A Multi-Feature Fusion Performance Evaluation Method for SAR Deception Jamming

Due to inaccurate reconnaissance parameters of the jammer and the decline in equipment performance over long-term usage, the false targets generated by the jammer usually have problems such as defocusing, abnormal brightness, and distortion, which fail to reach the ideal state. Therefore, experts or specialized assessment methods are needed to evaluate the interference effect. However, the human eye is not sensitive to minor changes. In such cases, the results obtained by some evaluation methods may be inconsistent with expert judgments. Therefore, this paper proposes an evaluation method that integrates three features of image edge information, brightness variation, and texture structure. This method mainly achieves two purposes: (1) Maintain a high evaluation effect when the image error does not change significantly, and be consistent with the expert’s judgment. (2) When the image error changes significantly, it can conduct effective effect evaluation like other methods, and has stronger universality and robustness. Furthermore, its robustness is reflected in the ability to reliably evaluate even in the presence of severe image distortion, without relying on geometric correction. Simulation experiments are conducted under three error conditions, and result comparisons verify the advantages and robustness of the proposed method. Finally, the effectiveness of proposed method is verified using real jamming data.