A trajectory-oriented Possion Multi-Bernoulli mixture method for matched field tracking to achieve trajectory continuity

Matched field processing (MFP) is a widely used array processing method for target localization. However, weak correlation and low SNR data degrade its performance. Furthermore, submerged targets do not radiate signals all the time for the sake of concealment, which be called as "flickering targets" in this paper. MFP is invalid when the flickering target is silent. In order to achieve trajectory continuity of the flickering target and correct localization errors of MFP, we propose a trajectory-oriented Poisson Multi-Bernoulli mixture method for matched field tracking (TPMBM-MFT). This method substitutes the trajectory state model for the traditional target state model and uses the Poisson Multi-Bernoulli mixture of random finite set (PMBM-RFS) to describe the trajectory state model and the MFT measurement model. The performance is verified by using the SWellEx-96 data set and comparing with MFP localization results and other two tracking methods.