This paper focuses on the analysis and design of Multi-aspect SAR(MuSAR) system for Compressive sensing-based(CS-based) 3D imaging. For this purpose,the Point ambiguous function(PAF) is proposed to analyze the factors that dominate the Mutual coherence(MC) of MuSAR sensing matrix. The PAF contacts with the parameters and configuration of MuSAR system directly and is easy to manipulate. With PAF, the present study analyzes the factors that dominate the performance of CS-based MuSAR 3D imaging. First of all, the stochastic waveform is an excellent selection. Second, the angular-frequency-diversity can improve the robustness of3 D imaging. Finally, the finer sampling of received data could improve the robustness of MuSAR 3D imaging. Simulation experiments show the validity of conclusion. This paper focuses on the analysis and design of Multi-aspect SAR (MuSAR) system for Compressive sensing-based 3D imaging. For this purpose, the Point ambiguous function (PAF) is proposed to analyze the factors that dominate the The PAF contacts with the parameters and configuration of MuSAR system directly and is easy to manipulate. With PAF, the present study that factors that dominate the performance of CS-based MuSAR 3D imaging. First of all, the stochastic waveform is an excellent selection. Second, the angular-frequency-diversity can improve the robustness of3 D imaging. Finally, the finer sampling of received data could improve the robustness of MuSAR 3D imaging. Simulation experiments show the validity of conclusion.