  Monitoring networks contain monitoring nodes which observe an area of
interest to detect any possible existing object and estimate its states. Each
node has characteristics such as probability of detection and clutter density
which may have different values for distinct nodes in non-homogeneous
monitoring networks. This paper proposes a modified covariance intersection
method for data fusion in such networks. It is derived by formulating a mixed
game model between neighbor monitoring nodes as players and considering inverse
of the trace of fused covariance matrix as players' utility function.
Monitoring nodes estimate the states of any possible existing object by
applying joint target detection and tracking filter on their own observations.
Processing nodes fuse the estimated states received from neighbor monitoring
nodes by the proposed modified covariance intersection. It is validated by
simulating target detection and tracking problem in two situations: one-target
and unknown number of targets.
