Reworking the MUSIC Algorithm to Mitigate MSTID Direction Estimation Bias Associated with SuperDARN Radar Field-of-View Geometry

Medium Scale Traveling Ionospheric Disturbances (MSTIDs) are variations in the F region ionospheric electron density. MSTIDs can be associated with atmospheric gravity waves (AGWs) and provide critical information for understanding the ionosphere, which is an electrically charged region of the atmosphere. Previous SuperDARN studies of MSTIDs have used the Multiple Signal Classification (MUSIC) algorithm to determine the size, speed, and direction of these disturbances in the ionosphere. Upon analyzing MSTID MUSIC results from ten North American SuperDARN radars over a period of twelve winter seasons (2010-2022), we found a bias in the SuperDARN MSTID MUSIC direction estimation algorithm that preferentially reports waves as traveling along the boresight direction of the radars. We demonstrate that this bias is caused by the radar Field-of-View geometry and report on the progress algorithm development for removing this bias.