Traditional state estimation approaches need to solve nonlinear and non-convex optimization problems and gradient-based methods are often used to do this. However

the global optimum cannot be guaranteed mathematically and convergence issue may be confronted. This paper proposes a bilinear robust state estimation (BRSE) method based on exactly linearization measurement equations presented by a foreigner. In this method

only a linear weighted least absolute value (WLAV) problem (equivalent to a linear programming problem)

a nonlinear transformation

and a linear weighted least squares (WLS) problem (quadratic programming problem) should be solved to ensure global optimum mathematically and no existence of convergence. Finally

simulation results show the effectiveness of the proposed method. This work is supported by National High Technology Research and Development Program of China (863 Program) (No. 2012AA050208)

National Natural Science Foundation of China (No. 51407069) and Fundamental Research Funds for the Central Universities (No. 2014QN02).