Publications

The Weather Systems Processor (WSP) is being deployed by FAA at 35 medium and high-density ASR-9 equipped airports across the United States. The Machine Intelligent Gust Front Algorithm (MIGFA) developed at Lincoln Laboratory provides important gust front detection and tracking capability for this system as well as other FAA systems including Terminal Doppler Weather Radar (TDWR) and Integrated Terminal Weather System (ITWS). The algorithm utilizes multidimensional image processing, data fusion, and fuzzy logic techniques to recognize gust fronts observed in Doppler radar data. Some deficiencies in algorithm performance have been identified through ongoing analysis of data from two initial limited production WSP sites in Austin, TX (AUS) and Albuquerque, NM (ABQ). At AUS, the most common cause of false alarms is bands of low-reflectivity rain echoes having shapes and intensities similar to gust front thin line echoes. Missed or late detections have occasionally occurred when gust fronts are near or embedded in the leading edge of approaching line storms, where direct radar evidence of the gust front (e.g.. thin line echo, velocity convergence) may be fragmented or absent altogether. In ABQ, "canyon wind" events emanating, from mountains located just east of the airport occur with very little lead time, and often with little or no radar signatures, making timely detection on the basis of the radar data alone difficult. MIGFA is equipped with numerous parameters and thresholds that can be adjusted dynamically based on recognition of the local or regional weather context in which it is operating. Through additional contextual weather information processing, this dynamic sensitization capability has been further exploited to address the deficiencies noted above, resulting in an appreciable improvement in performance on data collected at the two WSP sites.

Conflicts between birds and commercial aircraft are a noteworthy problem at both large and small airports [Cleary, 1999]. The risk factor for United States airports continues to increase due to the steady rise in take-off/landings and bird populations. There is a significant bird strike problem in the terminal area as shown by the incidents reported in the National Bird Strike Database [Cleary and Dolbeer, 1999]. The focus of bird strike mitigation in the past has centered primarily on wildlife management techniques. Recently, an Avian Hazard Advisory System (AHAS) has been developed to reduce the risks of bird strikes to military operations [Kelly, 1999]. This system uses a mosaic of data obtained from the Next Generation Weather Radar (NEXRAD). This sensor serves as an excellent tool for enroute bird advisories due to the radar coverage provided across the majority of the United States. However, its utility in the airport terminal environment is limited due to the slow update rate and the fact that the distance of most NEXRADs from the airport results in beam heights that are too high to detect low-altitude birds over the airport. The Federal Aviation Administration (FAA) operates two radar systems – the Terminal Doppler Weather Radar (TDWR), and the Airport Surveillance Radar (ASR-9) -- that could be used to help monitor bird activity at an airport in order to: 1. Provide continuously updated information on locations and approximate numbers of birds in flocks roosting or feeding on or near an airfield; 2. Generate real-time warnings of bird activity for dissemination to pilots of landing or departing aircraft by air traffic controllers or by direct data link. The TDWR provides wind shear warnings in the terminal area to enhance safety, while the ASR-9’s primary function is air traffic control. Both of these systems have been shown to detect biological echoes as well. Characteristics of the two radar systems have been examined and compared to determine capabilities for bird detection. Amongst other favorable factors, the high update rate and on-airport locale makes the ASR-9 a highly desirable platform for a bird detection and warning system for the terminal area. Data from an ASR-9 at Austin TX (AUS) equipped with a Weather Systems Processor (WSP) have been analyzed to assess the ASR-9's capability to detect and monitor bird activity. The WSP add-on provides a variety of radar base data products similar to those that would be available on all ASR-9s as part of an ASR-9 Service Life Extension Program (SLEP) currently underway. The Austin airport area is subject to large flocks of wintering migratory birds as well as a resident population of bats in close proximity to the airport. Radar data, visual observations and bird strike information during periods of active bird/bat movements have been collected for this study. An automated processing algorithm called the Terminal Avian Hazard Advisory System (TAHAS) is being developed to detect and track roosting and migratory birds using ASR-9 data. A key challenge will be the ability to discriminate biological from non-biological targets based on variables such as vertical continuity, variance or spectral width, and horizontal velocity distribution.