We discuss the evolution and state-of-the-art of the use of Unmanned Aerial Systems (UAS) in the field of Photogrammetry and Remote Sensing (PaRS). UAS, Remotely-Piloted Aerial Systems, Unmanned Aerial Vehicles or simply, drones are a hot topic comprising a diverse array of aspects including technology, privacy rights, safety and regulations, and even war and peace. Modern photogrammetry and remote sensing identified the potential of UAS-sourced imagery more than thirty years ago. In the last five years, these two sister disciplines have developed technology and methods that challenge the current aeronautical regulatory framework and their own traditional acquisition and processing methods. Navety and ingenuity have combined off-the-shelf, low-cost equipment with sophisticated computer vision, robotics and geomatic engineering. The results are cm-level resolution and accuracy products that can be generated even with cameras costing a few-hundred euros. In this review article, following a brief historic background and regulatory status analysis, we review the recent unmanned aircraft, sensing, navigation, orientation and general data processing developments for UAS photogrammetry and remote sensing with emphasis on the nano-micro-mini UAS segment.

https://cyberleninka.org/article/n/529930.pdf

Unmanned aerial systems for photogrammetry and remote sensing: A review

Remotely Piloted Aircraft (RPA) is presently in continuous development at a rapid pace. Unmanned Aerial Vehicles (UAVs) or more extensively Unmanned Aerial Systems (UAS) are platforms considered under the RPAs paradigm. Simultaneously, the development of sensors and instruments to be installed onboard such platforms is growing exponentially. These two factors together have led to the increasing use of these platforms and sensors for remote sensing applications with new potential. Thus, the overall goal of this paper is to provide a panoramic overview about the current status of remote sensing applications based on unmanned aerial platforms equipped with a set of specific sensors and instruments. First, some examples of typical platforms used in remote sensing are provided. Second, a description of sensors and technologies is explored which are onboard instruments specifically intended to capture data for remote sensing applications. Third, multi-UAVs in collaboration, coordination, and cooperation in remote sensing are considered. Finally, a collection of applications in several areas are proposed, where the combination of unmanned platforms and sensors, together with methods, algorithms, and procedures provide the overview in very different remote sensing applications. This paper presents an overview of different areas, each independent from the others, so that the reader does not need to read the full paper when a specific application is of interest

Overview and Current Status of Remote Sensing Applications Based on Unmanned Aerial Vehicles (UAVs)

This newly revised and greatly expanded edition of the popular Artech House book Principles of GNSS, Inertial, and Multisensor Integrated Navigation Systems offers you a current and comprehensive understanding of satellite navigation, inertial navigation, terrestrial radio navigation, dead reckoning, and environmental feature matching . It provides both an introduction to navigation systems and an in-depth treatment of INS/GNSS and multisensor integration. The second edition offers a wealth of added and updated material, including a brand new chapter on the principles of radio positioning and a chapter devoted to important applications in the field. Other updates include expanded treatments of map matching, image-based navigation, attitude determination, acoustic positioning, pedestrian navigation, advanced GNSS techniques, and several terrestrial and short-range radio positioning technologies. The book shows you how satellite, inertial, and other navigation technologies work, and focuses on processing chains and error sources. In addition, you get a clear introduction to coordinate frames, multi-frame kinematics, Earth models, gravity, Kalman filtering, and nonlinear filtering. Providing solutions to common integration problems, the book describes and compares different integration architectures, and explains how to model different error sources. You get a broad and penetrating overview of current technology and are brought up to speed with the latest developments in the field, including context-dependent and cooperative positioning. DVD Included: Features eleven appendices, interactive worked examples, basic GNSS and INS MATLAB simulation software, and problems and exercises to help you master the material.

Principles of GNSS, Inertial, and Multisensor Integrated Navigation Systems, Second Edition

Assessment of air quality has been traditionally conducted by ground based monitoring, and more recently by manned aircrafts and satellites. However, performing fast, comprehensive data collection near pollution sources is not always feasible due to the complexity of sites, moving sources or physical barriers. Small Unmanned Aerial Vehicles (UAVs) equipped with different sensors have been introduced for in-situ air quality monitoring, as they can offer new approaches and research opportunities in air pollution and emission monitoring, as well as for studying atmospheric trends, such as climate change, while ensuring urban and industrial air safety. The aims of this review were to: (1) compile information on the use of UAVs for air quality studies; and (2) assess their benefits and range of applications. An extensive literature review was conducted using three bibliographic databases (Scopus, Web of Knowledge, Google Scholar) and a total of 60 papers was found. This relatively small number of papers implies that the field is still in its early stages of development. We concluded that, while the potential of UAVs for air quality research has been established, several challenges still need to be addressed, including: the flight endurance, payload capacity, sensor dimensions/accuracy, and sensitivity. However, the challenges are not simply technological, in fact, policy and regulations, which differ between countries, represent the greatest challenge to facilitating the wider use of UAVs in atmospheric research.

An Overview of Small Unmanned Aerial Vehicles for Air Quality Measurements: Present Applications and Future Prospectives

Additive manufacturing in unmanned aerial vehicles (UAVs): Challenges and potential

The meteorological mini unmanned aerial vehicle (M2AV) was used for measuring the meteorological wind. The wind is the vector difference between the aircraft speed relative to the earth (inertial velocity) and relative to the airflow (true airspeed). The latter was computed from five-hole-probe pressure measurements in combination with calibration–coefficient polynomials obtained during wind tunnel calibration. The aircraft inertial velocity, position, and attitude were calculated using a Kalman filter that combined data from a global positioning system (GPS) and an inertial navigation system (INS). The temporal (and spatial) resolution of the M2AV wind measurement is remarkably fine. An inertial subrange of locally isotropic turbulence can be measured up to 40 Hz (or 0.55 m at 22 m s−1 airspeed). The first M2AV wind estimation showed some systematic deviations compared to the expected values (like a constant mean wind in every flight direction). Therefore, an in-flight wind calibration technique...

Measuring the Wind Vector Using the Autonomous Mini Aerial Vehicle M2AV

The limitations of manned airborne meteorological measurements led to a new unmanned system, the Meteorological Mini-UAV (M 2 AV), recently developed by the Institute of Aerospace Systems, Technical University of Braunschweig. The task was to develop, test and verify a meteorological sensor package as payload for an already available carrier aircraft, the UAV ‘Carolo T200’. Thereby the limitations in size and mass had to be respected. The M 2 AV is capable of performing turbulence and wind vector measurements within the atmospheric boundary layer and permits very short measurement cycles as an economic supplement during meteorological campaigns. The article gives details on the technical items. Results from meteorological data sets measured by the M 2 AV are used for data quality assessment. In October 2005 the M 2 AV participated in the meteorological field experiment ‘LAUNCH 2005’ in Linden berg near Berlin. The M 2 AV data were compared with lidar and sodar/RASS measurements. Furthermore, an in situ comparison of temperature, humidity and wind vector data with the helicopter-borne turbulence probe Helipod was analysed and gave information about the M 2 AV data quality. Zusammenfassung Dieser Artikel befasst sich mit dem unbemannten meteorologischen Kleinflugzeug (M 2 AV), das vom Institut fur Luft- und Raumfahrtsysteme der Technischen Universitat Braunschweig entwickelt wurde. Die Grenzen bemannter Flugmessungen fuhrten zur Entwicklung eines neuartigen, unbemannten meteorologischen Flugmesssystems, dem M 2 AV. Die Aufgabe bestand darin, ein Sensorpaket fur ein bestehendes Tragerflugzeug, das unbemannte Kleinstflugzeug ‘Carolo T200’ zu en twickeln, zu testen und zu verifizieren. Dabei mussten insbesondere die Rahmenbedingungen bezuglich der Grose und der Masse beachtet werden. Trotzdem sollte das M 2 AV in der Lage sein, innerhalb der atmospharischen Grenzschicht den Windvektor zu messen und Turbulenz aufzulosen. Das entwickelte System gestattet dicht aufeinanderfolgende Messungen als okonomische Unterstutzung wahrend meteorologischer Kampagnen. Es wird die Technik des M 2 AV im Detail beschrieben und die Ergebnisse aus der wissenschaftlichen Untersuchung von meteorologischen Datensatzen verwendet, um die Datenqualitat und die raumliche Auflosung einzuschatzen.

Peter Vörsmann

Papers

Measuring the Wind Vector Using the Autonomous Mini Aerial Vehicle M2AV

First application of the meteorological Mini-UAV 'M2AV'

Active debris removal of multiple priority targets

2012 Special Issue: Fault-tolerant nonlinear adaptive flight control using sliding mode online learning

Development of in-situ Space Debris Detector