本文選題：兵器科學(xué)與技術(shù) + 輻射源識別��； 參考：《兵工學(xué)報(bào)》2017年08期

【摘要】：針對協(xié)同偵察數(shù)據(jù)級融合識別中通信量大的問題,利用壓縮感知可用少量測量值表征完整信號的特點(diǎn),提出了一種基于壓縮感知的數(shù)據(jù)級融合識別方法。接收終端采用確定測量陣對偵察信號的Gabor時(shí)頻特征進(jìn)行壓縮測量,通過傳輸少量的壓縮測量值以減輕通信壓力,融合中心根據(jù)多源測量數(shù)據(jù)間的相關(guān)特性,采取相關(guān)性融合規(guī)則直接對多源壓縮測量數(shù)據(jù)進(jìn)行融合,最后再計(jì)算融合壓縮測量值在不同類信號字典下的重構(gòu)誤差,最小重構(gòu)誤差對應(yīng)的信號類別即識別結(jié)果。分別對融合識別方法識別性能和相關(guān)性融合規(guī)則融合效果進(jìn)行仿真分析,實(shí)驗(yàn)結(jié)果表明:所提方法在保證識別率的同時(shí)大幅減小了數(shù)據(jù)通信代價(jià),在低信噪比時(shí)識別性能突出、抗噪聲干擾性能好;相比于其他融合規(guī)則,基于測量向量相關(guān)性的融合規(guī)則可保留更為全面的信息。
[Abstract]:Aiming at the problem of large traffic in data level fusion recognition of cooperative reconnaissance, a data level fusion recognition method based on compressed sensing is proposed, in which a small number of measurements can be used to represent the complete signal. The receiving terminal uses a certain measurement array to compress and measure the Gabor time-frequency characteristics of the reconnaissance signal. By transmitting a small amount of compressed measurement values to reduce the communication pressure, the fusion center is based on the correlation characteristics between the multi-source measurement data. The correlation fusion rule is adopted to fuse the multi-source compression measurement data directly. Finally, the reconstruction error of the fusion compression measurement value in different kinds of signal dictionaries is calculated. The category of the signal corresponding to the minimum reconstruction error is the recognition result. The performance of fusion recognition method and the fusion effect of correlation fusion rules are simulated and analyzed respectively. The experimental results show that the proposed method can greatly reduce the cost of data communication while ensuring the recognition rate, and the performance of the proposed method is outstanding when the signal-to-noise ratio is low. Compared with other fusion rules, the fusion rules based on measurement vector correlation can retain more comprehensive information.
【作者單位】： 空軍工程大學(xué)航空航天工程學(xué)院;
【基金】：航空科學(xué)基金項(xiàng)目(20152096019)
【分類號】：TN971

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本文編號：1904031