An Enhanced Multi-target Multi-Bernoulli Particle Filtering for Direction of Arrival Tracking in the Presence of Impulsive Noise

In the scerinao of impulsive noise, this paper proposes a multi-Bernoulli enhanced auxiliary particle filtering (MB-EAPF) algorithm for multi-source direction of arrival tracking by utilizing uniform linear array configuration. By proposing an EAPF to solve the particle degradation issue raised by the resampling method of the conventional multi-target multi-Bernoulli (MeMBer) filtering. Moreover, since the measurement data is disturbed by impulsive noise and its second-order statistic fails, the phased fractional low order moment matrix is utilized as an alternate covariance matrix. Furthermore, the likelihood function of the MeMBer filtering is replaced by the multiple signal classification spatial spectral function and exponentially weighted to obtain more particles closer to the posterior distribution. Simulation results demonstrate that the proposed algorithm provides better tracking performance and more accurate estimation than the conventional MeMBer filtering.