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The application of data-filtering techniques for air-traffic-control and surveillance systems is re-reviewed. Operational requirements of these systems are primarily described. They are typically composed of radars (mechanical scanning and phased array), data-processing devices (digital computers) and displays. The environment is determined by the number and characteristics of targets and by the density and characteristics of the unintentional (weather, etc.) and intentional interferences. The effect of the environment on the filtering techniques used is also considered. In the case of air traffic control, a(Â¿, Ã) filtering algorithm, which is used for primary radars, secondary radars and d.a.b.s. (discrete address beacon systems) is described. Collision-avoidance techniques and their implementation are also mentioned. In the case of air defence and surveillance systems, the algorithms are more sophisticated because of unpredictable target motion, high acceleration and intentional interferences. The types of algorithms which may be employed are the Kalman filter (also with variable data rate for phased-array radar), adaptive filters for manoeuvring targets, filters for target tracking in clutter and jamming environment, a filter for tracking of targets formations and, finally, nonlinear filters using radial velocity information. Moreover, the above mentioned techniques affect fire-control and interceptor-guidance methods. The filtering methods are extended to the multiradar case. Some specific problems, which are herein emphasised, concern the ways of combining the information coming from the different radars, the measurement time alignment and co-ordinate conversion over large areas. The methods of filter implementation, being affected by the technology available, are also described. Finally, a comprehensive list of references, refering to the different topics, has been included.