Multisensor multitarget intensity filter

A multisensor multitarget intensity filter is derived for N sensors. The multitarget process is assumed to be a Poisson point process, as are the sensor measurement sets. The sensor data are pooled, but sensor labels are retained. The likelihood function of the pooled data is obtained via the Poisson point process models. The Bayes information updated point process is not Poisson, but it is shown that all its single target marginal probability densities are identical. The Bayes posterior density is approximated by the product of its marginal densities. The marginal single target density is scaled to obtain the intensity of the Poisson point process approximation. The fused multisensor multitarget intensity filter is the average of the sensor intensity filters, provided sensor coverages are identical. The filter for non-identical sensor coverages is also described.