Abstract: The present article describes the architecture of a system submitted to the DCASE 2020 Challenge - Task 3: Sound Event Localization and Detection. The proposed method conforms a low complexity solution for the task. It is based on four building blocks: a spatial parametric analysis to find single-source spectrogram bins, a particle tracker to estimate trajectories and temporal activities, a spatial filter, and a single-class classifier implemented with a gradient boosting machine . Results from the development dataset show that the proposed method outperforms a deep learning baseline in three out of the four evaluation metrics considered in the challenge, and obtains an overall score almost ten points above the baseline.