Publications

The Traffic Alert and Collision Avoidance System (TCAS) is mandated on all large transport aircraft to reduce mid-air collision risk. Since its introduction, no mid-air collisions between TCAS-equipped aircraft have occurred in the United States. However, General Aviation (GA) aircraft are generally not equipped with TCAS and experience collisions several times per year. There is interest in low-cost collision avoidance systems for GA aircraft to reduce collision risk with other GA aircraft as well as with TCAS-equipped aircraft. Since TCAS was designed for large aircraft that can achieve greater vertical rates, the assumptions made by the system and the associated advisories are not always appropriate for GA aircraft. Modifying the TCAS logic to accommodate GA aircraft is far from straightforward. Even minor changes to TCAS to correct operational issues are difficult to implement due to the interaction of the complex rules defining the logic. Recent work has explored an alternative to the TCAS logic based on optimization with respect to a probabilistic model of aircraft behavior. The model encodes performance constraints of GA aircraft, and a computational technique called dynamic programming allows the optimal collision avoidance strategy to be computed efficiently. Prior work has focused on systems that meet the performance assumptions of the existing TCAS logic. However, these assumptions are not always appropriate for GA aircraft. This paper will present simulation results comparing the existing logic to logic that has been optimized to operate onboard GA aircraft. If both aircraft are equipped with collision avoidance logic, it is important that the advisories be coordinated to prevent both aircraft from climbing or descending. The TCAS logic has a built-in coordination mechanism with which a GA system must maintain compatibility. Several coordination strategies, both with the optimized logic and the current logic, are evaluated in simulation.

We designed and constructed a system that includes aircraft, ground vehicles, and throwable sensors to search a semiforested region that was partially covered by foliage. The system contained 4 radio-controlled (RC) trucks, 2 aircraft, and 30 SensorMotes (throwable sensors). We also investigated communications links, search strategies, and system architecture. Our system is designed to be low-cost, contain a variety of sensors, and distributed so that the system is robust even if individual components are lost.

Airspace protection in the capital area is provided by an Integrated Air Defense System (IADS) created through the coordinated response of U.S. government and local law-enforcement agencies, including the Department of Defense, the Department of Homeland Security, the Federal Aviation Administration, and the Capitol Police. The IADS includes U.S. Coast Guard helicopters, fighter aircraft, and airborne early-warning aircraft cued by surveillance radars. Under Operation Noble Eagle, the response to a threat includes warning flares deployed from fighter aircraft and, ultimately, the use of surface and air-launched missiles. Selecting the appropriate response requires a means for rapidly assessing the aircraft threat. New and existing sensors must be simultaneously cued to the target of interest and integrated with existing sources of information to display a common-air-picture display to support the decision makers. This article describes the development of an Enhanced Regional Situation Awareness system, an integrated sensing and decision support system developed for the complex and busy airspace surrounding the National Capital Region.

Decision-directed learning (DDL) is an iterative discrete approach to finding a feasible solution for large-scale combinatorial optimization problems. DDL is capable of efficiently formulating a solution to network scheduling problems that involve load limiting device utilization, selecting parallel configurations for software applications and host hardware using a minimum set of resources, and meeting time-to-result performance requirements in a dynamic network environment. This paper quantifies the algorithms that constitute DDL and compares its performance to other popular combinatorial self-directed real-time networked resource configuration for dynamically building a mission specific signal-processor for real-time distributed and parallel applications.

A concise theoretical technique is presented for estimating the minimum miss distance capability of command guided missile systems using synthetic proportional navigation. The effect of the parameter values on the system capability is shown to be a function of range-to-intercept; the technique enables the system designer and analyst to quantify system performance and to develop a systematic understanding of the performance limitations of command guidance systems at each intercept range. New analytical equations based upon adjoint theory are developed for statistical miss distance caused by target maneuver, range-dependent, servo, glint and atmosphere noises for command guided systems. An optimal total system time constant is derived which yields the minimum statistical miss distance. Realistic constraints on the minimum achievable system time constant are considered. The equations derived for the optimal total system time constant are valuable to the system designer for minimizing miss distance over the ranges of system parameters and limitations, and intercept conditions.