Graduate School of Engineering & Management


Universities & Industry
CDE collaborates on research projects with both universities and industries. The Center manages new and existing Cooperative Research and Development Agreements (CRADAs). CDE will also collaborate in the co-authorship of joint proposals. Inquiries should be directed to Dr. Steven Fiorino, CDE Director.

Government Agencies
CDE works directly with DOD and other US government agencies to address research problems related to directed energy by consulting, advising, and conducting sponsored research. Most CDE research is sponsred by the US Air Force or other government agencies. Inquiries concerning research collaboration should be directed to Dr. Steven Fiorino, CDE Director.

CDE currently collaborates with the following universities, industries, and government agencies:

  • Air Force Research Laboratory
  • Air Force
  • Army
  • Dayton Area Graduate Studies Institute (DAGSI)
  • Directed Energy Professional Society (DEPS)
  • Directed Energy Test and Evaluation Capability (DETEC)
  • High Energy Laser – Joint Technology Office (HEL-JTO)
  • The Joint Precision Approach and Landing System (JPALS)
  • MZA
  • National Aeronautics and Space Administration (NASA)
  • The National Air and Space Intelligence Center (NASIC)
  • Naval Postgraduate School (NPS) and the Optical Sciences Company (tOSC)
  • Navy
  • Notre Dame
  • University of Dayton
  • National Reconnaissance Office (NRO)
  • Riverside Research 
  • University of California, Los Angeles (UCLA)
  • University of New Mexico (UNM)


Modeling & measurement of deep turbulence, refractive layers and their effects

There is a growing interest in the Department of Defense (DoD) in developing optical systems capable of operating over long distances (path lengths up to and over 100 km) in the atmosphere. These systems are envisioned to be a part of land-, airborne- or space-based weapon, sensing and surveillance platforms operating at different altitudes ranging from the ground and atmospheric boundary layer to the upper troposphere, stratosphere, and even space. To optimally design, build, and evaluate the performance of these new systems requires fundamental scientific knowledge of atmospheric effects along paths that may cross several extended regions with distinctive refractive index spatial structures and temporal dynamics, as well as deep understanding of impact of the extended-range atmospheric phenomena on optical wave characteristics.  The existing fundamental scientific understanding and knowledge necessary to enable accurate prediction of the impact of atmospheric effects on laser beam and image propagation over long distances is either insufficient or even absent. Under a multi-university research initiative (MURI) grant from AFOSR, CDE is collaborating with 5 other universities to understand and model atmospheric optics effects over extended range propagation distances and in deep turbulence. Several new approaches for atmospheric sensing over long-range distances are being investigated by the researchers at CDE:

Mesoscale estimations of Cn2 profile based on satellite and weather radar measurements

The idea is based on utilization of information that is available from the continuously operating weather satellites and radar systems for atmospheric turbulence sensing over mesoscale size areas. The researchers also considered the possibility for sensing of the refractive structure parameter Cn2 based on a combined analysis of data obtained from weather radars and satellites, and numerical weather prediction simulations. They showed that the temperature field data from satellite measurements can be used to derive vertical index of refraction structure parameter profiles, while numerical weather prediction data can be used to enhance the accuracy of the satellite-derived Cn2 values. This work is in progress with the ultimate goal of estimating structure parameters of temperature, CT2, refractive index, Cn2, and wind velocity, Cv2 over large volumes and obtaining cloud location and aerosol extinction fields. The numerical weather forecasting results are compared to the corresponding atmospheric characteristics obtained using ground-based LIDAR measurements. The ongoing research can result in currently unavailable capabilities for atmospheric optical characteristics estimation over mesoscale size regions of interest which include long-range laser beam propagation or optical imaging paths.  

Atmospheric refractivity and turbulence sensing with time-lapse imagery

Refractive effects of the atmosphere can range from something as subtle as an apparent shift in target position to something as spectacular as mirages and the green flash. Although the physics behind these phenomena are well known, their characteristics such as strength, frequency of occurrence, and correlation to meteorological data are lacking. These characteristics can be of value to different tactical mission planning. In order to examine the potential of predicting the refractive behavior of the atmosphere at a particular location from meteorological measurements and modeling, the CDE team along with their MURI collaborators pioneered a low-cost time-lapse imaging system consisting of a commercial camera with a zoom lens for the purpose of sensing the guiding and optical ray bending phenomena caused by atmospheric refraction.

A significant advantage of the proposed time-lapse imaging system is that long duration monitoring of image dynamics (weeks or months) is possible with the camera operated in a time-lapse mode. Experiments have been performed with this type of system over a 12.8 km path in Dayton, OH and a 15.3 km path in Las Cruces, NM. Due to changes in the refractive index gradient during the course of a day, a corresponding slow vertical drift in the images was observed. An estimate of the gradient variations during the daytime was obtained from this image motion. The path averaged refractive index gradient variations derived from the time-lapse imagery were compared with those derived from a coupled mesoscale- ray trace  model developed by one of the collaborating teams. The daytime gradient variations from the imaging experiment were in good agreement with those predicted from the mesoscale-ray trace models. These first results are a good indication for the possibility to predict refractive index gradient variations from both numerical weather models and time-lapse imaging.

The time-lapse imagery was also exploited to estimate turbulence. The images showed two distinguished components of image motion: the slow vertical motion due to changes in refractive index gradient and a faster, random motion, which can be attributed to turbulence-induced wavefront tilts. Since statistics of wavefront tilts depends on the turbulence strength, the random image motion sensing was used for estimating the path averaged refractive index structure constant, Cn2. The proposed Cn2 estimation technique uses a set of weighting functions that depend on the size of the imaging aperture and the patch size in the image whose motion is being tracked. Since this technique is phase based, it may be applied to strong turbulence paths where traditional irradiance based methods fail to work due to saturation effects.  This work is in progress with the ultimate goal of obtaining turbulence profile along a path from time-lapse imagery.