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作 者:张涛[1] ZHANG Tao(School of Intelligent Manufacturing,HuaiNan Union University,Huainan Anhui 232038,China)
机构地区:[1]淮南联合大学智能制造学院,安徽淮南232038
出 处:《重庆科技大学学报(自然科学版)》2024年第4期124-130,共7页Journal of Chongqing University of Science and Technology(Natural Sciences Edition)
基 金:安徽省高校优秀拔尖人才培训项目“高校优秀青年骨干人才国内访学研修项目”(GXGNFX2022128);淮南联合大学创新团队项目“新型雷达信息处理技术创新团队”(LCX2302)。
摘 要:在弱信噪比场景下,目标回波信号往往非常微弱,难以被雷达探测到,其中包含的一些重要信息更难被识别。因此,需要采取有效措施来发掘受噪声影响较大的弱信噪比目标。研究采用组网雷达回波数据时空同步融合技术,将多组雷达回波信息时频对齐叠加处理。通过单类信号仿真测试,在同等条件下,叠加信号中能有效发掘出普通雷达无法准确识别的目标,采用多类雷达信号混合测试,该方法依然适用。实验证实该方法识别目标效果好、适应范围广,可以拓展到其他雷达信号处理领域,为雷达信号处理提供一种新的思路。The target echo signals are often very weak in low signal-to-noise(SNR)ratio scenarios and it is difficult for radar to detect the signals,which includes some important information that are more difficult to identify.Therefore,effective measures are adopted to explore weak SNR targets affected by noise.This study uses the technique of time-space synchronization fusion of networked radar echo data to align and superimpose multiple sets of radar echo information in time and frequency.Through single class signal simulation testing,under the same conditions,targets that ordinary radars cannot accurately identify can be effectively recognized through the superposition signal.This method is still applicable through mixed testing of multiple types of radar signals.Experiments prove that this method is effective and has a wide range of adaptability,which can be extended to other fields of radar signal processing and provide a new approach for radar signal processing.
分 类 号:TN957.51[电子电信—信号与信息处理]
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