Abstract-The single sensor probability hypothesis density (PHD) and cardinalized probability hypothesis density (CPHD) filters have been developed using the random finite set framework. The existing multisensor extensions of these filters have limitations such as sensor order dependence, numerical instability or high computational requirements. In this paper we derive update equations for the multisensor CPHD filter. We propose a computationally tractable implementation that greedily identifies measurement subsets and partitions that significantly contribute to the update equations.
In REF , Nannuru et al. derived the update equations for the general multisensor CPHD filter as well as a computationally tractable implementation.
Multisensor CPHD filter
IEEE Transactions on Aerospace and Electronic Systems, Volume: 52, Issue: 4, August 2016
Mathematics Computer Science