  The sensor whose output is a function of the sum of contributions from
targets present in the surveillance area is called superpositional sensor. In
this letter, target clustering based multi-Bernoulli filter for superpositional
sensors is proposed.Targets are clustered according to the set of resolution
cells illuminated by them. Single target posterior density is strictly derived,
and densities of all the targets are combined to a approximate multi-target
posterior, which makes the multiBernoulli density is conjugate with respect to
the likelihood of superpositional sensors. The Gaussian implementation of the
proposed algorithm is also presented, where the multidimensionality and the
nonlinearity of update equation are handled by sigma point transformation. The
simulation results illustrate that the proposed algorithm is effective
confronted with the interaction of multiple targets and long term overlapping
of two targets.
