• Title/Summary/Keyword: Automatic dependent surveillance-broadcast

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Low-Earth orbit satellite constellation for ADS-B based in-flight aircraft tracking

  • Nguyen, Thien H.;Tsafnat, Naomi;Cetin, Ediz;Osborne, Barnaby;Dixon, Thomas F.
    • Advances in aircraft and spacecraft science
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    • v.2 no.1
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    • pp.95-108
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    • 2015
  • Automatic Dependent Surveillance Broadcast (ADS-B) is quickly being adopted by aviation safety authorities around the world as the standard for aircraft tracking. The technology provides the opportunity for live tracking of aircraft positions within range of an ADS-B receiver stations. Currently these receiver stations are bound by land and local infrastructural constraints. As such there is little to no coverage over oceans and poles, over which many commercial flights routinely travel. A low cost space based ADS-B receiving system is proposed as a constellation of small satellites. The possibility for a link between aircraft and satellite is dependent primarily on proximity. Calculating the likelihood of a link between two moving targets when considering with the non-periodic and non-uniform nature of actual aircraft flight-paths is non-trivial. This analysis of the link likelihood and the performance of the tracking ability of the satellite constellation has been carried out by a direct simulation of satellites and aircraft. Parameters defining the constellation (satellite numbers, orbit size and shape, orbit configuration) were varied between reasonable limits. The recent MH370 disappearance was simulated and potential tracking and coverage was analysed using an example constellation. The trend of more satellites at a higher altitude inclined at 60 degrees was found to be the optimal solution.

Risk Analysis of Aircraft Operations in Seoul TMA Based on DAA Well Clear Metrics using Recorded ADS-B Data (ADS-B 데이터를 이용한 서울 TMA에서의 DAA Well Clear 기반 위험도 분석)

  • Lee, Hak-Tae;Lee, Hyeonwoong
    • Journal of Advanced Navigation Technology
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    • v.24 no.6
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    • pp.527-532
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    • 2020
  • Seoul terminal maneuvering area (TMA) that includes Incheon International Airport (ICN) and Gimpo International Airport is a very congested airspace with around 1,000 daily flights and the airspace blocked at the boundary between Incheon flight information region (FIR) and Pyongyang FIR. Consequently, with frequency radar vectorings, separation assurance in this airspace is complicated thus resulting in higher controller workload. In this paper, the conflict and collision risks in Seoul TMA are analyzed using recorded ADS-B data for past three years. Using the recorded trajectories, original flight plan procesures and routes are reconstructed and the risks are quantified using detect and avoid well clear (DWC) metric that is developed for large unmanned aircraft system. The region west of ICN was found to be the highest risk area regardless of the runway directions. In addition, merge and crossing points between procedures displayed relatively high risks.

Airspeed Estimation Through Integration of ADS-B, Wind, and Topology Data (ADS-B, 기상, 지형 데이터의 통합을 통한 대기속도 추정)

  • Kim, Hyo-Jung;Park, Bae-Seon;Ryoo, Chang-Kyung;Lee, Hak-Tae
    • Journal of the Korean Society for Aeronautical & Space Sciences
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    • v.50 no.1
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    • pp.67-74
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    • 2022
  • To analyze the motion of aircraft through computing the dynamics equations, true airspeed is essential for obtaining aerodynamic loads. Although the airspeed is measured by on-board instruments such as pitot tubes, measurement data are difficult to obtain for commercial flights because they include sensitive data about the airline operations. One of the commonly available trajectory data, Automatic Dependent Surveillance-Broadcast data, provide aircraft's speed in the form of ground speed. The ground speed is a vector sum of the local wind velocity and the true airspeed. This paper present a method to estimate true airspeed by combining the trajectory, meteorological, and topology data available to the public. To integrate each data, we first matched the coordinate system and then unified the altitude reference to the mean sea level. We calculated the wind vector for all trajectory points by interpolating from the lower resolution grid of the meteorological data. Finally, we calculate the true airspeed from the ground speed and the wind vector. These processes were applied to several sample trajectories with corresponding meteorological data and the topology data, and the estimated true airspeeds are presented.