A mini-max fusion strategy in distributed multi-sensor system

In this paper, a mini-max fusion strategy in distributed multi-sensor system is proposed, which aims to minimize the worst-case squared estimation error when the cross-covariances between local sensors are unknown and the normalized estimation errors of local sensors are norm bounded. However, this leads to a mini-max convex-concave problem, which is non-convex in general, we relax it to get an approximate solution. The resulted fusion called as the Chebyshev fusion estimation (CFE) is a nonlinear combination of local estimations. The simulations illustrate that the proposed CFE is a robust fusion and more accurate than the previous covariance intersection (CI) method.