Optimizing Machine Learning Algorithms for Dynamic Direction Finding
John M. Willis, Satheesh Bojja Venkatakrishnan, John L. Volakis · 2023
We build, analyze, and compare six machine learning algorithms for direction-finding on dynamic systems. Each model is optimized to decrease its computational complexity to make quicker angle-of-arrival estimates and maintain accuracy. The extracted angle determination compares favorably in terms of accuracy and speed to the MUSIC algorithm, with some models exceeding its performance.