Date of Award

Winter 2011

Document Type


Degree Name

Doctor of Philosophy (PhD)


Micro and Nanoscale Systems

First Advisor

Jean Gourd


This dissertation introduces a novel process to study and analyze sensor data in order to obtain information pertaining to mobile targets at the sub-pixel level. The process design is modular in nature and utilizes a set of algorithmic tools for change detection, target extraction and analysis, super-pixel processing and target refinement. The scope of this investigation is confined to a staring sensor that records data of sub-pixel vehicles traveling horizontally across the ground. Statistical models of the targets and background are developed with noise and jitter effects. Threshold Change Detection, Duration Change Detection and Fast Adaptive Power Iteration (FAPI) Detection techniques are the three methods used for target detection. The PolyFit and FermiFit are two tools developed and employed for target analysis, which allows for flexible processing. Tunable parameters in the detection methods, along with filters for false alarms, show the adaptability of the procedures. Super-pixel processing tools are designed, and Refinement Through Tracking (RTT) techniques are investigated as post-processing refinement options. The process is tested on simulated datasets, and validated with sensor datasets obtained from RP Flight Systems, Inc.