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標題: | 結合張量分析應用於解決非理想環境下的多輸入多輸出雷達之強健性波束成型技術 Robust Beamforming Based on Tensor Analysis for MIMO Radar under Mismatched Scenarios |
作者: | Wei-Chi Lee 李瑋琦 |
指導教授: | 李枝宏(Ju-Hong Lee) |
關鍵字: | 張量分析,干擾加雜訊自相關矩陣,多輸入多輸出雷達,信號角度誤差,元件位置擾動,交耦合現象,信號射散現象, tensor analysis,interference plus noise covariance matrix,MIMO radar,signal angle error,element position error,mutual coupling,signal scattering, |
出版年 : | 2020 |
學位: | 碩士 |
摘要: | 本篇論文結合張量分析方法與本實驗室先前所提出之極小極大方法並配合文獻中干擾加雜訊自相關矩陣重建概念,運用於多輸入多輸出雷達系統波束成型中。以提升系統對於多重誤差情境下的強健性。在非理想環境中,包括預設信號角度與實際信號角度不匹配之信號角度誤差、由於天線安裝或受於外力而產生的元件位置擾動、天線間相互電磁影響而產生之天線交耦合現象、天線間相互不匹配導致對於接收信號之增益(Gain)與相位(Phase)存在誤差、信號於傳送路徑所產生信號射散現象。這些誤差是有機會同時並存的。因此發展多重誤差環境下的強健性演算法是更符合現實環境中所應用的情境。 而透過本論文所提出之演算法,將接收到的資料向量透過張量分析所得之信號方向向量透過極小極大方法進行更精確之估計,並配合干擾加雜訊自相關矩陣重建。除了對於多重誤差情境提供了良好的強健性外,當欲接收信號功率增大時,可以避免系統將欲接收信號視為干擾一併消除之情形,大幅增加了此強健性波束成型演算法的泛用性。 This thesis deals with the robust adaptive beamforming of MIMO radar systems in the presence of multiple mismatch scenarios. In order to improve the system's robustness against multiple error scenarios. We combine the tensor analysis with the minimax method which previously proposed by our laboratory, and utilize the concept of interference plus noise covariance matrix reconstruction presented in the literature. The multiple error scenarios include signal angle error that the presumed signal angle doesn’t match to the actual signal angle, the element position error due to the antenna installation or external force, the mutual coupling effect caused by the mutual electromagnetic influence between the antennas, the mismatch between antennas leads to errors in the gain and phase of the received signal, and the signal scattering in the transmission path. These errors may coexist at the same time. Therefore, the development of robust algorithms under the multiple error environments is more in line with the situation applied in the real environments. In developing the robust algorithms, we take the signal direction vector estimated by the tensor analysis of the received data vector. Then, the minimax method is utilized to further improve the accuracy of the estimate of the signal direction vector. Finally, we incorporate the interference plus noise autocorrelation matrix reconstruction with linearly-constrained minimum variance (LCMV) beamformer. The proposed algorithms provide superior robustness MIMO radar performance under multiple error scenarios. Moreover, they can avoid that the MIMO radar system treats the desired signal as interference and eliminate it as the signal-to-noise power ratio (SNR) increases. Computer simulations confirm the effectiveness of the proposed algorithms. |
URI: | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/78319 |
DOI: | 10.6342/NTU202002428 |
全文授權: | 有償授權 |
顯示於系所單位: | 電信工程學研究所 |
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U0001-0508202002180300.pdf 目前未授權公開取用 | 3.4 MB | Adobe PDF |
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