  In future wireless communication networks, existing active localization will
gradually evolve into more sophisticated (passive) sensing functionalities. One
main enabler for this process is the merging of information collected from the
network's nodes, sensing the environment in a multi-static deployment. The
current literature considers single sensing node systems and/or single target
scenarios, mainly focusing on specific issues pertaining to hardware
impairments or algorithmic challenges. In contrast, in this work we propose an
ensemble of techniques for processing the information gathered from multiple
sensing nodes, jointly observing an environment with multiple targets. A
scattering model is used within a flexibly configurable framework to highlight
the challenges and issues with algorithms used in this distributed sensing
task. We validate our approach by supporting it with detailed link budget
evaluations, considering practical millimeter-wave systems' capabilities. Our
numerical evaluations are performed in an indoor scenario, sweeping a variety
of parameter to analyze the KPIs sensitivity with respect to each of them. The
proposed algorithms to fuse information by multiple nodes show significant
gains in terms of targets' localization performance, with up to 35\% for the
probability of detection, compared to the baseline with a mono-static setup.
