本文選題：信息處理技術(shù) + 波達(dá)方向估計(jì)��； 參考：《吉林大學(xué)學(xué)報(bào)(工學(xué)版)》2017年01期

【摘要】：為了高效、準(zhǔn)確地估計(jì)相干信號(hào)的波達(dá)方向(DOA),提出了一種基于特征空間多重信號(hào)分類(MUSIC)算法的空間平滑估計(jì)方法。首先對(duì)相干信號(hào)進(jìn)行空間平滑處理,然后對(duì)其應(yīng)用特征空間MUSIC算法進(jìn)行DOA的精確估計(jì),使其最大限度地利用信號(hào)子空間和噪聲子空間的信息。本文方法并不影響非相關(guān)信號(hào)存在時(shí)DOA的估計(jì),且還可以對(duì)信號(hào)源功率進(jìn)行有效的估計(jì),以提高對(duì)小能量信號(hào)的成功估計(jì)概率。與傳統(tǒng)空間平滑算法及修正MUSIC算法相比,本文方法具有更低的信噪比門(mén)限和更高的估計(jì)精度及分辨力。最后的仿真實(shí)驗(yàn)驗(yàn)證了本文方法的有效性和魯棒性。
[Abstract]:In order to estimate the DOA of coherent signals efficiently and accurately, a spatial smoothing estimation method based on feature space multi-multiple signal classification algorithm (MUSIC-based) is proposed. Firstly, the coherent signal is processed by spatial smoothing, and then the DOA is estimated accurately by using the eigenspace MUSIC algorithm to maximize the use of the information of the signal subspace and the noise subspace. The proposed method does not affect the estimation of DOA in the presence of non-correlated signals, and it can also effectively estimate the power of the signal source so as to improve the probability of successful estimation of small energy signals. Compared with the traditional spatial smoothing algorithm and the modified MUSIC algorithm, the proposed method has lower SNR threshold, higher estimation accuracy and higher resolution. Finally, the simulation results show the effectiveness and robustness of the proposed method.
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本文編號(hào)：1824203