Abstract
Automatic dependent surveillance—broadcast (ADS-B) is one of the next-generation aeronautical surveillance systems for air traffic control. ADS-B requires an aircraft to periodically broadcast its own position to other aircraft and ground stations, thereby enabling high-performance surveillance. In this study, the received signal strength (RSS) of the ADS-B signal was measured and characterized for opportunistic flights. The RSS distribution for a single aircraft was modeled as a sum of three components: nominal RSS, bias in the equivalent isotropically radiated power (EIRP), and fading. Then, the RSS distribution for multiple aircraft was defined, considering that the EIRP bias and fading parameter are different for different aircraft. To this end, a composite distribution was employed, the parameters of which were estimated from the bias and fading statistics. Furthermore, a practical approximation of the model was proposed. The proposed model is suitable for large-scale data, enabling the realization of aircraft-by-aircraft analysis. Also, it can provide a clear explanation of the mechanism by which the RSS distribution is formed.
Highlights
A ERONAUTICAL surveillance systems are used to provide aircraft information to air traffic controllers, and they constitute an essential infrastructure for ensuring safe flights
The received signal strength (RSS) distribution for a single aircraft was modeled using the sum of the nominal RSS, equivalent isotropically radiated power (EIRP) bias, and fading
The RSS distribution for multiple aircraft was modeled by a compound distribution because the EIRP bias and the fading parameter are aircraft dependent and were modeled as random variables
Summary
A ERONAUTICAL surveillance systems are used to provide aircraft information to air traffic controllers, and they constitute an essential infrastructure for ensuring safe flights. The measurement of the ADS-B signals results in a large amount of aeronautical data with relatively low cost. Measurements from a 14-day period were analyzed in [33] and [34], but the resulting log-distance model was relatively simple because the uncertainty of the transmission antenna type (bottom or top), transmit antenna gain, and transmit power hindered the realization of a detailed analysis Another example is [28], in which visual comparison with the free space model was presented for one aircraft. The proposed model is expected to be suitable for large-scale data, enabling the realization of aircraft-by-aircraft analysis It can provide a clear explanation of how the RSS distributions of individual aircraft relate to the aggregated distribution.
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