A Novel Model for Analyzing the Statistical Properties of Targets’ RCS

The statistical distribution of radar cross-section (RCS) of complex targets varies for different attitude angles and may even behave as a bimodal distribution. Classical distribution models are unable to fully and accurately characterize the fluctuation properties of RCS in radar targets. In this letter, we present a novel distribution model for describing and analyzing the statistical properties of dynamic RCS. We used RCS statistical data for different attitude angle ranges and performed comparative analysis with Gaussian mixture density models (GMDM) (the second-order GMDM and the third-order GMDM). To evaluate the effectiveness and performance of our proposed method, we calculated various evaluation indicators of the three models. The results suggest that the proposed model has better fitting effect and higher fitting accuracy than the second-order GMDM. Simultaneously, although its performance on the backward RCS data is slightly inferior to that of the third-order GMD, our model requires fewer parameters. So, the model can be more suitable for describing the fluctuation characteristics of dynamic RCS of radar targets. The findings are useful in the detection of radar targets and provide an alternative for improving the total performance of radar.