Aiming at the problem of the parameter estimation fusion of multisensor linear regression model

where the noise of the observation is unknown but norm-bounded.The feasible parameter set（FPS） is described as all admissible solution to the linear system.Chebyshev center of FPS is the point of in the worst-case which make the estimation error minimize

which is used as a robust estimation fusion of the parameter.This problem can be solved in the complex domain in some cases

but in real domain only get the relaxed Chebyshev center（RCC） estimator in present research.It is demonstrated Chebyshev center of FPS on real plane can be solved by convex optimization of a set of finite restrain

so Chebyshev center can be obtained via efficient optimization algorithms.An approximate Chebyshev center（ACC） fusion algorithm is designed via the projections of the FPS to each coordinate planes.The numerical experiment results show that the method is prior to relaxed Chebyshev center fusion.