There are several instruments and methods to retrieve the atmospheric Mixing Layer Height (MLH). However, none of these instruments or methods can measure the development of the MLH under all atmospheric conditions. For example, aerosol signatures measured by backscatter lidars can be used to determine the MLH but this approach is reasonable only when the atmosphere is well-mixed. Microwave Radiometer (MWR) derived profiles have low vertical resolution and cannot resolve fine structures in the boundary layer, especially, at higher altitudes. Here we propose a method which combines data from a ground-based lidar and a MWR, in simulated as well as real measurements scenarios, to overcome these limitations. The method works by fitting an erf-like transition model function to the section of range-corrected lidar backscatter signal. The section of the lidar backscatter signal for fitting the model function is obtained by incorporating the MWR estimates of MLH along with their uncertainties. The fitting is achieved by using an extended Kalman filter (EKF). The proposed approach, by exploiting the synergy between the two instruments, enables to detect MLH with original vertical and temporal resolutions. Test cases combining simulated data for a co-located lidar-ceilometer and a MWR are presented. The simulated data is obtained from the Dutch Atmospheric Large Eddy Simulation (DALES) model for boundary layer studies. Doppler wind lidar along with radiosondes (whenever available) data is used to assess the quality of the synergetic MLH estimates. Data from the HD(CP)2 Observational Prototype Experiment (HOPE) campaign at Jülich, Germany is used to test the proposed method.