Multi-Protocol Remote Monitoring for Radio Networks

Increasing demand for smaller UAVs (e.g., sometimes with wingspans on the order of six inches and weighing less than one pound) generated a need for much smaller flight and sensing equipment. NASA Langley's new sensing and flight control system for small UAVs includes both an active flight control board and an avionics sensor board. Together, these compare the status of the UAVs position, heading, and orientation with the pre-programmed data to determine and apply the flight control inputs needed to maintain the desired course. To satisfy the small form-factor system requirements, micro-electro-mechanical systems (MEMS) are used to realize the various flight control sensing devices. MEMS-based devices are commercially available single-chip devices that lend themselves to easy integration onto a circuit board. The system uses less energy than current systems, allowing solar panels planted on the vehicle to generate the systems power. While the lightweight technology was designed for smaller UAVs, the sensors could be distributed throughout larger UAVs, depending on the application.

The digital twin NAS simulator provides a complete digital copy of the individual systems that comprise the NAS to allow for the creation of offline simulations to test proposed changes to one or more individual systems based on actual historical data from the NAS or on real-time data from the NAS. The NAS is composed of a collection of systems, including source systems such as weather stations from various locations or airports, which are used by other systems such as individual aircraft flight data and airline operators. Other systems may include management systems such as the FAA, air traffic control centers, and flight traffic monitors. Operational data from each of these systems may be archived by a central information sharing platform such as the System Wide Information Management (SWIM) Program operated by the FAA. The digital twin NAS simulator can access archived SWIM data to create a digital twin NAS system to provide a virtual environment that may operate in real-time alongside the actual NAS, with the digital twin receiving live data updates from the actual NAS. A dedicated application programming interface (API) is used to facilitate communication between various distributed external components and the testbed. The testbed receives NAS data during a test and feeds the data to the simulation manager for use with a digital twin of the NAS system. The result is a virtual environment that is an exact twin of the actual operational system and is able to function identically to the actual NAS system because it is based on and uses the same data archived from the actual NAS system. A primary function of the virtual twin NAS is that it will allow for changes to one or more systems to be simulated against the archived NAS data and subsequently allow for a comparison between the simulated results and the actual results from the operational system. The digital twin simulator may also function in a distributed network environment, allowing for simulations of different elements to run simultaneously, which speeds up and improves the testing and evaluation of proposed changes.

NASA's Extensible Traffic Management (xTM) system allows for distributed management of the airspace where disparate entities collaborate to maintain a safe and accessible environment. This digital ecosystem relies on a common data generation and transfer framework enabled by well-defined data collection requirements, algorithms, protocols, and Application Programming Interfaces (APIs). The key components in this new paradigm are: Data Standardization: Defines the list of data attributes/variables that are required to inform and safely perform the intended missions and operations. Automated Real Time And/or Post-Flight Data Verification Process: Verifies system criteria, specifications, and data quality requirements using predefined, rule-based, or human-in-the-loop verification. Autonomous Evolving Real Time And/or Post-Flight Data Validation Process: Validates data integrity, quantity, and quality for audit, oversight, and optimization. The verification and validation process determines whether an operation’s performance, conformance, and compliance are within known variation. The technology can verify thousands of flight operations in near-real time or post flight in the span of a few minutes, depending on networking and computing capacity. In contrast, manual processing would have required hours, if not days, for a team of 2-3 experts to review an individual flight.

NASA Ames has developed an Autonomous Situational Awareness Platform system for a UAS (ASAP-U), a traffic management system to incorporate Unmanned Aerial Systems (UASs) into the National Airspace System. The Autonomous Situational Awareness Platform (ASAP) is a system that combines existing navigation technology (both aviation and maritime) with new procedures to safely integrate Unmanned Aerial Systems (UASs) with other airspace vehicles. It uses a module called ASAP-U, which includes a transmitter, receivers, and various links to other UAS systems. The module collects global positioning system GPS coordinates and time from a satellite antenna, and this data is fed to the UAS's flight management system for navigation. The ASAP-U module autonomously and continuously sends UAS information via a radio frequency (RF) antenna using Self-Organized Time Division Multiple Access (SOTDMA) to prevent signal overlap. It also receives ASAP data from other aircraft. In case of transmission overload, priority is given to closer aircraft. Additionally, the module can receive weather data, navigational aid data, terrain data, and updates to the UAS flight plan. The collected data is relayed to the flight management system, which includes various databases and a navigation computer to calculate necessary flight plan modifications based on regulations, right-of-way rules, terrain, and geofencing. Conflicts are checked against databases, and if none are found, the flight plan is implemented. If conflicts arise, modifications can be made. The ASAP-U module continuously receives and transmits data, including UAS data and data from other aircraft, to detect conflicts with other aircraft, terrain, weather, and geofencing. Based on this information, the flight management system determines the need for course adjustments and the flight control system executes them for a safe flight route.

The Virtual Target Generator (VTG) is a system designed to create radio frequency (RF) signals that mimic the presence of nearby aircraft, for testing satellite-based surveillance systems. The VTG works by using a GPS receiver or other position data source to calculate a virtual target position, which may be calculated by applying predefined offsets and trajectories relative to the host. These virtual positions are encoded into standard message formats, such as ADS-B, and modulated onto an RF carrier signal. The VTG includes a calibrated signal amplifier that adjusts the signal power so only the target test aircraft receives the signal, ensuring no other aircraft are affected. The test aircraft's surveillance avionics detect and interpret these virtual targets as if they were actual aircraft, enabling full participation in the testing of traffic collision avoidance, surveillance, or display systems. The VTG supports complex test scenarios including dynamic movement, multiple simultaneous targets, and customizable aircraft parameters such as speed, heading, and altitude. The system is fully compliant with FAA ADS-B specifications and can be installed on the test aircraft itself or on a nearby companion aircraft.