Rotary-wing Unmanned Aircraft Systems Research Articles

Rapid Assessment of Insect Pest Outbreak Using Drones: A Case Study with Spodoptera exigua (Hübner) (Lepidoptera: Noctuidae) in Soybean Fields.

Rapid assessment of crop damage is essential for successful management of insect pest outbreaks. In this study, we investigated the use of an unmanned aircraft system (UAS) and image analyses to assess an outbreak of the beet armyworm, Spodoptera exigua (Hübner) (Lepidoptera: Noctuidae), that occurred in soybean fields in South Korea. A rotary-wing UAS was deployed to obtain a series of aerial images over 31 soybean blocks. The images were stitched together to generate composite imagery, followed by image analyses to quantify soybean defoliation. An economic analysis was conducted to compare the cost of the aerial survey with that of a conventional ground survey. The results showed that the aerial survey precisely estimated the defoliation compared to the ground survey, with an estimated defoliation of 78.3% and a range of 22.4-99.8% in the 31 blocks. Moreover, the aerial survey followed by image analyses was found to be more economical than the conventional ground survey when the number of target soybean blocks subject to the survey was more than 15 blocks. Our study clearly demonstrated the effectiveness of using an autonomous UAS and image analysis to conduct a low-cost aerial survey of soybean damage caused by S. exigua outbreaks, which can inform decision-making for S. exigua management.

Toward sustainable meteorological profiling in polar regions: Case studies using an inexpensive UAS on measuring lower boundary layers with quality of radiosondes

This study assessed the possibility of producing profiles of atmospheric parameters, including aerosol number concentration, using observations obtained by a conventional low-cost small rotary-wing Unmanned Aircraft Systems (UAS). A radiation shield for the meteorological sensor was developed to reduce the effects from heat exhaust from both the rotors and the body of the UAS and from solar radiation. Field experiments in northern Japan during winter confirmed that the continuous UAS-derived meteorological data obtained in the lower boundary layer were of quality equivalent to that of radiosonde observations in a cold environment (<− 20 °C), that is, better than other meteorological rotary-wing UASs. The continuous profiling of aerosols also demonstrated the capability for monitoring air quality below a very strong inversion layer during winter. Quality-controlled UAS meteorological profiles would be a potential observation data source for skillful numerical weather prediction, particularly in data-sparse regions such as the Arctic and Antarctic, contributing to the sustainable polar observing network.

Estimation of Airspeed, Angle of Attack, and Sideslip for Small Unmanned Aerial Vehicles (UAVs) Using a Micro-Pitot Tube

Fixed and rotary-wing unmanned aircraft systems (UASs), originally developed for military purposes, have widely spread in scientific, civilian, commercial, and recreational applications. Among the most interesting and challenging aspects of small UAS technology are endurance enhancement and autonomous flight; i.e., mission management and control. This paper proposes a practical method for estimation of true and calibrated airspeed, Angle of Attack (AOA), and Angle of Sideslip (AOS) for small unmanned aerial vehicles (UAVs, up to 20 kg mass, 1200 ft altitude above ground level, and airspeed of up to 100 knots) or light aircraft, for which weight, size, cost, and power-consumption requirements do not allow solutions used in large airplanes (typically, arrays of multi-hole Pitot probes). The sensors used in this research were a static and dynamic pressure sensor (“micro-Pitot tube” MPX2010DP differential pressure sensor) and a 10 degrees of freedom (DoF) inertial measurement unit (IMU) for attitude determination. Kalman and complementary filtering were applied for measurement noise removal and data fusion, respectively, achieving global exponential stability of the estimation error. The methodology was tested using experimental data from a prototype of the devised sensor suite, in various indoor-acquisition campaigns and laboratory tests under controlled conditions. AOA and AOS estimates were validated via correlation between the AOA measured by the micro-Pitot and vertical accelerometer measurements, since lift force can be modeled as a linear function of AOA in normal flight. The results confirmed the validity of the proposed approach, which could have interesting applications in energy-harvesting techniques.

Inversion of Magnetic Data Acquired with a Rotary-Wing Unmanned Aircraft System for Gold Exploration

A hexacopter unmanned aircraft system instrumented with a caesium vapour magnetometer recorded total magnetic intensity over a 5.0 km2 prospective gold area in the Abitibi Subprovince of the Canadian Precambrian Shield. The survey also included a N–S repeatability line which showed that the unmanned aircraft system was very stable in flight with average standard deviations from nominal altitude and easting being 1.8 m and 0.7 m, respectively. The total magnetic intensity map revealed the structural framework of the banded iron formations present in the survey area and showed that the gold ore zones are not directly associated with magnetic highs but rather with steeply dipping faults. The total magnetic intensity data was inverted in 3-D using unconstrained and constrained approaches with 12.5 m (northing) × 12.5 m (easting) × 5 m (depth) cells and a maximum of 20 iterations. The processed (after diurnal corrections, heading correction, and tie-line levelling) total magnetic intensity data was input directly in the unconstrained inversion algorithm. Initial model building for the constrained inversion was a much more laborious process involving the inclusion of 15 synthetic structures based on borehole magnetic susceptibility measurements and knowledge of the local geology. The results of both inversion approaches were very similar. They revealed the presence of near-vertical thin sheets, individually resolvable down to approximately 400 m. In this particular case, the straightforward unconstrained inversion yielded a realistic and detailed model of the subsurface in approximately 1 h of runtime. Unmanned aircraft system total magnetic intensity data could therefore be processed and inverted almost immediately after acquisition and have an impact on decisions made in the field while a survey is still in progress.

Probabilistic Risk-Based Operational Safety Bound for Rotary-Wing Unmanned Aircraft Systems Traffic Management

A novel method to determine probabilistic operational safety bound for rotary-wing unmanned aircraft systems (UAS) traffic management is proposed in this paper. The key idea is to combine a deterministic model for rotary-wing UAS flying distance estimation to avoid conflict and a probabilistic uncertainty quantification methodology to evaluate the risk level (defined as the probability of failure) of separation loss between UAS. The proposed methodology results in a dynamic and probabilistic airspace reservation to ensure the safety and efficiency for future UAS operations. The model includes UAS performance, system updating frequency and accuracy, and weather conditions. Also, the parameterized probabilistic model includes various uncertainties from different sources and develops an anisotropic operational safety bound. Monte Carlo simulations are used to illustrate the operational safety bound determination with a specified risk level (i.e., probability of failure). It is known that uncertainty plays an important role in determining the operational safety bound size, and the proposed methodology provides a simple and efficient quantification of uncertainty impact on the safety bound with a prescribed risk level. It is also providing a useful tool to quantify uncertainty reduction with additional information and measurements in future UAS operations.

Accessing the Life in Smoke: A New Application of Unmanned Aircraft Systems (UAS) to Sample Wildland Fire Bioaerosol Emissions and Their Environment

Wildland fire is a major producer of aerosols from combustion of vegetation and soils, but little is known about the abundance and composition of smoke’s biological content. Bioaerosols, or aerosols derived from biological sources, may be a significant component of the aerosol load vectored in wildland fire smoke. If bioaerosols are injected into the upper troposphere via high-intensity wildland fires and transported across continents, there may be consequences for the ecosystems they reach. Such transport would also alter the concept of a wildfire’s perimeter and the disturbance domain of its impact. Recent research has revealed that viable microorganisms are directly aerosolized during biomass combustion, but sampling systems and methodology for quantifying this phenomenon are poorly developed. Using a series of prescribed fires in frequently burned forest ecosystems, we report the results of employing a small rotary-wing unmanned aircraft system (UAS) to concurrently sample aerosolized bacteria and fungi, particulate matter, and micrometeorology in smoke plumes versus background conditions. Airborne impaction-based bioaerosol sampling indicated that microbial composition differed between background air and smoke, with seven unique organisms in smoke vs. three in background air. The air temperature was negatively correlated with the number of fungal colony-forming units detected. Our results demonstrate the utility of a UAS-based sampling platform for active sampling of viable aerosolized microbes in smoke arising from wildland fires. This methodology can be extended to sample viable microbes in a wide variety of emissions sampling pursuits, especially those in hazardous and inaccessible environments.

Environmental and Sensor Integration Influences on Temperature Measurements by Rotary-Wing Unmanned Aircraft Systems.

Obtaining thermodynamic measurements using rotary-wing unmanned aircraft systems (rwUAS) requires several considerations for mitigating biases from the aircraft and its environment. In this study, we focus on how the method of temperature sensor integration can impact the quality of its measurements. To minimize non-environmental heat sources and prevent any contamination coming from the rwUAS body, two configurations with different sensor placements are proposed for comparison. The first configuration consists of a custom quadcopter with temperature and humidity sensors placed below the propellers for aspiration. The second configuration incorporates the same quadcopter design with sensors instead shielded inside of an L-duct and aspirated by a ducted fan. Additionally, an autopilot algorithm was developed for these platforms to face them into the wind during flight for kinematic wind estimations. This study will utilize in situ rwUAS observations validated against tower-mounted reference instruments to examine how measurements are influenced both by the different configurations as well as the ambient environment. Results indicate that both methods of integration are valid but the below-propeller configuration is more susceptible to errors from solar radiation and heat from the body of the rwUAS.

Coordinated Unmanned Aircraft System (UAS) and Ground-Based Weather Measurements to Predict Lagrangian Coherent Structures (LCSs).

Concentrations of airborne chemical and biological agents from a hazardous release are not spread uniformly. Instead, there are regions of higher concentration, in part due to local atmospheric flow conditions which can attract agents. We equipped a ground station and two rotary-wing unmanned aircraft systems (UASs) with ultrasonic anemometers. Flights reported here were conducted 10 to 15 m above ground level (AGL) at the Leach Airfield in the San Luis Valley, Colorado as part of the Lower Atmospheric Process Studies at Elevation—a Remotely-Piloted Aircraft Team Experiment (LAPSE-RATE) campaign in 2018. The ultrasonic anemometers were used to collect simultaneous measurements of wind speed, wind direction, and temperature in a fixed triangle pattern; each sensor was located at one apex of a triangle with ∼100 to 200 m on each side, depending on the experiment. A WRF-LES model was used to determine the wind field across the sampling domain. Data from the ground-based sensors and the two UASs were used to detect attracting regions (also known as Lagrangian Coherent Structures, or LCSs), which have the potential to transport high concentrations of agents. This unique framework for detection of high concentration regions is based on estimates of the horizontal wind gradient tensor. To our knowledge, our work represents the first direct measurement of an LCS indicator in the atmosphere using a team of sensors. Our ultimate goal is to use environmental data from swarms of sensors to drive transport models of hazardous agents that can lead to real-time proper decisions regarding rapid emergency responses. The integration of real-time data from unmanned assets, advanced mathematical techniques for transport analysis, and predictive models can help assist in emergency response decisions in the future.

On the Use of Unmanned Aircraft for Sampling Mesoscale Phenomena in the Preconvective Boundary Layer

AbstractThe potential value of small unmanned aircraft systems (UAS) for monitoring the preconvective environment and providing useful information in real time to weather forecasters for evaluation at a National Weather Service (NWS) Forecast Office are addressed. The general goal was to demonstrate whether a combination of fixed-wing and rotary-wing UAS can provide detailed, accurate, and useful measurements of the boundary layer important for determining the potential for convection initiation (CI). Two field operations were held: a validation study in which the UAS data were compared with collocated measurements made by mobile rawinsondes and ground-based remote sensing systems and a real-time experiment held to evaluate the potential value of the UAS observations in an operationally relevant environment. Vertical profile measurements were made by the rotary-wing UAS at two mesonet sites every 30 min up to 763 m (2500 ft) AGL in coordination with fixed-wing UAS transects between the sites. The results showed the ability of the fixed-wing UAS to detect significant spatial gradients in temperature, moisture, and winds. Although neither of two different types of rotary-wing UAS measurements were able to strictly meet the requirements for sensor accuracy, one of the systems came very close to doing so. UAS sensor accuracy, methods for retrieving the winds, and challenges in assessing the representativeness of the observations are highlighted. Interesting mesoscale phenomena relevant to CI forecasting needs are revealed by the UAS. Issues needing to be overcome for UAS to ever become a NOAA operational observing system are discussed.

Considerations for temperature sensor placement on rotary-wing unmanned aircraft systems

Abstract. Integrating sensors with a rotary-wing unmanned aircraft system (rwUAS) can introduce several sources of biases and uncertainties if not properly accounted for. To maximize the potential for rwUAS to provide reliable observations, it is imperative to have an understanding of their strengths and limitations under varying environmental conditions. This study focuses on the quality of measurements relative to sensor locations on board rwUAS. Typically, thermistors require aspiration and proper siting free of heat sources to make representative measurements of the atmosphere. In an effort to characterize ideal locations for sensor placement, a series of experiments were conducted in the homogeneous environment of an indoor chamber with a pedestal-mounted rwUAS. A suite of thermistors along with a wind probe were mounted inside of a solar shield, which was affixed to a linear actuator arm. The actuator arm was configured such that the sensors within the solar shield would travel underneath the platform into and out of the propeller wash. The actuator arm was displaced horizontally underneath the platform while the motors were throttled to 50 %, yielding a time series of temperature and wind speed that could be compared to temperatures being collected in the ambient environment. Results indicate that temperatures may be biased in the order of 0.5–1.0 ∘C and vary appreciably without aspiration, sensors placed close to the tips of the rotors may experience biases due to frictional and compressional heating as a result of turbulent fluctuations, and sensors in proximity to motors may experience biases approaching 1 ∘C. From these trials, it has been determined that sensor placement underneath a propeller on an rwUAS a distance of one quarter the length of the propeller from the tip is most likely to be minimally impacted from influences of turbulence and motor, compressional, and frictional heating while still maintaining adequate airflow. When opting to use rotor wash as a means for sensor aspiration, the user must be cognizant of these potential sources of platform-induced heating when determining sensor location.

Aeromagnetic Surveying with a Rotary-Wing Unmanned Aircraft System: A Case Study from a Zinc Deposit in Nash Creek, New Brunswick, Canada

Unmanned aircraft systems (UASs) have been under rapid development for applications in the mineral exploration industry, mainly for aeromagnetic surveying. They provide improved detection of smaller, deeper and weaker magnetic targets. A traditional system flying an altitude of 100 m above ground level (AGL) can detect a spherical ore body with a radius of ~ 16 m and a magnetic susceptibility of 10−4 buried at a depth of 40 m. A UAS flying at an altitude of 50 or 2 m AGL would require the radius to be 11 or 5 m, respectively. A demonstration survey was performed using the SkyLance rotary-wing UAS instrumented with a cesium vapour magnetometer in Nash Creek, New Brunswick, Canada. The UAS flew over a zinc deposit featuring three magnetic anomalies. It acquired repeatable data that compared well with upward continuation maps of ground magnetic data. Dykes or faults that are dipping eastward at 25° and are approximately 1.5 m wide fit the observed response of the three anomalies captured on the UAS magnetic data.

Investigation of Rotor–Airframe Interaction Noise Associated with Small-Scale Rotary-Wing Unmanned Aircraft Systems

In this study, acoustic measurements of a hover condition are taken on isolated rotor–airframe configurations representative of small-scale, rotary-wing unmanned aircraft systems (UAS). Each rotor–airframe configuration consists of two fixed-pitch blades powered by a brushless motor, with a simplified airframe geometry intended to represent a generic multicopter arm. In addition to acoustic measurements, computational fluid dynamics–based aeroacoustic predictions are implemented on a subset of the experimentally tested rotor–airframe configurations in an effort to better understand the noise content of the rotor–airframe systems. Favorable agreements are obtained between acoustic measurements and predictions, based on both time- and frequency-domain postprocessing techniques. Results indicate that close proximity of airframe surfaces results in the generation of considerable tonal acoustic content in the form of harmonics of the rotor blade passage frequency (BPF). Analysis of the acoustic prediction data shows that the presence of the airframe surfaces can generate noise levels either comparable to or greater than the rotor blade surfaces under certain rotor tip clearance conditions. Analysis of the on-surface Ffowcs Williams and Hawkings source terms provides insight as to the predicted physical noise-generating mechanisms on the rotor and airframe surfaces.

Interpretation of Very Low Frequency Measurements Carried Out with an Unmanned Aerial System by 2D Conductivity Models

Very Low Frequency (VLF) measurements were successfully acquired using an Unmanned Aircraft System (UAS) as the measurement platform at two sites. The first site was characterized by strong anthropogenic anomalies and was located in Switzerland. The second site was a saltwater-freshwater transition zone in Northern Germany. The induction coils were used to measure the three components of the magnetic field of VLF transmitters. The magnetic field sensors and the corresponding data logger were suspended below a 50 kg rotary wing UAS. Prior to the test survey, noise measurements were carried out to establish a proper distance for the logger and the sensor, which were found at 2 m and 4 m from the body of the UAS, respectively. A suspension system was developed to enable stable flight characteristics in combination with the VLF system. The test flights were carried out with low speed (1 m/s) and at low altitude (approximately 3 m) above ground. A processing algorithm was developed to analyze the time series of the measured magnetic fields. Transfer functions for the vertical magnetic field were derived using both a scalar and a bivariate analysis approach. After rotating the transfer functions into the strike direction of the 2D subsurface anomaly, a two dimensional inversion method was applied for the interpretation of the conductivity structure to a depth of 15 m. In addition, radiomagnetotelluric (RMT) measurements were carried out on the same UAS-VLF profiles. The RMT data were interpreted by 2D inversion for comparison and are used here to derive the background resistivity, which cannot be achieved by VLF measurements. As a result, good correlation was found between the UAS-VLF and RMT conductivity models.

Small Unmanned Aircraft Evaluated for Avalanche Control

The Washington State Department of Transportation's (DOT) snow avalanche control program reduces winter roadway closure times and hazards to motorists. The University of Washington and the Washington State DOT evaluated small unmanned aircraft systems (UASs) as a tool to enhance this program. Because of military investment, UAS technology has dropped in cost as it has become increasingly capable and easier to operate. Commercially available UASs, which fly autonomously, can be operated off a roadway and can collect low-cost, real-time aerial imagery while also carrying payloads. This project conducted a series of test flights involving both fixed- and rotary-wing (helicopter) UASs over a roadway in mountainous terrain. The flights demonstrated that UASs can conduct snowpack and terrain surveillance and can accurately drop explosive charges such as those used to trigger controlled avalanches. The rotary-wing UAS was particularly usable because of its ability to hover, which provided a stable camera platform, and because it required minimal area to land. The reliability of UASs is a concern, and their capabilities may be challenged by mountainous terrain and weather. This problem may be reduced as UASs become either less expensive and more expendable or more reliable and all-weather capable. A major barrier to use of UASs is the need to obtain approval to fly from FAA, a process that can be time-consuming and restrictive. FAA is currently updating its plans to integrate UASs into the national airspace, and a number of technology-based solutions are being considered.