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Aircraft Tracking in Air Traffic Control

Air Traffic Control (ATC) is responsible for managing the flow of aircraft operating within the National Airspace System (NAS). The Federal Aviation Agency (FAA) has projected that demands at the nation''s major airports may soon exceed capacity. Hence, the flow of traffic around airports is a major bottleneck to air traffic. Various researchers have investigated several concepts to enhance future Air Traffic Management. These include conflict detection and resolution, pilot intent inference, accurate aircraft trajectory predictions, and aircraft time-of-arrival predictions. A key requirement for implementation of the above concepts is an accurate knowledge of aircraft positions, velocities and flight modes. Furthermore, an accurate modeling of aircraft flight mode transitions is required for conformance monitoring under future ATM operations, such as Airborne spacing, trajectory based operations, and super density operations, under the Next Generation Air Transportation System (NextGen).

We have developed an aircraft dynamic model for aircraft tracking in ATC based on the SLHS. The SDTHE algorithm is then used as the state estimation algorithm for tracking the aircraft positions/velocities and estimating the aircraft flight modes. A distinction of the SLHS model is that it can model aircraft which are following standard ATC flight routes or clearances, and is able to describe uncertianties in aircraft's flight mode transitions due to navigation uncertainties and unknown pilot intents. It has been shown that the proposed model/algorithm yields better tracking accuracy and mode estimation accuracy compared with other popular hybrid system models and hybrid estimation algorithms in ATC tracking. A comparison of the performance of the SDTHE algorithm and that of the IMM algorithm in a ATC tracking application is given in Figure 4 and Table 1. For the IMM algorithm, we have considered two designs (IMM1 and IMM2) with different constant mode transition probabilities.

(a) Tracking error in horizontal plane.

(b) Tracking error in vertical plane.

Figure 4: Comparison of tracking errors of the SDTHE algorithm and those of the IMM algorithm.

Table 1: Comparison of mode estimation errors of SDTHE algorithm versus those of the IMM algorithm.