and Slovenia: University of Orléans, University of Siegen, Hellenic Mediterranean University, Niccolò Cusano University, Vilnius Gediminas Technical University, Polytechnic Institute of Porto and University of Maribor. In 2022, two institutions joined the alliance: the Maria Curie-Skłodowska University from Poland and the University of Vigo from Spain. Also in 2022, an institution from Austria joined the alliance as an associate member: Carinthia University of Applied Sciences. This research book presents a selection of the research activities of ATHENA University's partners. It contains an overview of the research activities of individual members, a selection of the most important bibliographic works of members, peer-reviewed student theses, a descriptive list of ATHENA lectures and reports from individual working sections of the ATHENA project. The ATHENA Research Book provides a platform that encourages collaborative and interdisciplinary research projects by advanced and early career researchers