Various probabilistic and deterministic methods have been developed and extensively validated in simulation environments to enhance safety in hybrid manned-unmanned airspace. However, reliance on simulation alone limits real-world assessment of algorithm reliability. This work closes a critical simulation-to-flight validation gap for right-of-way (RoW) logic by experimentally evaluating a morphing potential field algorithm in representative encounters and quantifying the minimum detection distance required for a fixed-wing UAS to maintain well-clear from a crewed aircraft. Flight tests were conducted using a general aviation Cessna 172 Skyhawk and a fixed-wing UAS, both instrumented with ADS-B to enable cooperative DAA functionality. Seventeen flight test scenarios were conducted, systematically varying the relative heading and speed to generate a diverse set of encounters and to map well-clear outcomes as a function of detection range. Results indicate that simulations accurately predicted the UAS's ability to maintain the required 2000-ft right-of-way separation in most cases, with 88% of flight test outcomes aligning with simulation-based well-clear classifications. Taken together, the experimentally observed detection range thresholds and the measured simulation-to-flight mismatch demonstrate that high-fidelity nonlinear simulation provides strong predictive capability for DAA performance and can effectively guide design and pre-flight screening. However, the observed sensitivity to nonlinear right-of-way logic, encounter phasing, and unmitigated collision distance highlights the necessity of at least a detection range of 3,962-m or greater in the tested ranges to meet well-clear requirements when utilizing the morphing potential field algorithm.

Rapid growth in unmanned aircraft systems (UAS) applications has resulted in exponential increase in the number of new but inexpensive aircraft. Open-source or engineering-level analysis software supports most of these designs and their dynamic analyses. This work analyzes the validity of a perturbed non-linear six-degree-of-freedom simulation of a fixed-wing UAS under six flight conditions. The aircraft model is developed using a component build-up method. Simulations are compared to flight data under different flight conditions: straight flight, level turn, ascending and descending flight. We additionally assessed the dynamic model accuracy when the aircraft was forced into loss of control. In another flight test, the commanded flight speed was reduced to coerce the aircraft into a stall. Unsupervised learning algorithms are used to classify flight data into different flight phases and to select flight portions for analysis. Monte Carlo (MC) simulations are performed to assess dynamic model accuracy while taking simulation parameter uncertainties into account. Results qualify uncertainty levels in predicted states and show that the base dynamic model can only capture aircraft's body rotation rate trends within some errors. The MC simulations mostly capture the flight rotation rates, however, in several instances, the flight data is not captured despite considering simulation parameter uncertainties.

Wake vortices can have a big impact on the flight safety of manned and unmanned aircraft. This paper focuses on the development and validation of HawkWakeSim 2.0, a new simulation tool for modeling and predicting small fixed-wing UAS’ response to wake vortex encounters. Currently, two different UAS were implemented: a T-tailed Phastball UAS and a flying-wing KHawk 55 UAS operating in both open loop and with inner loop roll and pitch hold controllers. HawkWakeSim 2.0 uses coupled aerodynamics (vortex lattice method) and flight dynamics calculations for prediction of small UAS’ responses to wake vortices produced by various types of leading aircraft. Results from two wake encounter angles, 20-degree and 90-degree, are presented when flying through wake vortices generated by three representative manned aircraft, Cessna 172, Cessna Citation, and Boeing 737. Initial results show the effectiveness of the developed simulation when compared with another simplified WVE modeling method. Representative longitudinal and lateral UAS WVE response metrics such as body frame accelerations and rotation rates were investigated for wake hazard evaluation.

With the advent of the unmanned aerial systems (UAS) era, it is important that research be conducted into the reliable and safe operation of UAS in urban areas, where aircraft are flying over people and property in spatially constrained environments. A large focus in recent years has been on adaptable collision avoidance systems capable of avoiding fixed and airborne traffic. This paper presents flight test validation of an adaptive collision algorithm known as the morphing potential field algorithm. The morphing potential field algorithm has been modified to allow implementation of more advanced guidance logics such as L 2 + guidance. The aim is to validate the morphing collision avoidance path planning algorithm in a complex scenario, with multiple aircraft-two fixed wing and two rotary wing-flying the same spatially constrained area. The aircraft were intentionally put in a collision course with each other and other obstacles. Validation flight tests were successfully conducted to assess performance of morphing potential field navigation algorithms and also to quantify the impact of possible communication delays on the safety of collision avoidance methods for high speed and high inertia aircraft.

Ice thickness and bed topography of fast-flowing outlet glaciers are large sources of uncertainty for the current ice sheet models used to predict future contributions to sea-level rise. Due to a lack of coverage and difficulty in sounding and imaging with ice-penetrating radars, these regions remain poorly constrained in models. Increases in off-nadir scattering due to the highly crevassed surfaces, volumetric scattering (due to debris and/or pockets of liquid water), and signal attenuation (due to warmer ice near the bottom) are all impediments in detecting bed-echoes. A set of high-frequency (HF)/very high-frequency (VHF) radars operating at 14 MHz and 30–35 MHz were developed at the University of Kansas to sound temperate ice and outlet glaciers. We have deployed these radars on a small unmanned aircraft system (UAS) and a DHC-6 Twin Otter. For both installations, the system utilized a dipole antenna oriented in the cross-track direction, providing some performance advantages over other temperate ice sounders operating at lower frequencies. In this paper, we describe the platform-sensor systems, field operations, data-processing techniques, and preliminary results. We also compare our results with data from other ice-sounding radars that operate at frequencies both above (Center for Remote Sensing of Ice Sheets (CReSIS) Multichannel Coherent Depth Sounder (MCoRDS)) and below (Jet Propulsion Laboratory (JPL) Warm Ice Sounding Explorer (WISE)) our HF/VHF system. During field campaigns, both unmanned and manned platforms flew closely spaced parallel and repeat flight lines. We examine these data sets to determine image coherency between flight lines and discuss the feasibility of forming 2D synthetic apertures by using such a mission approach.

This work presents validation and verification for a novel collision avoidance algorithm designed for fixed-wing unmanned aerial systems with high speed and high inertia. The generic potential field formulation is reformulated to better navigate fixed-wing aircraft in complex scenarios and in unstructured environments in the presence of external disturbances. In this approach, the potential field is adaptively morphed to account for approach angles and relative velocities. To avoid violating aircraft dynamic constraints, the morphing potential field considers aircraft six degrees of freedom dynamic constraints. LQ guidance path planning with multi-scale moving point guidance algorithms were designed and implemented, and their tracking performance and was assessed through flight testing. Several successful flight tests involving two UASs in head-on collision scenarios were successfully conducted.

This paper presents recent updates to the CReSIS radar sensor package and the platforms supporting these sensors. These sensors cover a wide frequency range (14 MHz to 38 GHz). The specific frequency bands are chosen to balance between bandwidth available and signal penetration. The wide frequency range is also used for measuring different phenomenology. CReSIS has integrated these radar systems, including antennas, on a wide variety of fixed wing crewed aircraft, several UAV platforms, and for ground-based applications. The software for processing the radar data is now open source and an overview of the capabilities and how to access and use the software are presented. Finally, example data products which explore the new capabilities of the sensors and platforms are given.

A novel approach to collision and obstacle avoidance in fixed-wing unmanned aerial systems with high speed and high inertia was developed by reformulating classical artificial potential field navigational approaches. Classical artificial potential field navigation is a formidable approach to collision avoidance for slow and small robots including rotary-wing UASs, however they lack robustness and adaptability for large fixed-wing aircraft flying in close proximity or congested areas. As part of a concept demonstration, this work presents the validation and verification of morphing potential collision avoidance using large unmanned aerial systems flying at 60 ft/sec. The morphing potential function was constrained by the aircraft's six-degree-of-freedom dynamic characteristics and maximum allowable bank angle. A virtual time-varying waypoint is used to navigate the aircraft in a dynamically changing environment. The validation flight tests were successfully conducted and real-time avoidance capabilities were demonstrated.

The impact of high update rate on the disparity in eigenvalues of the auto-correlation matrix, along with slow convergence and reduced stability of numerical analysis are well studied. However, the impact of high update rates of autopilots on the performance of unmanned aircraft has been ignored due to the intrinsic limitations of COTS autopilots computation power. Although MEMS based IMUs have very high update rates, the majority of existing UAS autopilot system processing power is limited to 20 Hz. In this work, the challenges and processes for developing and flight test validating an autonomous flight controller for a large 30-kg fixed-wing UAS using an in-house advanced autopilot system at a relatively higher update rate (50 Hz) are outlined. The goal was specifically set to identify the impact of high update rate and high vibration on an LQR-based automatic flight controller. Initial flight test results yielded adverse performance in the presence of significant sensor noise due to the high structural vibrations of the airframe from a reciprocal engine, high sampling rate, and the inherent lack of robustness of LQR control to unmodelled dynamics. Post processing of flight test data was used to identify the noise profile of the engine and improve IMU filters. This was utilized in designing and implementing a stability-augmentation system. The improved controller was flight tested at different initial conditions under substantial wind conditions (9-12 knots) and the system displayed satisfactory results for autonomous flight.

We have developed an unmanned aerial system consisting of a compact sounding radar operating in the frequency bands of 14 and 35 MHz integrated into a fixed-wing UAV for remote surveys of glaciers and ice-sheets. The system is capable of collecting coherent sounding measurements along multiple parallel tracks. With the use of differential GPS for precise trajectory determination, we demonstrate multipass SAR array processing. The system was recently deployed by CReSIS personnel in the spring of 2016 to survey the Russell glacier in Greenland. This paper reports on the instrumentation including the integration of the radar, antennas, and aircraft; the survey flights in Greenland; and results from measurements collected at 35 MHz.

The wide use of the Global Positioning System (GPS) for navigation has been persistent for a long time. However, in today's scenario when technologies are advancing the accuracy of positioning systems, there are various new threats and challenges emerging. The signal receivers for positioning systems are prone to spoofing. This external interference in the system is usually done by feeding false signals to the receiver. Though the dead reckoning method is still in use, any interference with GPS can still lead to disaster. Insects and birds are known to use solar position for guidance and it is widely accepted by researchers that some birds, such as pigeons, use solar position in their homing flight. There are similar studies performed on honeybees and monarch butterflies. The use of solar position by these insects and birds brings up the question of whether a mathematical model can be used to replicate the results for aircraft navigation, and can a bio-inspired navigation algorithm like this be implemented? Solar position algorithms are already in wide use. The solar position algorithms available calculate the azimuth and zenith/incidence angles for the solar position at any given point of time when the position of the observer is known. The objective for navigation is to find an observer's position from solar position to present an alternative to GPS for navigational use. This document proposes a method for calculating the observer's position when the azimuth and zenith/incidence angles for solar position, attitude of aircraft and time are known. The approach proposed is that the position of the observer can be calculated by reversing the ENEA algorithm where instead of calculating the solar position using an observer's position, one will be calculating the position of the observer from solar position and time. The study includes the comparison of the calculated position of a UAS using the proposed method with the onboard GPS readings for both the ideal and the mimicked sensor accuracies for the position of the sun.

Prior static studies of three-dimensionally woven carbon/epoxy textile composites show that large interlaminar normal and shear strains occur as a result of layer waviness under static compression loading. This study addresses the dynamic response of 3D through-thickness angle interlock textile composites, and how interaction between different layer waviness influences the modal frequencies. The samples have common as-woven textile architecture, but they are cured at varying compaction pressures to achieve varying levels of fiber volume and fiber architecture distortion. Samples produced have varying final cured laminate thickness, which allows observations on the influence of increased fiber volume (generally believed to improve mechanical performance) weighed against the increased fiber distortion (generally believed to decrease mechanical performance). The results obtained from this study show that no added damping was developed in the as-woven identical panels. Furthermore, a linear relation exists between modal frequency and thickness (fiber volume).

Airborne sounding of ice sheets requires large, wing-mounted antenna arrays to effectively filter and suppress the surface clutter that often masks weak bed echoes. However, when a high-sensitivity antenna array is mounted to the wings of an aircraft, the array is subjected to structural dynamics and subsequent deformation. We measured the response of a scaled wing-mounted array when excited at four different vibration frequencies to characterize the effects of airframe vibration on array beamforming and received radar signals. We determined that phase and amplitude errors caused by the expected vibration from the aircraft do not significantly degrade the radiation pattern when the Chebyshev or minimum-variance distortionless response (MVDR) beamformers are used. In the case of the Chebyshev-weighted array, vibrations did not cause pattern sidelobes to vary by more than 1.5 dB. In the case of the minimum-variance-distortionless-response-weighted array, vibrations did cause pattern nulls to shift and decrease in depth, but these pattern distortions were negligible, and did not significantly degrade clutter suppression. In addition, we were able to identify the frequency of vibration as well as the frequency of local structural modes by taking the FFT of the signal's phase.

This paper extends reverberation chamber theory to include chambers constructed out of non-metallic composite materials. This extension allows reverberation chamber theory to predict the shielding effectiveness (SE) of modern aluminum and composite aircraft. Existing theory is based on a power balance approach for aperture-excited cavities, and this paper extends it to include leakage through the cavity walls. Cavity excitation and power dissipation mechanisms are examined in detail, and the cavity SE is related to cavity energy loss in terms of the “quality factor.” SE measurements were made on a partially assembled Uncrewed Aerial System constructed with a carbon-fiber composite skin. The test-analysis agreement shows a high degree of correlation.

To unlock the economic and societal benefits of unmanned aerial vehicles (UAVs), they must possess an acceptable level of situation awareness so as not to become a public safety hazard. Implementation of a system to provide this awareness will surely involve a sense-and-avoid radar due to its capability and robustness. This paper focuses on the development of a sense-and-avoid radar system being developed for operation on a 40% scale Yak-54 UAV that will provide range, Doppler, and angle-of-arrival information of targets which might cause a collision. A two-dimensional (2-D) fast-Fourier transform (FFT) is implemented which maps targets of interest to a single range-Doppler cell. Phase differences in the target signal from an array of receiving antennas are used to determine the target echo's three-dimensional angle-of-arrival. The complete radar system consumes slightly less than 20 W. While the investigation is still underway, initial results indicate that a frequency-modulated, continuous-wave radar system using a 2-D FFT processing algorithm is one viable solution to improve UAV situation awareness.