Abstract: A probability hypothesis density (PHD) filter using signal amplitude information base on framework of finite set statistics (FISST) is proposed for multi-target tracking in the image plane of optical sensor. Signal amplitude likelihood functions are derived to incorporate amplitude information into this filter. First, the amplitude of signal generated by optical sensor is modeled, and the signal amplitudes of target and clutter are calculated respectively while an alternative method is adopted for the case of unknown target SNR. Gaussian mixture (GM) is used to implement this filter. Simulation results show the significant improvement in multi-target tracking performance and computation cost of our algorithm compared with the generic PHD filter just using location measurements, even when the SNR of target is unknown.

Key words: Optical sensor, Signal amplitude information, RFS, PHD, Multi-target tracking, Gaussian mixture