Application of Evolution Strategies to the Design of Tracking Filters with a Large Number of Specifications
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Application of Evolution Strategies to the Design of Tracking Filters with a Large Number of Specifications ´ Garc´ıa Herrero Jesus Departamento de Inform´atica, Escuela Polit´ecnica Superior (EPS), Universidad Carlos III de Madrid, 28911 Legan´es, Madrid, Spain Email: [email protected]
Juan A. Besada Portas Departamento de Se˜nales, Sistemas y Radiocomunicaciones, ETSI Telecomunicaci´on, Universidad Polit´ecnica de Madrid, 28040 Madrid, Spain Email: [email protected]
´ Antonio Berlanga de Jesus Departamento de Inform´atica, EPS, Universidad Carlos III de Madrid, 28911 Legan´es, Madrid, Spain Email: [email protected]
´ Jose´ M. Molina Lopez Departamento de Inform´atica, EPS, Universidad Carlos III de Madrid, 28911 Legan´es, Madrid, Spain Email: [email protected]
Gonzalo de Miguel Vela Departamento de Se˜nales, Sistemas y Radiocomunicaciones, ETSI Telecomunicaci´on, Universidad Polit´ecnica de Madrid, 28040 Madrid, Spain Email: [email protected]
Jose´ R. Casar Corredera Departamento de Se˜nales, Sistemas y Radiocomunicaciones, ETSI Telecomunicaci´on, Universidad Polit´ecnica de Madrid, 28040 Madrid, Spain Email: [email protected] Received 28 June 2002 and in revised form 14 February 2003 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 hundreds of performance goals. The design problem is stated as a numeric search in the filter parameters space to attain all specifications or at least minimize, in a compromise, the excess over some specifications as much as possible, applying global optimization techniques coming from evolutionary computation field. Besides, a new methodology is proposed to integrate specifications in a fitness function able to effectively guide the search to suitable solutions. The method has been applied to the design of an IMM tracker for a real-world civil air traffic control application: the accomplishment of specifications defined for the future European ARTAS system. Keywords and phrases: evolution strategies, radar tracking filters, multicriteria optimization.
1.
INTRODUCTION
A tracking filter has the double goal of reducing measurement noise and consistently predicting future values of signal. This kind of problems has efficient solutions in the case
of stationary signals, but solutions for nonstationary problems are not so consolidated yet. This is the case in the field we are dealing with in this paper, tracking aircraft trajectories from radar measurements in air traffic control (ATC) applications.
Evolution Strategies to Design Tracking Filters The design of tracking filters for the ATC problem demands complex algorithms, like the modern interacting multiple model (IMM) filter [1]. These algorithms depend on a high number of parameters (seven in the IMM desi
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