The purpose of this thesis is to emphasize the lacking areas in the field of direction of arrival estimation and to propose building blocks for continued solution development in the area. A review of current methods are discussed and their pitfalls are emphasized. DOA estimators are compared to each other for usage on a conformal microphone array which receives impulsive, wideband signals. Further, many DOA estimators rely on the number of source signals prior to DOA estimation. Though techniques exist to achieve this, they lack robustness to estimate for certain signal types, particularly in the case where multiple radar targets exist in the same range bin. A deep neural network approach is proposed and evaluated for this particular case. The studies detailed in this thesis are specific to acoustic and radar applications for DOA estimation.