  Wireless localization is a key requirement for many applications. It concerns
position estimation of mobile nodes (agents) relative to fixed nodes (anchors)
from wireless channel measurements. Cooperative localization is an advanced
concept that considers the joint estimation of multiple agent positions based
on channel measurements of all agent-anchor links together with all agent-agent
links. In this paper we present the first study of cooperative localization for
magneto-inductive wireless sensor networks, which are of technological interest
due to good material penetration and channel predictability. We demonstrate
significant accuracy improvements (a factor of 3 for 10 cooperating agents)
over the non-cooperative scheme. The evaluation uses the Cram\'er-Rao lower
bound on the cooperative position estimation error, which is derived herein. To
realize this accuracy, the maximum-likelihood estimate (MLE) must be computed
by solving a high-dimensional least-squares problem, whereby convergence to
local minima proves to be problematic. A proposed cooperative localization
algorithm addresses this issue: first, preliminary estimates of the agent
positions and orientations are computed, which then serve as initial values for
a gradient search. In all our test cases, this method yields the MLE and the
associated high accuracy (comprising the cooperation gain) from a single solver
run. The preliminary estimates use novel closed-form MLE formulas of the
distance, direction and orientation for single links between three-axis coils,
which are given in detail.
