Joint DOA tracking and spectral signature estimation of wideband sources using a multi-spectral TBD-CPHD filter

•Joint Direction of arrival tracking and spectral signature estimation of wideband sources.•Using the random finite set framework for the derivation of Cardinalized probability hypothesis density filter.•Considering the superpositional measurement model and improving the performance by providing a tack-before-detect CPHD filter in low SNR scenarios.•Derivation of filter relations using Parallel combination lemma which is generally used in multi-sensor fusion.•Covariance-based measurements and Complex Wishart random matrices. In this paper, a novel method for direction of arrival (DOA) tracking of multiple unknown time-varying number of wideband emitters is presented using a random finite set (RFS) framework. This method combines multiple narrowband covariance-based measurements to form a wideband cardinalized probability hypothesis density (CPHD) filter using the parallel combination (PC) Lemma generally used in multisensor fusion. By doing this, each narrowband frequency bin acts as a separate virtual spectral sensor. The covariance-based measurements, represented by complex Wishart random matrices, also allow the method to have a track-before-detect (TBD) property, which has shown to be advantageous in very low signal-to-noise ratios (SNR). Furthermore, the proposed method can simultaneously monitor the spectrum of the environment and extract the spectral characteristics of the active sources, i.e. can work as some sort of cognitive radio (CR). The suggested algorithm is implemented using an auxiliary particle filter. The simulation results and the comparison with the known state-of-the-art approaches confirm the superiority of the proposed method in negative SNR scenarios and low number of snapshots.