Algorithms for airborne Doppler radar wind shear detection

Honeywell has developed algorithms for the detection of wind shear/microburst using airborne Doppler radar. The Honeywell algorithms use three dimensional pattern recognition techniques and the selection of an associated scanning pattern forward of the aircraft. This 'volumetric scan' approach acquires reflectivity, velocity, and spectral width from a three dimensional volume as opposed to the conventional use of a two dimensional azimuthal slice of data at a fixed elevation. The algorithm approach is based on detection and classification of velocity patterns which are indicative of microburst phenomenon while minimizing the false alarms due to ground clutter return. Simulation studies of microburst phenomenon and x-band radar interaction with the microburst have been performed and results of that study are presented. Algorithm performance indetection of both 'wet' and 'dry' microbursts is presented

Automatic Passenger Counting in the HOV Lane

This research applied wave band and computer vision methods to automatically count vehicle occupants in the High Occupancy Vehicle (HOV) lane at a high level of accuracy. The research showed that use of near-infrared bandwidth offers potential as a method for developing an automatic vehicle occupant counting system. Near-infrared only can produce images when looking through glass, but not metal or heavy clothes, which limits its accuracy in counting children or occupants resting in vehicles. The mid-infrared camera did not produce clear images at highway speeds. The next step involves additional research into a working device that can count vehicle occupants reliably, including analysis of device performance with more types of vehicles, passengers in the back seats, children in car seats, and passengers lying down.GuidestarPavlidis, Ioannis; Symosek, Peter; Morellas, Vassilios; Fritz, Bernard; Papanikolopoulos, Nikolaos P; Sfarzo, Robert. (1999). Automatic Passenger Counting in the HOV Lane. Retrieved from the University Digital Conservancy, https://hdl.handle.net/11299/686