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Abstract
Deception is an effective means of jamming against synthetic aperture radar (SAR). The performance of deceptive jamming is affected by the accuracy of parameter measurement and the applied antijamming methods of SAR. In this article, we analyze the accuracy of current deceptive jamming evaluation indicators, propose a new method for evaluating the performance of deceptive jamming based on the combination of typical dominant deceptive jamming evaluation indicators, and recessive indicators extracted by convolutional neural networks, and obtain a level of deceptive jamming using a softmax activation function in a fully connected network. Deceptive jamming images affected by the SAR motion parameter measurement error are taken as training and test sets. Finally, the moving and stationary target acquisition and recognition database is used as a deceptive jamming template in order to verify the effectiveness of the proposed method.
Highlights
S YNTHETIC aperture radar (SAR) is widely used in military and civilian applications, such as target classification, identification, and detection due to its high resolution at all times of day and in all types of weather [1]
The performance evaluation of deceptive jamming (PEoDJ) against synthetic aperture radar (SAR) is useful for testing, upgrading, and combatting electronic countermeasure (ECM) methods and equipment [4]–[8], there have been relatively few studies of the PEoDJ
In order to evaluate the performance of deceptive jamming, the imaging characteristics of SAR can simultaneously utilize three aspects of indicators: the data domain, such as the signalto-jamming ratio, and information loss ratio [18]; the scatterer target domain, such as the integral sidelobe ratio, peak sidelobe ratio, and impulse response width [22], [23]; and the scene target domain, such as image mean, image variance, Euclidean distance [24], equivalent number of looks (ENL) [25], correlation coefficient [25]–[27], dynamic range, image entropy [28], [29], and structural similarity (SSIM) [30], [31]
Summary
S YNTHETIC aperture radar (SAR) is widely used in military and civilian applications, such as target classification, identification, and detection due to its high resolution at all times of day and in all types of weather [1]. In order to evaluate the performance of deceptive jamming, the imaging characteristics of SAR can simultaneously utilize three aspects of indicators: the data domain, such as the signalto-jamming ratio, and information loss ratio [18]; the scatterer target domain, such as the integral sidelobe ratio, peak sidelobe ratio, and impulse response width [22], [23]; and the scene target domain, such as image mean, image variance, Euclidean distance [24], equivalent number of looks (ENL) [25], correlation coefficient [25]–[27], dynamic range, image entropy [28], [29], and structural similarity (SSIM) [30], [31] These indicators are limited in practical application because they only focus on the variation of a single image and cannot directly judge the performance of a jamming method.
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