Multi-sensor IF Estimation Based on Time-Frequency and Spatial Filtering

Abstract

Instantaneous frequency (IF) is an important parameter whose accurate estimation is useful in many applications including source localization, blind source separation and signal detection. We propose a computationally efficient and accurate multi-component IF estimator for multi-sensor recordings. The proposed method iteratively estimates the IF of signal components by first tracking the components based on their angle of arrival information and then removing components through time-frequency (TF) and spatial filtering. Experimental results indicate that the proposed method based on joint TF and spatial filtering leads to accurate IF estimates as compared to a recent method that only performs filtering in the TF domain.