| 摘要: |
| 间歇采样转发干扰（Interrupted Sampling Jamming, ISJ）运用范围广泛，对雷达目标跟踪、识别等工作带来了巨大挑战。对间歇采样转发干扰的参数估计和重构是其中的关键和难点问题。本文针对目前的间歇采样转发干扰对抗方法难以在强噪声环境下快速有效实现的问题，提出采用分段信息熵（Shannon Entropy, ShEn）对间歇采样转发干扰的转发周期和切片宽度关键参数进行估计，采用分段脉冲压缩（Pulse Compression, PC）判断干扰类型和转发次数，最终重构干扰。通过分段，可将每个分段看作是包含干扰和不包含干扰两种类型，采用信息熵作为干扰的判决依据，计算出间歇采样转发干扰的参数，并在已知参数基础上，分别对各个干扰段进行脉冲压缩，可以判断信号段与干扰段的关系，进而重构出干扰，并实现干扰的抑制。仿真结果证明了该方法的可行性和有效性。 |
| 关键词: 间歇采样转发干扰 信息熵 脉冲压缩 参数估计 |
| DOI：DOI:10.3969/j.issn.1672-2337.2023.03.004 |
| 分类号:TN973.3 |
| 基金项目:国防科技大学科研项目（No.ZK22?46）； 国家自然科学基金（No.61890541， 61890542， 62071475） |
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| Interrupted Sampling Jamming Suppression Based on Piecewise Pulse Compression and Shannon Entropy |
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LIU Mengfei， CHEN Jiyuan， PAN Xiaoyi， ZHAO Feng
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College of Electronic Science and Technology, National University of Defense Technology, Changsha 410073, China
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| Abstract: |
| IInterrupted sampling jamming has found wide applications, bringing great challenges to target tracking and recognition. The parameter estimation and reconstruction of the jamming is the key and difficulty at present. Aiming at the problem that current methods are difficult to reject the jamming especially in strong noise, this paper proposes to estimate the key parameters of the jamming including transmitting period and width of jamming slice with Shannon entropy. Then the type of jamming and forwarding times is identified by pulse compression. Finally, the jamming is reconstructed. The echo is divided into the segment including jamming and the segment without jamming by segmentation. Shannon entropy can identify the difference and estimate the parameters of the jamming. On the basis of known parameters, pulse compression of each segment including jamming can identify the relationship between the segment including jamming and the segment without jamming. After recognition, the factors for constructing jamming are complete and the jamming is suppressed. The simulation results prove the feasibility and effectiveness of the proposed method. |
| Key words: interrupted sampling jamming Shannon entropy pulse compression parameter estimation |
