This paper presents a high-fidelity inhomogeneous ground clutter simulation method for airborne phased array Pulse Doppler (PD) radar aided by a digital elevation model (DEM) and digital land classification data (DLCD). The method starts by extracting the basic geographic information of the Earth’s surface scattering points from the DEM data, then reads the Earth’s surface classification codes of Earth’s surface scattering points according to the DLCD. After determining the landform types, different backscattering coefficient models are selected to calculate the backscattering coefficient of each Earth surface scattering point. Finally, the high-fidelity inhomogeneous ground clutter simulation of airborne phased array PD radar is realized based on the Ward model. The simulation results show that the classifications of landform types obtained by the proposed method are more abundant, and the ground clutter simulated by different backscattering coefficient models is more real and effective.

To suppress non-stationary main-lobe interference, we utilized the waveform information of the transmitted signal and proposed an interference suppression method based on a multi-polarized array without the need for calculating the target parameters. This method calculates the steering vector of the target through matched filtering. Additionally, for non-stationary interference whose statistical characteristics change over time, we extract high-energy frequency points from the time–frequency joint domain to obtain the time–frequency covariance matrix for subsequent beamforming. Simulation experiments demonstrate that this method leverages the signal polarization information sensed by the multi-polarized array, effectively suppressing non-stationary main-lobe interference in the polarization domain. This method does not require estimation of the target’s polarization parameters and is more suitable for real-world detection scenarios where the waveform is known.