  In this paper, we propose an algorithm for channel sensing, collaboration,
and transmission for networks of Tactical Communication Systems that are facing
intrusions from hostile Jammers. Members of the network begin by scanning the
spectrum for Jammers, sharing this information with neighboring nodes, and
merging their respective sets of observation data into a decision vector
containing the believed occupancy of each channel. A user can then use this
vector to find a vacant channel for its transmission. We introduce the concept
of nodes sharing these vectors with their peers, who then merge them into
super-decision vectors, allowing each node to better identify and select
transmission channels. We consider fading scenarios that substantially limit
the reliability of the users' observations, unless they cooperate to increase
the trustworthiness of their sensing data. We propose a pseudo-random channel
selection algorithm that strikes a balance between sensing reliability with the
number of channels being sensed. Simulation results show that the proposed
system improves the network's overall knowledge of the spectrum and the rate of
Jammer-free transmissions while limiting added computational complexity to the
nodes of the network, despite the Jammers' unpredictable nature.
