Comprehensive evaluation measures of nonlinear estimation algorithm performance

Abstract

Although many scholars say that their algorithms are better than others in the state estimation problem, only a fewer convincing algorithms were applied to engineering practices. The reason is that their algorithms outperform others only in some aspects such as the estimation accuracy or the computation load. To solve the problem of performance evaluation of state estimation algorithms, in this paper, the comprehensive evaluation measures (CEM) for evaluating the nonlinear estimation algorithm (NEA) is proposed, which can comprehensively reflect the performance of the NEAs. First, we introduce three types of the NEAs. Second, the CEM combining the flatness, estimation accuracy and computation time of the NEAs, is designed to evaluate the above NEAs. Finally, the superiority of the CEM is verified by a numerical example, which helps decision makers of nonlinear estimation algorithms theoretically and technically.