The equipment layout optimization of a UAV (Unmanned Aerial Vehicle) radar cabin can decrease cable length in order to promote the quality of radar and UAV system. Model-based Systems Engineering (MBSE) is widely used for UAV development, particularly for the layout design of UAV radar cabin. In this paper, a semantic modeling approach based on KARMA language is proposed to create the system model of the radar cabin layout based on an MBSE approach for formalizing Requirement, Function, Logical and Physical structure (RFLP). Moreover, the KARMA models for UAV radar cabin layout modeling are transformed to the Genetic Algorithm (GA) in MATLAB toolkit for radar cabin layout optimization by code generation. Based on the layout information generated from the KARMA models, the optimized layout solution is generated by the MATLAB toolkit. From the case study, we find the KARMA language enables to formalize the radar cabin design based on nine diagrams of SysML specification. And optimizations can be executed automatically after getting data generated from KARMA models. Thereby, the proposed semantic modeling approach improves design efficiency and quality during radar cabin design.