sUAS Swarm Navigation using Inertial, Range Radios and Partial GNSS

Small Unmanned Aerial Systems (sUAS) operations are increasing in demand and complexity. Using multiple cooperative sUAS (i.e. a swarm) can be beneficial and is sometimes necessary to perform certain tasks (e.g., precision agriculture, mapping, surveillance) either independent or collaboratively. However, controlling the flight of multiple sUAS autonomously and in real-time in a challenging environment in terms of obstacles and navigation requires highly accurate absolute and relative position and velocity information for all platforms in the swarm. This information is also necessary to effectively and efficiently resolve possible collision encounters between the sUAS. In our swarm, each platform is equipped with a Global Navigation Satellite System (GNSS) sensor, an inertial measurement unit (IMU), a baro-altimeter and a relative range sensor (range radio). When GNSS is available, its measurements are tightly integrated with IMU, baro-altimeter and range-radio measurements to obtain the platform’s absolute and relative position. When GNSS is not available due to external factors (e.g., obstructions, interference), the position and velocity estimators switch to an integrated solution based on IMU, baro and relative range meas-urements. This solution enables the system to maintain an accurate relative position estimate, and reduce the drift in the swarm’s absolute position estimate as is typical of an IMU-based system. Multiple multi-copter data collection platforms have been developed and equipped with GNSS, inertial sensors and range radios, which were developed at Ohio University. This paper outlines the underlying methodology, the platform hardware components (three multi-copters and one ground station) and analyzes and discusses the performance using both simulation and sUAS flight test data

Conflict-free trajectory optimization with target tracking and conformance monitoring

This is a postprint (author final draft) deposit on institutional repository UPCommons from UPC, thanks to AIAA. Original version can be found on: https://arc.aiaa.org/doi/10.2514/1.C034251This paper proposes an optimization framework that computes conflict-free optimal trajectories in dense terminal airspace, while continuously monitoring trajectory conformance in an effort to improve predictability. The objective is to allow, as much as possible, continuous vertical trajectory profiles without impacting negatively on airspace capacity. Given automatic dependent surveillance–broadcast intent information, the future state of potential intruder aircraft are predicted, and this nominal trajectory is used as a constraint in the ownship trajectory optimization process. In it, a continuous multiphase optimal control problem is solved, taking into account spatial and temporal constraints. Additionally, a linearized Kalman filter keeps track of the target by estimating the deviations of its actual trajectory from its nominal trajectory, issuing a warning when an appropriate threshold is exceeded. This may be due to unexpected events, biases in the performance and weather models, wrong parameter assumptions, etc. An illustrative example is given, based on a computer simulation of two hypothetical trajectories in the Barcelona terminal maneuvering area. The results show how this framework resolves the problem of uncertainties in the trajectory predictions and results in a more efficient conflict resolution.Peer ReviewedPostprint (author's final draft

GNSS Double Differences used as Beacon Landing System for Aircraft Instrument Approach

When using GNSS navigation for final approach guidance of aircraft to a landing site, the only systems currently available are differential GNSS with additional integrity data called augmentation systems. These work well when the landing site is fixed in space and well surveyed. In all other cases, augmentation systems are difficult to use. Here, we propose relative navigation based on GNSS double difference measurement to accomplish the same task, but also onto moving landing platforms or at unsurveyed locations. We call this the Beacon Landing System. Furthermore, we show long term measurement data confirming the sub-meter accuracy and results from flight tests. During the flight test we successfully used the relative navigation for aircraft guidance

Design and Testing of a Vertically Guided High Precision Approach into Salzburg Airport

The approach to landing on runway 33 of Salzburg Airport, Austria is severely impacted by mountainous terrain on the extended runway centerline. This renders all straight-in approaches but those based on Required Navigation Performance (RNP) Authorization Required (AR) impossible. Only the high navigation accuracy available under RNP AR minimizes the required obstacle protection areas sufficiently to be not penetrated by terrain. The combination of RNP AR and Localizer Performance with Vertical guidance (LPV) makes it furthermore possible to use a more precise angular guidance for the final approach. In Salzburg, this enables a reduction of the decision height from 368 ft to 218 ft above aerodrome level as critical terrain and obstacles now fall outside of the protection areas. A Level D full flight simulator test with an Airbus A350 showed that advanced RNP 0.1 coding is sufficient to achieve RNP 0.1 performance under all permitted environmental conditions

Usability Evaluation of Indicators of Energy-Related Problems in Commercial Airline Flight Decks

A series of pilot-in-the-loop flight simulation studies were conducted at NASA Langley Research Center to evaluate indicators aimed at supporting the flight crews awareness of problems related to energy states. Indicators were evaluated utilizing state-of-the-art flight deck systems such as on commercial air transport aircraft. This paper presents results for four technologies: (1) conventional primary flight display speed cues, (2) an enhanced airspeed control indicator, (3) a synthetic vision baseline that provides a flight path vector, speed error, and an acceleration cue, and (4) an aural airspeed alert that triggers when current airspeed deviates beyond a specified threshold from the selected airspeed. Full-mission high-fidelity flight simulation studies were conducted using commercial airline crews. Crews were paired by airline for common crew resource management procedures and protocols. Scenarios spanned a range of complex conditions while emulating several causal factors reported in recent accidents involving loss of energy state awareness by pilots. Data collection included questionnaires administered at the completion of flight scenarios, aircraft state data, audio/video recordings of flight crew, eye tracking, pilot control inputs, and researcher observations. Questionnaire response data included subjective measures of workload, situation awareness, complexity, usability, and acceptability. This paper reports relevant findings derived from subjective measures as well as quantitative measures

Emerging Technologies for Airplane State Awareness and Prediction

Loss of control in flight (LOC-I) is consistently the leading cause of fatal aircraft accidents. A study of LOC accidents and incidents, commissioned by the Commercial Aviation Safety Team (CAST) identified a growing trend in loss of Airplane State Awareness (ASA) by the flight crew. This has led to recommended safety enhancements that include flight deck technologies with the potential of enhancing flight crew awareness of airplane energy state. The goal of this research is to develop and evaluate technologies that predict and assess the future aircraft energy state and auto-flight configuration, and provide appropriate alerting to anticipated problematic auto-flight inputs, with the aim of enhancing pilots situational awareness

Risk-Based UAV Flight Path Optimization in Accordance with SORA

With the EU regulation of drone operations varying based on the specific type of drone, path planning can be done to consider risk mitigation. This paper proposes a transition-based rapidly exploring random tree star (T-RRT*) path planning algorithm for fixed-wing drone operations over rural areas. Risk is decoded in the cost function, which mainly considers population density and special infrastructure types. It was found that the algorithm is capable of finding paths that minimize exposure of the general population and infrastructure. However, path and computational inefficiencies were found. Usage of another data structure or algorithm might improve performance

Cooperative Swarm Geometry Optimization for Assured Navigation with Range Radios in GNSS-Denied Environments

This paper addresses cooperative navigation using range radios to enable absolute positioning of low-flying UAS (LF) while operating in GNSS-denied environments. High-flying UAS (HF) are positioned above the denied area and broadcast position reports. These reports, in combination with range measurements from the LF to the HF, enable absolute positioning of the LF. (1) Methods: As the navigation performance is directly influenced by the geometry of both LF and HF’s relative positions, HF positions shall be optimized such that the Dilution of Precision (DOP) becomes minimal. The authors derive optimal azimuth angle combinations, which guarantee a minimal Horizontal Dilution of Precision (HDOP), and show the error characteristic for sub-optimal configurations, which enables the formulation of multi-vehicle-constrained optimization problems for specific combinations of numbers of HF and LF. (2) Results: An optimization problem is derived and solved for two HF aiding three LF as an example application for the derived rules. (3) Conclusions: The resulting geometry has yielded promising HDOP values, improving navigation performance in GNSS-denied environments