A kinematics-based flight model, for normal flight regimes, currently uses precise flight data to achieve a high level of aircraft realism. However, it was desired to further increase the model’s accuracy, without a substantial increase in program complexity, by determining the vertical velocity and vertical acceleration using EUROCONTROL’s Base of Aircraft DAta (BADA) model [1]. BADA is a well-known aircraft performance database model maintained and developed by EUROCONTROL Experimental Centre in France. The hybrid model uses the BADA algorithm to determine the vertical velocity and gives original results for determining the vertical acceleration. The approximate accuracy of these vertical parameters was checked by comparing them with preexisting test distributions [2] and an in-house flight simulator application. The hybrid model uses kinematic algorithms for all other functions and parameters. To obtain specific results, C code was written to access text data from BADA’s collection of approximately one hundred airplanes. Accessing this database causes an increase in overall program execution time that was deemed acceptable due to the infrequency of changing plane types. Also, by examining many airplane trajectories obtained from different BADA airplanes, we determined that the model is accurate enough to uniquely represent many different types of aircraft.

This paper investigates the Sense And Avoid (SAA) system for Unmanned Aircraft Systems (UASs) with a Multiple-Trajectory-Prediction (MTP) algorithm that can potentially operate in all categories defined by the U.S. Federal Aviation Administration (FAA) [1]. The MTP algorithm selects avoidance maneuvers for the aircraft to obtain the maximum separation by running simulations in an on-board SAA computer. The algorithm searches for the best maneuver parameters using the data from advanced surveillance systems such as the Automatic Dependent Surveillance-Broadcast (ADS-B). The proposed SAA system with MTP algorithm could be used as the Common Algorithm (CA) for UAS SAA operations with lower cost and higher accuracy compared to the existing systems such as TCAS.

This paper investigates the Sense And Avoid (SAA) system for Unmanned Aircraft Systems (UASs) with a Multiple-Trajectory-Prediction (MTP) algorithm that can potentially operate in all categories defined by the U.S. Federal Aviation Administration (FAA) [1]. The MTP algorithm selects avoidance maneuvers for the aircraft to obtain the maximum separation by running simulations in an on-board SAA computer. The algorithm searches for the best maneuver parameters using the data from advanced surveillance systems such as the Automatic Dependent Surveillance-Broadcast (ADS-B). The proposed SAA system with MTP algorithm could be used as the Common Algorithm (CA) for UAS SAA operations with lower cost and higher accuracy compared to the existing systems such as TCAS.

This paper introduces a new mathematical method for reckoning paths of constant heading along an oblate ellipsoidal surface (e.g., the Earth) and for determining the distances of those paths. The method is particularly fast and accurate, lending itself to use in computationally intensive computer applications, including fast-time aviation simulations and any navigation-related Monte Carlo simulations, where fast execution times and position accuracy are both desirable. This method performs especially well for paths having a large distance and for headings that include changes in both latitude and longitude. In the paper, the proposed method and a traditional "exact" method are derived and their fundamental governing equations provided. Two other methods are also presented for comparison. All methods can produce a final position given an initial position, heading, and distance to be traveled. These methods can also be used to find the distance to a line of longitude or latitude, given a heading and an initial position. For each of four, an example of total path distance is calculated (two of the methods have known, precise World Geodetic System 84 results which are used). These total path distances are then compared to each other for accuracy and in terms of the required calculation execution times.