PPHDF-AI for multitarget tracking with unknown target SNR

The performance of multitarget tracking can be improved by using target amplitude information (AI) for that targets can be identified earlier through the enhanced discrimination between target and false alarm. However, one of the limitations of this application is that the signal-to-noise ratio (SNR) of target is usually unknown in practice. This paper proposes a particle probability hypothesis density filter (PPHDF) with amplitude information (PPHDF-AI) by extending the state vector and measurement vector of particle filter (PF) can be easily. By the extension of dynamic equation and measurement equation, the proposed algorithm can estimate targets SNR as well as their individual states. Simulation results demonstrate that the proposed method is quite suitable for situation that target SNR is unknown, and is superior to traditional methods.