A portable primary radar for general aviation.

A detailed situation awareness of the local environment is essential for safe flight in General Aviation. When operating under Visual Flight Rules, eyesight is crucial for maintaining situation awareness and objects may be overlooked. Technical solutions such as Flarm have been sought, but they only work on a basis of co-operation: obstacles without the proper equipment are invisible. Recent developments in the field of radar technology, partly empowered by the demand for sensors for autonomous cars, have improved the size and power consumption of available hardware. Today, the hardware exists to build a portable primary radar system for situation awareness. In this paper the results are presented of efforts to build the first portable primary radar for general, which has to be lightweight, cheap and have a low power consumption. The focus in this paper is on the software design of such a radar system. The physical principles of radar sensing are described, as well as the scientific steps needed to provide situation awareness. The hardware and software for the radar are both built and tested, and the results of these tests are presented. A flight experiment is performed with a small aircraft flying past a stationary radar on a small hill. It is found that the radar is capable of detecting the aircraft up to a distance of at least 3 kilometers. 3D localization is performed and the location determined by the radar was on average 46 meters away from the aircraft position as measured by satellite navigation, relative to a total distance of about 1000 meters from the radar. A low-pass filter can be applied on the raw results in order to improve the location estimation further. Future research will focus on bringing the portable radar in motion while operating.

Weather field reconstruction using aircraft surveillance data and a novel meteo-particle model.

Wind and temperature data are important parameters in aircraft performance studies. The lack of accurate measurements of these parameters forces researchers to rely on numerical weather prediction models, which are often filtered for a larger area with decreased local accuracy. Aircraft, however, also transmit information related to weather conditions, in response to interrogation by air traffic controller surveillance radars. Although not intended for this purpose, aircraft surveillance data contains information that can be used for weather models. This paper presents a method that can be used to reconstruct a weather field from surveillance data that can be received with a simple 1090 MHz receiver. Throughout the paper, we answer two main research questions: how to accurately infer wind and temperature from aircraft surveillance data, and how to reconstruct a real-time weather grid efficiently. We consider aircraft as moving sensors that measure wind and temperature conditions indirectly at different locations and flight levels. To address the first question, aircraft barometric altitude, ground velocity, and airspeed are decoded from down-linked surveillance data. Then, temperature and wind observations are computed based on aeronautical speed conversion equations. To address the second question, we propose a novel Meteo-Particle (MP) model for constructing the wind and temperature fields. Short-term local prediction is also possible by employing a predictor layer. Using an unseen observation test dataset, we are able to validate that the mean absolute errors of inferred wind and temperature using MP model are 67% and 26% less than using the interpolated model based on GFS reanalysis data.

Carbon-supported base metal nanoparticles: cellulose at work.

Pyrolysis of base metal salt loaded microcrystalline cellulose spheres gives a facile access to carbon-supported base metal nanoparticles, which have been characterized with temperature-dependent XRD, SEM, TEM, ICP-MS and elemental analysis. The role of cellulose is multifaceted: 1) it facilitates a homogeneous impregnation of the aqueous base metal salt solutions, 2) it acts as an efficacious (carbonaceous) support material for the uniformly dispersed base metal salts, their oxides and the metal nanoparticles derived therefrom, and 3) it contributes as a reducing agent via carbothermal reduction for the conversion of the metal oxide nanoparticles into the metal nanoparticles. Finally, the base metal nanoparticles capable of forming metastable metal carbides catalytically convert the carbonaceous support into a mesoporous graphitic carbon material.

Human factors evaluations of Free Flight Issues solved and issues remaining.

The Dutch National Aerospace Laboratory (NLR) has conducted extensive human-in-the-loop simulation experiments in NLR's Research Flight Simulator (RFS), focussed on human factors evaluation of Free Flight. Eight years of research, in co-operation with partners in the United States and Europe, has shown that Free Flight has the potential to increase airspace capacity by at least a factor of 3. Expected traffic loads and conflict rates for the year 2020 appear to be no major problem for professional airline crews participating in flight simulation experiments. Flight efficiency is significantly improved by user-preferred routings, including cruise climbs, while pilot workload is only slightly increased compared to today's reference. Detailed results from three projects and six human-in-the-loop experiments in NLR's Research Flight Simulator are reported. The main focus of these results is on human factors issues and particularly workload, measured both subjectively and objectively. An extensive discussion is included on many human factors issues resolved during the experiments, but also open issues are identified. An intent-based Conflict Detection and Resolution (CD&R) system provides "benefits" in terms of reduced pilot workload, but also "costs" in terms of complexity, need for priority rules, potential compatibility problems between different brands of Flight Management Systems and large bandwidth. Moreover, the intent-based system is not effective at solving multi-aircraft conflicts. A state-based CD&R system also provides "benefits" and "costs". Benefits compared to the full intent-based system are simplicity, low bandwidth requirements, easy to retrofit (no requirements to change avionics infrastructure) and the ability to solve multi-aircraft conflicts in parallel. The "costs" involve a somewhat higher pilot workload in similar circumstances, the smaller look-ahead time which results in less efficient resolution manoeuvres and the sometimes false/nuisance alerts due to missing intent information. The optimal CD&R system (in terms of costs versus benefits) has been suggested to be state-based CD&R with the addition of intended or target flight level. This combination of state-based CD&R with a limited amount of intent provides "the best of both worlds". Studying this CD&R system is still an open issue.