一種新的時分多址信號射頻特征及其在特定輻射源識別中的應(yīng)用
doi: 10.11999/JEIT190163
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戰(zhàn)略支援部隊信息工程大學(xué)信息系統(tǒng)工程學(xué)院 鄭州 450001
基金項目: 國家自然科學(xué)基金(61401511, U1736107)
A Novel Radiometric Signature of Time-Division Multiple Access Signals and Its Application to Specific Emitter Identification
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Institute of Information System Engineering, Information Engineering University, Zhengzhou 450001, China
Funds: The National Natural Science Foundation of China (61401511, U1736107)
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摘要: 時分多址(TDMA)信號特定輻射源識別(SEI)的性能主要受限于突發(fā)數(shù)據(jù)的長度。為此,該文提出一種新的射頻特征,從載波相位上揭示了相鄰時隙的用戶是否相同,為相同用戶的數(shù)據(jù)累積提供了依據(jù)。該文首先分析了特征的產(chǎn)生機理,并給出了提取方法;根據(jù)特征的統(tǒng)計特性,推導(dǎo)了自適應(yīng)的判決門限,實現(xiàn)了相鄰時隙用戶身份的檢測;在此基礎(chǔ)上,設(shè)計了新的SEI處理流程,通過數(shù)據(jù)累積打破了每個時隙單獨識別的傳統(tǒng)思維。實驗結(jié)果表明:該特征對噪聲具備良好的魯棒性,能夠?qū)崿F(xiàn)相鄰時隙用戶身份的準(zhǔn)確檢測;與傳統(tǒng)做法相比,新的處理流程能夠有效改善TDMA信號SEI的性能。
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關(guān)鍵詞:
- 特定輻射源識別 /
- 時分多址信號 /
- 射頻特征 /
- 載波相位連續(xù)性
Abstract: For Time-Division Multiple Access (TDMA) signals, the performance of Specific Emitter Identification (SEI) is primarily limited by burst duration. To remedy this shortcoming, a novel radiometric signature is presented, which reveals whether the users of the adjacent time slots are the same from a perspective of carrier phase, thereby providing the basis for data accumulation of the same user. First, the feature mechanism is introduced, as well as the extraction method. Thereafter, user identity detection of the adjacent slots is implemented with an adaptive threshold, which is derived from the distribution of the signature. Finally, a new SEI processing procedure is designed with data accumulation, which breaks the routine of identifying only one slot at a time. Simulation results demonstrate that the proposed signature is resilient against the noise, and can accurately detect the user identity of the adjacent slots. Compared with the traditional processing procedure, the proposed one can effectively improve the SEI performance of TDMA signals. -
表 1 不同信噪比下的檢測性能
信噪比${{{E_S}} / {{N_0}}}$(dB) 判決門限$\gamma $ 檢測概率${P_{\rmq7j3ldu95}}$(%) 檢測正確率${P_{\rm{c}}}$(%) 10 0.0582 99.6723 97.2490 12 0.0467 99.6969 97.6732 14 0.0386 99.7077 98.0256 16 0.0336 99.7108 98.2951 18 0.0304 99.7369 98.4334 20 0.0285 99.7431 98.5184 22 0.0273 99.8092 98.6035 24 0.0266 99.8215 98.6404 下載: 導(dǎo)出CSV
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