SINBAD - Safety Improved with a New concept by Better Awareness on airport approach Domain
Overview
Background & policy context:
Improving the ability to monitor air traffic in a rapidly growing density of aircraft is a necessity complicated by the foreseen increase of Non-Cooperative Targets (NCT). A new monitoring system capable of raising an alert to endangered aircraft or other ground based assets, in case of a confirmed collision risk, is a crucial element to significantly increase aircraft safety and security, especially in the airport Control Terminal Region (CTR) zone. In order to meet these challenges, a new technology has arisen over the past years: the MSPSR (MultiStatic Primary Surveillance Radar).
The SINBAD project was based on passive MSPSR using DVB-T (digital television broadcast) opportunity transmitters. SINBAD stands for Safety and security Improved by New functionality for Better Awareness on airport approach and departure Domain. It was launched under the 6th EU Framework Programme. SINBAD performed the proof of application of a new concept: improvement of aircraft safety and security at airport approach to 2015 horizon.
Objectives:
SINBAD aimed to perform the proof of application of a new concept, intended to improve aircraft safety and security at airport approach to 2015 horizon. Collision avoidance is currently ensured by the Air Traffic Management System (ATMS), and the Airborne Collision Avoidance System. Both systems are actually ineffective against the risk of accidental or hostile collision by non-cooperative small or low flying aircraft.
The main targets of SINBAD to overcome these limitations are:
- to drastically improve the capability of the ATMS to monitor such non-cooperative aircraft, using a breakthrough low cost sensor technology, the MultiStatic PCL (Passive Coherent Location),
- to support controllers by providing them with an Active Hazard Assessment (AHA) capability, allowing them to quickly alert the adequate authorities and if needed to the relevant airliners, in case of confirmed danger .
The scientific objectives of SINBAD are:
- to develop and optimise a mock-up of the MultiStatic PCL sensor on live data, and of the AHA software component,
- to assess MultiStatic PCL improvement in detection and localisation performances compared to currently available sensors,
- to assess AHA's performance in terms of probability to anticipate collision risks between relevant aircraft and airliners, with a controlled false alarm rate.
Methodology:
To achieve this goal, the tasks performed in SINBAD were:
- to refine the air traffic control (ATC) and security management (SMS) operational concepts for those parts that could make use of such enhanced surveillance capabilities;
- to develop a new concept of primary multi-lateration surveillance (PMS);
- to develop a new concept of Active Hazard Assessment (AHA) functionality for the ATC sub system;
- to perform their proof-of-concept at two different sites (Brno and Frankfurt airports).
The objectives NCT classification work in the SINBAD project was to develop software to support the investigations on the feasibility of such a classification, and to establish the background for further relevant research. They were fully achieved.
The Active Hazard Assessment NCTR module used radar echo data from SINBAD's sensor to classify NCTs supplemented with the motion kinematics. The performance data were calculated from 4D flight paths, and a fuzzy logic function was created and tuned with statistics on several types of aircraft (28 including B747, A320, MD90, PZL101, C172, Falcon, Zlin142, Predator, etc.). The belonging probability was given as a membership value by the fuzzy logic. The accuracy of the results was tested in Brno TMA (Terminal Control Area) with radar measurements in the summer of 2010.
The calculated data were reliable; the applied assumptions have an imperceptible influence on results. However while kinematics provides around 80% accuracy in classification, RCS data were insufficient to complement it to an acceptable operational value.
The method needs further relevant development but the NCT classification is achievable with suitable 3D models and with availability of several different bistatic RCS from SINBAD’s sensor independent Tx/Rx pairs. The capacity to classify should be improved by adding more the aircrafts in the database, preferably by measurement but also with additional simulation.
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