Comparative Analysis of Statistical Characteristics between Bi-SAR Images and Mon-SAR Images

The transmitter and receiver of bistatic SAR (Synthetic Aperture Radar) are placed on two different carrier platforms, which provide higher flexibility and have become one of the research hotspots in the field of SAR. Compared to monostatic SAR, bistatic SAR has many unique advantages. Due to the misalignment of the bistatic SAR transmitter and receiver, there are differences in imaging results between bistatic SAR and monostatic SAR. SAR image interpretation is key to the application of SAR images, and accurately describing the characteristics of SAR images is a prerequisite for effectively understanding SAR images. In order to observe the differences in statistical characteristics between the two, in this paper, we use statistical modeling methods to compare and analyze the texture characteristics of SAR images. Firstly, some texture SAR images were selected, and then the generalized Gamma distribution model from the empirical model was used to statistically model the bistatic SAR and monostatic SAR images. The parameter decoupling method was used to effectively estimate the model parameters. Finally, the local variation coefficient, which describes scene heterogeneity, was calculated to measure the texture information of the images. By processing the measured data, we found that, for the same imaging scene, monostatic SAR imaging results have stronger texture information compared to bistatic SAR. This article analyzes the differences in image characteristics between bistatic SAR and monostatic SAR from the perspective of statistical characteristics, laying the foundation for SAR image interpretation and target recognition.