Classification of Military Aircraft in Real-time Radar Systems based on Supervised Machine Learning with Labelled ADS-B Data

Applications and Technologies of Big Data in the Aerospace Domain

“…Although the solution was not yet fully finalized, experimental results showed a promising capability of accurately predicting the type of an aircraft. Dästner et al [56] demonstrated how different Machine Learning methodologies and ADS-B BD can be utilized to classify and identify military aircrafts in real-time applications. More specifically, RF, Gradient Boost Trees and Multilayer Perceptron classification techniques were used.…”

“…Air traffic flow analysis based on ADS-B BD [33], using air traffic and weather BD for improving strategic planning of airlines [34], trajectory prediction based on surveillance and other BD [35], using flown trajectories BD to calculate flight performance indices [36], and visualization of multiple trajectories, utilizing flight BD [37] Delay Prediction and Resource Allocation Flight delay prediction using multiple ML algorithms [38], flight delay prediction based on ADS-B and other BD [39], BD-based residual airspace resource evaluation methodology [40], and BD-enabled network architecture for AGVNs [41] Maintenance Optimization Optimized maintenance and resource allocation based on BD analytics [42] and improving predictive maintenance by utilizing BD from heterogeneous sources [43] Collecting Customer Insights/Increasing Customer Satisfaction BD-based analysis of customer engagement of a commercial airline [44], linear regression model for predicting flight-related web searches [45], and increasing customer satisfaction and improving aviation service quality by utilizing BD from different sources [46] Solutions for the Industry Improving source localization in industrial facilities by using UAV BD [48] and BD analytics for supply chain efficiency based on UAV BD [49] Solutions for Infrastructures Detection of electrical transmission towers based on BD from UAVs [50], BD-based methodology for optimizing 5G service provisioning from UAVs [51], optimized BD management leading to better disaster management [52], EMS based on BD analytics for minimizing operating costs of UAVs [53], and BD data management optimization in applications with UAV base stations [54] Supporting Military Operations BD analysis for characterizing if an aircraft is commercial or military [55], using ADS-B BD for real time classification of aircrafts [56], and improving knowledge management and analysis for testing and evaluation processes of the Joint Strike Fighter program using BD analysis [57] Increasing Air Force Safety BD-based architecture for improving military flight safety [58], improving military aircrafts' health management systems by utilizing heterogeneous BD …”

Trust the Crowd: Wireless Witnessing to Detect Attacks on ADS-B-Based Air-Traffic Surveillance

“…Whereas Sun et al [51] present a trust framework to detect faulty data in VANETs, Hundman et al [17] apply similar data verification schemes for spacecraft. Dästner et al [8] classify military aircraft based on their ADS-B report trace. Wang et al [55] analyzes the feasibility of false data filtering in general sensor networks and Henningsen et al [13] especially focus on industrial networks.…”