Gonzalo de Miguel Vela

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A simple ADS-B data fusion method to incorporate ADS-B data in traffic control centres already operative is presented. The implementation of this solution has low-impact on the system with a quite acceptable performance. The goal is to make the fusion with the minimal intervention on the tracking filter already tuned and tested.
This paper describes the application of evolution strategies to the design of interacting multiple model (IMM) tracking filters in order to fulfill a large table of performance specifications. These specifications define the desired filter performance in a thorough set of selected test scenarios, for different figures of merit and input conditions, imposing(More)
This paper describes an off-line bias estimation and correction system for Air Traffic Control related sensors, used in a newly developed Eurocontrol tool for the assessment of ATC surveillance systems. Current bias estimation algorithms are mainly focused in radar sensors, but the installation of new sensors (especially Automatic Dependent(More)
This work addresses the application of a machine-learning approach to classify ATC trajectory segments from recorded opportunity traffic. It is based on the mode probabilities estimated by an IMM tracking filter operating forward and backward over available data. A learning algorithm creates a rule base for classification from these data, once they have(More)
The evolution of airborne communication systems and ground stations make it possible to improve the performance of tracking systems, in order to increase capacity, safety and efficiency of air traffic environments. These new systems enable downlinking several aircraft parameters for use in ground air traffic management (ATM) systems. Some of these(More)
This work addresses off-line accurate trajectory reconstruction for air traffic control. We propose the use of specific dynamic models after identification of regular motion patterns. Datasets recorded from opportunity traffic are first segmented in motion segments, based on the mode probabilities of an IMM filter. Then, reconstruction is applied with an(More)
This paper describes two tracking filters based on the use of kinematic information (velocity, acceleration), in addition to usual position measurements. This kinematic information allows for more advanced filtering methods, reducing error especially on maneuvers. In the paper we will show two different Kalman filter exploiting this information, and compare(More)
In this contribution we present a design procedure, based on Evolutionary Strategies Optimisation, to parametrize Interacting Multiple Model tracking structures for Air Traffic Control Applications. The objective, not addressed in the available bibliography on IMM filters, is to find the most suitable parameters (including transition probabilities and(More)
We present a double-parameter CFAR with very reasonable losses and low computational complexity. Its basic architecture has been conceived from tail extrapolation theory. The detector uses a detection threshold, set from the measured PFA which is obtained with an auxiliary threshold (pseudothreshold), lower than the final detection threshold. Starting from(More)