[Back]

S. Niedermayr, G. Retscher, A. Wieser:
"The Role of RFID in a Low-cost Localization System for Provision of a Complete Operational Picture on Regional Airports";
Talk: European Navigation Conference ENC 2013, Wien (invited); 2013-04-23 - 2013-04-25; in: "European Navigation Conference 2013", (2013), 7 pages.

A Complete Operational Picture (COP) for airports is the comprehensive representation of all relevant information that is required for the operation on the airport in fields of activities which are accessed by more than one user. Effective management of the entire traffic on the airport in tight cooperation of the airport operator and air traffic control is therefore of high priority. Nowadays, a variety of localization techniques such as multilateration, GNSS, Wireless Local Networks (WLAN) and Radio Frequency Identification (RFID) are available for the provision of the movement of vehicles and objects for the visualization in a COP. A low-cost solution may be sufficient to determine the position and movement on the apron of all vehicles (such as baggage carts, tank lorries, etc.) and mainly static objects (i.e., objects which are moved rarely as compared to the time they are static, such as parked baggage trolleys or containers and gangways). As each localization technology has its advantages and disadvantages, an intelligent integration of positioning techniques in a multi-modal manner is developed in our pilot study. The combination and tight coupling of GNSS pseudoranges and WLAN signal strengths for the location determination of the vehicles is applied as a main localization technology. The use of RFID as a secondary positioning technology in the multi-modal localization system is introduced and investigated in this paper. RFID transponders (a.k.a. tags) can be deployed at so-called virtual gates (e.g. at critical transit passages such as entrances to taxiways, hangars and other buildings or gas stations, etc.). The vehicles are equipped with RFID readers and in driving past a virtual gate the position and driving direction of the vehicle can be determined. On the other hand, mostly static objects are positioned using a newly developed refined cell-based approach. The cell origin is determined using Bayesian estimation applied to data collected by vehicles quasi-randomly passing the objects. In the study it could be shown that the multi-modal localization concept can be employed successfully for the location determination of all relevant vehicles and objects on the apron of an airport.