Results
We explore different metrics ( Mean Absolute Error, Mean Absolute Percentage Error, Root Means Squared Error, Mean Error and R-squared ) for each model and report them in table \ref{results-table}. Our evaluation shows that pre-trained networks can be used to perform automated Doppler angle estimation with varying levels of agreement between observation and prediction(error between 4.03% to 9.51% ). A major constraint is availability of data to train the shallow network and a larger dataset should lead to increased accuracy in model estimates.