本文關(guān)鍵詞：低截獲概率雷達(dá)信號的時頻分析　出處：《南京理工大學(xué)》2014年碩士論文　論文類型：學(xué)位論文

  更多相關(guān)文章： 低截獲概率 參數(shù)提取 時頻分布 WVD CWD 信源熵

【摘要】：低截獲概率(Low Probability of Intercept, LPI)雷達(dá)具有低峰值功率、大時寬帶寬積等出眾優(yōu)點,這導(dǎo)致傳統(tǒng)截獲接收機(jī)難以檢測LPI雷達(dá)信號；同時LPI雷達(dá)多采用復(fù)雜信號調(diào)制方式,這也使得大部分傳統(tǒng)信號參數(shù)估計算法的性能嚴(yán)重下降甚至失效。本文從LPI技術(shù)原理著手,對多個經(jīng)典LPI雷達(dá)信號進(jìn)行了性能分析,重點結(jié)合LPI信號的非平穩(wěn)特點,詳細(xì)研究了時頻分布算法對LPI雷達(dá)信號進(jìn)行檢測及參數(shù)估計的性能,并對算法進(jìn)行性能優(yōu)化。主要研究內(nèi)容包括： 1)研究了LPI原理及技術(shù),并結(jié)合截獲因子概念詳細(xì)分析了LPI雷達(dá)的工作原理；從時域、頻域以及模糊函數(shù)等角度對多種典型LPI雷達(dá)信號進(jìn)行了詳細(xì)的仿真分析。 2)研究了時頻分布中的魏格納-威爾分布(Wigner-Ville Distribution, WVD)及偽魏格納-威爾分布(Pseudo Wigner-Ville Distribution, PWVD)推導(dǎo)了交叉項表示形式并分析了時頻聚集性。不同噪聲環(huán)境下,運(yùn)用PWVD對各LPI信號進(jìn)行仿真,仿真結(jié)果表明該算法具有很好的時頻聚集性,但存在嚴(yán)重交叉項影響,降低了算法的整體性能。 3)針對WVD中交叉項過大的問題,采用喬-威廉姆斯分布(Choi-Williams Distribution, CWD)對各LPI信號進(jìn)行分析及調(diào)制參數(shù)提取,仿真結(jié)果表明雖然交叉項得到了很好地抑制,但其時頻聚集性發(fā)生明顯惡化,嚴(yán)重降低了參數(shù)提取的精度。 4)針對交叉項過大或時頻聚集性惡化的問題,提出采用信源熵對CWD進(jìn)行參數(shù)優(yōu)化的方法。首先討論了該優(yōu)化算法的原理,給出了具體實施步驟框圖,并通過仿真得到所需優(yōu)化參數(shù)；其次,采用優(yōu)化后的CWD對各LPI信號進(jìn)行仿真,仿真結(jié)果表明優(yōu)化后CWD具有更優(yōu)秀的性能,不但很好地抑制住了交叉項幅度,在時頻聚集性方面也具有遠(yuǎn)好于一般CWD的表現(xiàn),顯著提高了參數(shù)提取的精度。
[Abstract]:Low Probability of Intercept (LPI) radar has the advantages of low peak power, large time broadband wide product and so on. This makes it difficult for traditional interceptor to detect LPI radar signal. At the same time, most of LPI radar adopt complex signal modulation, which makes the performance of most traditional signal parameter estimation algorithm seriously decline or even fail. This paper starts with the principle of LPI technology. The performance of several classical LPI radar signals is analyzed, and the performance of time-frequency distribution algorithm for LPI radar signal detection and parameter estimation is studied in detail in combination with the non-stationary characteristics of LPI signal. And the performance optimization of the algorithm is carried out. The main research contents include: 1) the principle and technology of LPI are studied, and the working principle of LPI radar is analyzed in detail with the concept of interception factor. In this paper, several typical LPI radar signals are simulated and analyzed in time domain, frequency domain and ambiguity function. 2) Wigner-Ville Distribution in time-frequency distribution is studied. WVD) and pseudo Wigner-Ville Distribution. PWVD is used to simulate the LPI signals in different noise environments. The simulation results show that the algorithm has good time-frequency aggregation, but there are serious cross-term effects, which reduces the overall performance of the algorithm. 3) aiming at the problem of excessive cross term in WVD, Choi-Williams Distribution is adopted. LPI signals were analyzed and modulation parameters were extracted. The simulation results show that although the crossover term is well suppressed, the time-frequency aggregation is obviously deteriorated. The precision of parameter extraction is seriously reduced. 4) aiming at the problem of excessive crossover or aggravation of time-frequency aggregation, a method for parameter optimization of CWD using source entropy is proposed. Firstly, the principle of the optimization algorithm is discussed, and the block diagram of concrete implementation steps is given. The optimal parameters are obtained by simulation. Secondly, the optimized CWD is used to simulate the LPI signals. The simulation results show that the optimized CWD has better performance, and not only suppress the amplitude of crossover terms well. In the aspect of time-frequency aggregation, the performance of CWD is much better than that of general CWD, and the precision of parameter extraction is improved significantly.
【學(xué)位授予單位】：南京理工大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2014
【分類號】：TN957.51

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