Opening up of the CBRS band for the secondary users' transmissions poses challenges in the protection of incumbent radar users from co-channel interference. The use of Machine Learning algorithms for addressing these challenges requires representative real-world datasets.This dataset contains overlapping radar and LTE signals captures over-the-air in the shared CBRS band using an experimental testbed composed of software defined radios in RF anechoic chamber.