Multi Sensor Data Fusion Architectures for Air Traffic Control Applications

Nowadays, the radar is no longer the sole technology which is able to ensure the surveillance of air traffic. The extensive deployment of satellite systems and air-to-ground data links leads to the emergence of complementary means and techniques on which a great deal of research and experiments have been carried out over the past ten years. In such an environment, the sensor data processing, which is a key element in any Air Traffic Control (ATC) centre, has been continuously upgraded so as to follow the sensor technology evolution and in the meantime improves the quality in term of continuity, integrity and accuracy criteria. This book chapter proposes a comprehensive description of the state of art and the roadmap for the future of the multi sensor data fusion architectures and techniques in use in ATC centres. The first part of the chapter describes the background of ATC centres, while the second part of the chapter points out various data fusion techniques. Multi radar data processing architecture is analysed and a brief definition of internal core tracking algorithms is given as well as a comparative benchmark based on their respective advantages and drawbacks. The third part of the chapter focuses on the most recent evolution that leads from a Multi Radar Tracking System to a Multi Sensor Tracking System. The last part of the chapter deals with the sensor data processing that will be put in operation in the next ten years. The main challenge will be to provide the same level of services in both surface and air surveillance areas in order to offer: ⢠highly accurate air and surface situation awareness to air traffic controllers, ⢠situational awareness via Traffic Information System â Broadcast (TIS-B) services to pilots and vehicle drivers, and ⢠new air and surface safety, capacity and efficiency applications to airports and airlines

Air Traffic Control Tracking Systems Performance Impacts with New Surveillance Technology Sensors

Nowadays, the radar is no longer the only technology able to ensure the surveillance of air traffic. The extensive deployment of satellite systems and air-to-ground data links lead to the emergence of other means and techniques on which a great deal of research and experiments have been carried out over the past ten years. In such an environment, the sensor data processing, which is a key element of an Air Traffic Control center, has been continuously upgraded so as to follow the sensor technology evolution and, at the same time, ensure a more efficient tracking continuity, integrity and accuracy. In this book chapter we propose to measure the impacts of the use of these new technology sensors in the tracking systems currently used for Air Traffic Control applications. The first part of the chapter describes the background of new-technology sensors that are currently used by sensor data processing systems. In addition, a brief definition of internal core tracking algorithms used in sensor data processing components, is given as well as a comparison between their respective advantages and drawbacks. The second part of the chapter focuses on the Multi Sensor Tracking System performance requirements. Investigation regarding the use of Automatic Dependent Surveillance â Broadcast reports and/or with a multi radars configuration, are conducted. The third part deals with the impacts of the âvirtual radarâ or âradar-likeâ approaches that can be used with ADS-B sensors, on the multi sensor tracking system performance. The fourth and last part of the chapter discusses the impacts of sensor data processing performance on sub-sequent safety nets functions that are: ⢠Short term conflict alerts (STCA), ⢠Minimum Safe Altitude Warnings (MSAW), and ⢠Area Proximity Warnings (APW)

Targeting Tryptophan Decarboxylase to Selected Subcellular Compartments of Tobacco Plants Affects Enzyme Stability and in Vivo Function and Leads to a Lesion-Mimic Phenotype

Tryptophan decarboxylase (TDC) is a cytosolic enzyme that catalyzes an early step of the terpenoid indole alkaloid biosynthetic pathway by decarboxylation of l-tryptophan to produce the protoalkaloid tryptamine. In the present study, recombinant TDC was targeted to the chloroplast, cytosol, and endoplasmic reticulum (ER) of tobacco (Nicotiana tabacum) plants to evaluate the effects of subcellular compartmentation on the accumulation of functional enzyme and its corresponding enzymatic product. TDC accumulation and in vivo function was significantly affected by the subcellular localization. Immunoblot analysis demonstrated that chloroplast-targeted TDC had improved accumulation and/or stability when compared with the cytosolic enzyme. Because ER-targeted TDC was not detectable by immunoblot analysis and tryptamine levels found in transient expression studies and in transgenic plants were low, it was concluded that the recombinant TDC was most likely unstable if ER retained. Targeting TDC to the chloroplast stroma resulted in the highest accumulation level of tryptamine so far reported in the literature for studies on heterologous TDC expression in tobacco. However, plants accumulating high levels of functional TDC in the chloroplast developed a lesion-mimic phenotype that was probably triggered by the relatively high accumulation of tryptamine in this compartment. We demonstrate that subcellular targeting may provide a useful strategy for enhancing accumulation and/or stability of enzymes involved in secondary metabolism and to divert metabolic flux toward desired end products. However, metabolic engineering of plants is a very demanding task because unexpected, and possibly unwanted, effects may be observed on plant metabolism and/or phenotype