本文選題：雷達(dá)通信一體化 + 信號識別��； 參考：《西安電子科技大學(xué)》2014年碩士論文

【摘要】：由于現(xiàn)代電子戰(zhàn)中各種電子設(shè)備的增多,雷達(dá)通信一體化設(shè)備是現(xiàn)在乃至將來的發(fā)展趨勢。雷達(dá)通信一體化信號兼具雷達(dá)信號和通信信號的特點,通過把通信信息調(diào)制到雷達(dá)信號載波上,利用雷達(dá)收發(fā)設(shè)備完成信號的發(fā)送和接收,再利用軟件無線電合成或分解雷達(dá)信號和通信信號。因此,雷達(dá)通信一體化不僅提高了通信信號的保密性和抗干擾能力,而且實現(xiàn)了雷達(dá)和通信系統(tǒng)的自動化和網(wǎng)絡(luò)化。本文針對目前雷達(dá)信號識別研究中存在的技術(shù)性問題,對現(xiàn)有雷達(dá)信號識別中的關(guān)鍵算法進(jìn)行了改進(jìn),并結(jié)合雷達(dá)通信一體化信號的特征,對雷達(dá)信號和通信信號的識別進(jìn)行了研究。具體研究內(nèi)容介紹如下:1.在電子偵察中,脈沖信號重頻模式的識別是在分選后進(jìn)行的,而分選結(jié)果的好壞直接決定了重頻模式識別的準(zhǔn)確度。由于諧波干擾和參數(shù)測量的偏差問題,分選后的脈沖信號存在不同比例的寄生脈沖,而目前重頻模式識別算法對存在寄生脈沖的情況識別率都不高。因此,針對雷達(dá)信號典型的六種重頻模式,本文提出了一種基于符號法識別重頻模式的方法。通過把PRI序列和DPRI序列符號化,并對符號化后的序列進(jìn)行編碼,從編碼序列中提取出四個特征參數(shù),分別為F、H、C和P,四個參數(shù)分別與對應(yīng)門限值比較,進(jìn)而識別六種重頻模式。仿真結(jié)果表明:在寄生脈沖所占比例從0~20%的情況下,對六種重頻模式均有高達(dá)95%以上的識別率。2.現(xiàn)代新體制雷達(dá)信號具有強(qiáng)穩(wěn)定性的特點,即相參性。目前,相參性識別方法中抗噪聲性能最好的為時域自相關(guān)法,但該方法只能從圖像上識別相參信號,不能實現(xiàn)識別自動化,為此,本文提出了改進(jìn)時域自相關(guān)法。通過改進(jìn)延遲器,實現(xiàn)了對非固定重頻信號的處理;通過把經(jīng)過濾波的脈沖信號符號化并編碼,并利用統(tǒng)計學(xué)中的平均自信息量從編碼序列中提取H1參數(shù),進(jìn)而區(qū)分相參信號和非相參信號。本文在重頻模式分別為固定重頻和上滑變重頻,以及脈內(nèi)調(diào)制方式分別為單一正弦波調(diào)制和線性調(diào)頻的情況下做了對比實驗,仿真結(jié)果表明:在不同的重頻模式和脈內(nèi)調(diào)制類型條件下,當(dāng)信噪比大于等于5dB時,對相參信號和非相參信號的識別率高達(dá)95%以上。3.雷達(dá)信號和通信信號最本質(zhì)的區(qū)別是脈內(nèi)調(diào)制方式不同。本文選用的雷達(dá)信號調(diào)制類型為單一正弦波調(diào)制、線性調(diào)頻、正弦調(diào)頻和4PSK調(diào)制,并選用調(diào)制方式為MSK的通信信號進(jìn)行研究。經(jīng)過研究,修正了快速離散分階數(shù)傅立葉變換,并提出了一種基于分階數(shù)傅立葉變換的脈內(nèi)調(diào)制類型識別方法。信號經(jīng)FRFT變換可以得到p-v曲線,并從中提取H2和H3參數(shù),經(jīng)門限比較可以實現(xiàn)自動化識別。仿真結(jié)果表明:在高斯白噪聲下,當(dāng)信噪比大于等于5dB時,對五種脈內(nèi)調(diào)制方式有高達(dá)95%以上的識別率。
[Abstract]:Due to the increase of various electronic equipments in modern electronic warfare, radar communication integration equipment is the development trend now and even in the future. The integrated radar communication signal has the characteristics of both radar signal and communication signal. By modulating the communication information onto the radar signal carrier, the radar transceiver equipment is used to transmit and receive the signal. Then software radio is used to synthesize or decompose radar signal and communication signal. Therefore, the integration of radar communication not only improves the confidentiality and anti-jamming ability of communication signal, but also realizes the automation and networking of radar and communication system. Aiming at the technical problems existing in the research of radar signal recognition, this paper improves the key algorithms of radar signal recognition, and combines the characteristics of radar communication integrated signal. The recognition of radar signal and communication signal is studied. The specific contents of the study are as follows: 1: 1. In electronic reconnaissance, the recognition of repetition mode of pulse signal is carried out after sorting, and the accuracy of pattern recognition of repetition frequency is directly determined by the result of sorting. Because of the problem of harmonic interference and the deviation of parameter measurement, there are different proportion of parasitic pulse in the separated pulse signal, but the recognition rate of the current repetition pattern recognition algorithm for the case of parasitic pulse is not high. Therefore, aiming at the six typical repetition modes of radar signal, this paper presents a method based on symbol method to identify the repetition mode. By symbolizing the PRI sequence and the DPRI sequence, and coding the symbolized sequence, four characteristic parameters are extracted from the coded sequence, namely, FG Heng C and P respectively. The four parameters are compared with the corresponding threshold values respectively, and six repetition modes are identified. The simulation results show that when the proportion of parasitic pulses is from 0 to 20%, the recognition rate of more than 95% is obtained for all the six repetition modes. The radar signal of modern new system has strong stability, namely coherence. At present, the best anti-noise method is time-domain autocorrelation method, but this method can only recognize coherent signals from images, so it can not realize automatic recognition. Therefore, an improved time-domain autocorrelation method is proposed in this paper. By improving the delayer, the processing of the unfixed repetition signal is realized, the filtered pulse signal is symbolized and encoded, and the H1 parameter is extracted from the coding sequence by using the average self-information in statistics. Then the coherent signal and the non-coherent signal are distinguished. In this paper, a comparative experiment is made under the condition that the repetition mode is fixed repetition frequency and the up-slip variable repetition frequency, and the intra-pulse modulation mode is single sine wave modulation and linear frequency modulation, respectively. The simulation results show that the recognition rate of coherent and non-coherent signals is over 95% when SNR is greater than or equal to 5dB under different repetition modes and intra-pulse modulation types. The essential difference between radar signal and communication signal is that the modulation mode is different. In this paper, the modulation types of radar signal are single sine wave modulation, linear frequency modulation, sine frequency modulation and 4PSK modulation, and the communication signal with MSK modulation is studied. The fast discrete fractional Fourier transform (FFT) is modified, and a method of intra-pulse modulation type recognition based on split-order Fourier transform is proposed. The p-v curve can be obtained by FRFT transformation, and the H _ 2 and H _ 3 parameters can be extracted from the p-v curve. The simulation results show that when the SNR is greater than or equal to 5dB under Gao Si white noise, the recognition rate of the five intra-pulse modulation schemes is up to 95%.
【學(xué)位授予單位】：西安電子科技大學(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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