Performance prediction of SAR noise jamming using NIIRS

Fanghe Lu; Jie Huang; Jiantao Wang

doi:10.1117/12.2634425

12 May 2022 Performance prediction of SAR noise jamming using NIIRS

Fanghe Lu, Jie Huang, Jiantao Wang

Proceedings Volume 12173, International Conference on Optics and Machine Vision (ICOMV 2022); 121730J (2022) https://doi.org/10.1117/12.2634425
Event: International Conference on Optics and Machine Vision (ICOMV 2022), 2022, Guangzhou, China

Abstract

The methods of synthetic aperture radar (SAR) jamming effect evaluation is a current research hotspot in the field of electronic countermeasures. Aiming at the problem that the existing SAR jamming evaluation techniques are only applicable to cooperative jamming effect evaluation and cannot provide real-time guidance to the jamming strategy of jammers on the battlefield. Our paper proposes a model which can predict the effect of SAR noise barrage jamming based on the image subjective evaluation standard—the National Image Interpretability Rating Scale (NIIRS). Two factors with the most significant impact on NIIRS, SAR image resolution and jamming-to-signal ratio, are selected as the independent variables of the model. This model not only enables the prediction of jamming effect, but also reflects the jamming effect to the loss of image interpretability directly. Experimentally, this model is fitted with a large amount of SAR image data, and the R2 is 0.91, RMSE is 0.41.

Citation Download Citation

Fanghe Lu, Jie Huang, and Jiantao Wang "Performance prediction of SAR noise jamming using NIIRS", Proc. SPIE 12173, International Conference on Optics and Machine Vision (ICOMV 2022), 121730J (12 May 2022); https://doi.org/10.1117/12.2634425

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