Spectral amplitude modulation（SAM）is an empirical and automated nonlinear filtering process. Despite its simplicity，it has achieved noteworthy outcomes. However，when the bearing fault signal is weak，the fault characteristic frequencies will become blurry and difficulty to be found in SAM. To overcome its shortcoming，an enhanced spectral amplitude modulation（eSAM）is proposed to further enhance the fault related components，where unbiased autocorrelation（AC）of the squared envelope（SE）of modified signal，instead of SE，is used to generate SAM. The fundamental concept which motivates this proposed method is taking advantage of AC process to further reduce the level of uncorrelated random noise generated by the nonlinear filtering process and enhance the fault related peaks. This proposed method inherits the simplicity of SAM，and yields a more visible result. The effectiveness of the method is verified by a set of simulation signals，a set of gearbox bearing test signals and the test signals of axle box bearing of high-speed train under different operating conditions. The results show that this method can effectively reduce the influence of complex interference and realize the identification of rolling bearing fault characteristics.