Date of Award


Document Type


Degree Name

Master of Science


Department of Electrical and Computer Engineering

First Advisor

Matthew Goda, PhD


Space Situational Awareness (SSA) requires repeated object updates for orbit accuracy. Detection of unknown objects is critical. A daytime model was developed that evaluated sun flares and assessed thermal emissions from space objects. Iridium satellites generate predictable sun glints. These were used as a model baseline for daytime detections. Flares and space object thermal emissions were examined for daytime detection. A variety of geometric, material and atmospheric characteristics affected this daytime detection capability. In a photon noise limited mode, simulated Iridium flares were detected. The peak Signal-to- Noise Ratios (SNR) were 6.05e18, 9.63e5, and 1.65e7 for the nighttime, daytime and infrared flares respectively. The thermal emission of space objects at 353K, 900K and 1300K with 2 to 20 m2 emitting areas were evaluated. The peak emission was for the 20 m2 900K object with an SNR of 1.08e10. A number of barriers remain to be overcome if daytime detection of space objects can be achieved. While the above SNR values are large, this is based on optimal detection. The SBR's were less than 1 for all cases. Image post-processing will be necessary to extract the object from the background. Successful daytime detection techniques will increase sensor utilization times and improve SSA.

AFIT Designator


DTIC Accession Number