Unmanned Aerial Systems Mission Research Articles

Long Range UAS Mission by LPWAN Communication

One of the key challenges for long range Unmanned Aerial Systems (UAS) is the limitation of the communication capability. Many existing communication technics are conventionally adopted in UAS to improve the quality of the communication such as satellite communication, cellular networks, and relay aircrafts. However, the mentioned solutions often incur several drawbacks including costs, complexity, communication delay, or inefficient power consumption. LoRaWAN is one of the recently emerging communication technics used in the Low Power Wide Area Networks (LPWAN) technology. It has a promising potential to improve the coverage of UAS communication, since it can transmit/receive signals below the noise floor in a very long range with very low energy consumption by using the waveform modulation technique called Chirp Spread Spectrum (CSS). In this paper, we show the potential of LPWAN as the supplementary communication in UAS. The experiment results show that LoRaWAN can maintain the communication capability beyond 80 km where the popular RF device, RFD900x, has lost its ability to communicate at this distance.

Design and Evaluation of Sensor Housing for Boundary Layer Profiling Using Multirotors.

Traditional configurations for mounting Temperature–Humidity (TH) sensors on multirotor Unmanned Aerial Systems (UASs) often suffer from insufficient radiation shielding, exposure to mixed and turbulent air from propellers, and inconsistent aspiration while situated in the wake of the UAS. Descent profiles using traditional methods are unreliable (when compared to an ascent profile) due to the turbulent mixing of air by the UAS while descending into that flow field. Consequently, atmospheric boundary layer profiles that rely on such configurations are bias-prone and unreliable in certain flight patterns (such as descent). This article describes and evaluates a novel sensor housing designed to shield airborne sensors from artificial heat sources and artificial wet-bulbing while pulling air from outside the rotor wash influence. The housing is mounted above the propellers to exploit the rotor-induced pressure deficits that passively induce a high-speed laminar airflow to aspirate the sensor consistently. Our design is modular, accommodates a variety of other sensors, and would be compatible with a wide range of commercially available multirotors. Extensive flight tests conducted at altitudes up to 500 m Above Ground Level (AGL) show that the housing facilitates reliable measurements of the boundary layer phenomena and is invariant in orientation to the ambient wind, even at high vertical/horizontal speeds (up to 5 m/s) for the UAS. A low standard deviation of errors shows a good agreement between the ascent and descent profiles and proves our unique design is reliable for various UAS missions.

Spatio-temporal evaluation of plant height in corn via unmanned aerial systems

Detailed spatial and temporal data on plant growth are critical to guide crop management. Conventional methods to determine field plant traits are intensive, time-consuming, expensive, and limited to small areas. The objective of this study was to examine the integration of data collected via unmanned aerial systems (UAS) at critical corn (Zea mays L.) developmental stages for plant height and its relation to plant biomass. The main steps followed in this research were (1) workflow development for an ultrahigh resolution crop surface model (CSM) with the goal of determining plant height (CSM-estimated plant height) using data gathered from the UAS missions; (2) validation of CSM-estimated plant height with ground-truthing plant height (measured plant height); and (3) final estimation of plant biomass via integration of CSM-estimated plant height with ground-truthing stem diameter data. Results indicated a correlation between CSM-estimated plant height and ground-truthing plant height data at two weeks prior to flowering and at flowering stage, but high predictability at the later growth stage. Log–log analysis on the temporal data confirmed that these relationships are stable, presenting equal slopes for both crop stages evaluated. Concluding, data collected from low-altitude and with a low-cost sensor could be useful in estimating plant height.

Photogrammetric reconstruction of homogenous snow surfaces in alpine terrain applying near-infrared UAS imagery

ABSTRACTOperating unmanned aerial systems (UAS) to record imagery of alpine snow cover for photogrammetric applications is challenging due to topographic and meteorological conditions. Furthermore, the homogenous snow surface encumbers the automated detection of matching points, which are required for generating accurate digital surface models (DSMs). On the other hand, there is rising demand for high spatial resolution snow depth and snow surface-type mapping as well as snow avalanche documentation. UAS have the potential to enable flexible, timely, and cost-efficient data acquisition, even in poorly accessible alpine terrain. This could be a major step forward for many applications in snow hydrology, avalanche research, mitigation measure planning, hazard zonation, and alpine ecology investigations.In this study, we investigate the applicability and performance of UAS-based structure-from-motion (SfM) photogrammetry on very homogenous snow surfaces, under suboptimal illumination conditions, at two alpine test sites in Tschuggen (2000 m a.s.l.) close to Davos, Switzerland, and Lizum (2000 m a.s.l.) near Innsbruck, Austria. We discuss the topographic and meteorological challenges for flying UAS missions in high-alpine terrain. Additionally, we compare DSMs calculated from the imagery acquired in the visual (VIS, λ = 400–700 nm) and near-infrared (NIR, λ = 700–830 nm) parts of the electromagnetic spectrum. We evaluate the resulting DSMs qualitatively and quantitatively by applying: a) differential Global Navigation Satellite System (GNSS) measurements at the Swiss test site, with an expected accuracy better than 0.1 m within x, y, and z directions; b) terrestrial laser scanning (TLS) at the Austrian test site, with an expected accuracy of ± 0.025 m (1σ), along with a distance-dependent error. The results of this study reveal the potential and limitations of UAS-based SfM photogrammetry for applications on snow-covered, alpine terrain in general and in particular the benefit of NIR imagery on the accuracy and precision of the results.