文章摘要
王宏磊,马远良.一种检测低信噪比下未知波形时变相干信号的方法*[J].,2019,38(4):477-483
一种检测低信噪比下未知波形时变相干信号的方法*
A method for detection of low SNR signals with unknown and variant waveforms
投稿时间:2019-04-19  修订日期:2019-07-01
中文摘要:
      从获取的数据中检测目标信号,是雷达、声呐等领域重要的研究内容。时频域严重畸变的回波信号以及时变线谱信号的自适应检测,具有重要意义。为了挖掘和推广自适应相干累积(Adaptive Coherent Integration,ACI)技术在未知时变信号检测领域的能力,本文给出了ACI算法的基本原理,并进行了系统性地理论推导,得到了ACI算法的宽带时变自回归滑动平均模型(ARMA)和窄带复解析模型。利用这些模型解释了产生信号相干累积的机理,分析得出了产生相干累积的条件,揭示了这种时变系统的许多奇异特性。结合仿真实验和实际海上实验数据对ACI算法展开验证,结果表明ACI算法对于低信噪比下未知波形信号具有优异的检测能力,展示出ACI算法在水下探测等相关领域存在广泛的实际应用前景。
英文摘要:
      Detection of targets’ signal from acquired data is an important research content in radar, sonar and other signal processing fields. The adaptive signal processing techniques have high practical application values due to the characteristic that no/less prior knowledge of signal is required. The adaptive detections of echo signals seriously distorted in time frequency domain and line spectrum varied in time are of great significance. In order to exploring and extending the ability of Adaptive Coherent Integration (ACI) in unknown time-varying signal detection, the fundamental theory of ACI algorithm is presented in this paper. Broadband time-varying autoregressive moving average (ARMA) model and narrow-band complex analytic model of ACI are theoretically deduced. The mechanism of signal coherent integration is explained by using these models. At the same time, the conditions of signal coherent integration are analyzed and presented. In the process of analysis, some unique characteristics of ACI are discussed. Finally, the performance of ACI algorithm is verified by computer simulations and experiment data on the sea. The results show that ACI algorithm has excellent detection ability for signals with unknown waveform under low signal to noise ratio. The studies in this paper show that ACI algorithm has a wide application prospect in underwater detection and other similar fields.
DOI:10.11684/j.issn.1000-310X.2019.04.002
中文关键词: 自适应相干累积,ARMA模型,窄带复解析模型,低信噪比
英文关键词: Adaptive Coherent Integration, ARMA model, Narrow-band complex analytic model, Low signal to noise ratio
基金项目:国家自然科学基金项目
作者单位E-mail
王宏磊 西北工业大学 wanghonglei@nwpu.edu.cn 
马远良 西北工业大学 ylma@nwpu.edu.cn 
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