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Access Type

Open Access Thesis

Document Type


Degree Program

Electrical & Computer Engineering

Degree Type

Master of Science (M.S.)

Year Degree Awarded


Month Degree Awarded



Wind energy is one of the fastest-growing segments of the world energy market; however, wind energy facilities can have detrimental effects on wildlife, especially birds and bats. The ability to monitor vulnerable species in the vicinity of proposed wind sites could enable site selection that favors more vulnerable species, but current monitoring tools lack this classification capability. This work analyzes polarimetric and Doppler measurements of migrating birds for species based variation.

A novel two stage feature extraction technique was developed to enable comparison between birds. Stage one involves mapping time changing radar measurements to the birds behavioral state in time (i.e. flapping and gliding); stage two uses this behavioral state information to produce temporal and statistical features that describe the frequency and appearance of these different behavioral states.

General trends of temporal features (ex. wing-beat frequency) in the dataset match Ecological literature and validate the feature extraction approach. Preliminary clustering of bird detection data suggests possible species based subgroups of targets, although a larger dataset is needed for further validation.


First Advisor

Stephen Frasier