發(fā)布時間：2019-03-26 11:12

【摘要】：常規(guī)基于配準補償方法因子孔徑損失和先驗信息失配問題,導(dǎo)致雜波距離依賴性和補償性能下降.為解決上述問題,將稀疏恢復(fù)算法引入到雜波距離依賴性補償當中,并對常規(guī)基于配準補償方法中各距離單元回波數(shù)據(jù)預(yù)處理過程加以改進,提出了一種基于稀疏恢復(fù)的穩(wěn)健距離配準補償方法——SRBC方法.該方法與常規(guī)基于配準補償方法相比,無需子孔徑平滑,不依賴于先驗知識,直接利用稀疏恢復(fù)得到超分辨的雜波空時譜,計算得出過渡協(xié)方差矩陣,再通過Capon譜重構(gòu)出雜波協(xié)方差矩陣.經(jīng)仿真驗證,SRBC方法不受先驗信息失配影響,不僅能夠?qū)崿F(xiàn)雜波距離依賴性的自適應(yīng)補償,在存在陣元誤差時的雜波抑制性能同樣較為穩(wěn)定.
[Abstract]:The problem of aperture loss and prior information mismatch based on the conventional registration compensation method results in clutter distance dependence and compensation performance degradation. In order to solve the above problems, sparse restoration algorithm is introduced into clutter distance dependence compensation, and the preprocessing process of echo data of each distance unit in the conventional registration-based compensation method is improved. A robust distance registration compensation method-SRBC method based on sparse restoration is proposed. Compared with the conventional registration-based compensation method, this method does not need sub-aperture smoothing and does not depend on prior knowledge. The super-resolution space-time spectrum of clutter is obtained directly by sparse restoration, and the transition covariance matrix is obtained by calculating the matrix of transition covariance. Then the clutter covariance matrix is reconstructed by Capon spectrum. Simulation results show that the SRBC method is not affected by prior information mismatch. It can not only compensate clutter distance dependence adaptively, but also stabilize clutter suppression performance in the presence of element errors.
【作者單位】： 空軍工程大學(xué)防空反導(dǎo)學(xué)院;空軍95100部隊;
【基金】：國家自然科學(xué)基金資助項目(6150010274)
【分類號】：TN959.73
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本文編號：2447488