The En Route Descent Advisor (EDA) is one of the Center TRACON Automation System (CTAS) decision support tools under development at the NASA Ames Research Center. EDA generates maneuver advisories for arrival aircraft to meet scheduled arrival times at the arrival meter fix, sometimes 20 -25 minutes ahead of the aircraft's scheduled meter fix arrival time. This work determined the sensistivity of the EDA advisories to system uncertainties, including initial condition, environmental, and aircraft performance data errors. Using a Monte Carlo simulation that incorporates a Matlab Trajectory Synthesizer (TS) simulation, the sensitivities of the EDA predicted trajectory to these data error sources were obtained. The key metric is the meter fix crossing time error since this metric directly measures the performance of EDA. This performance analysis involved a minimum of 200 Monte Carlo trials per error parameter. In addition to the single aircraft performance analysis, the impact of aircraft prediction errors on conflict detection between closely-spaced aircraft was also explored. These Monte Carlo performance analyses determined how robust the EDA advisories are to input parameter uncertainties. Nomenclature

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The NASA passive Final Approach Spacing Tool (FAST) provides advisory information to the terminal air traffic controller for sequencing and merging of landing aircraft. It consists of the Trajectory Synthesizer (TS) and the Scheduling Logic (SL). FAST has undergone extensive field testing and performance evaluations of the FAST TS algorithms have been conducted. However, no analytical performance evaluations of the FAST SL logic have been performed to date. This paper evaluates the sensitivity of the FAST SL algorithms to velocity errors which are introduced by the radar tracking software. A linear error covariance analysis was performed of the terminal area radar and its alpha-beta tracking filter software. For comparison, an alternate Kalman tracking filter was also evaluated. Using these radar tracking velocity estimation error histories for a typical aircraft flight profile, the FAST TS estimated time of arrival (ETA) statistics history was obtained. To determine the impact of the velocity and ETA errors on FAST SL, figures of merit were defined which predict the probability that FAST SL will reach an incorrect aircraft sequencing decision. These figures of merit were then evaluated, based on the velocity and ETA statistics histories.

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