基於估計干擾指引向量之重建干擾加雜訊自相關矩陣應用於雙基地多輸入多數出雷達系統的強健式波束賦形技術

Robust Adaptive Beamforming in Bistatic MIMO Radar Based on Interference-Plus-Noise-Covariance Matrix Reconstruction with Interference Steering Vector Estimation

李雲翔(Yun-Xiang Li)

指導教授 ： 李枝宏

國立臺灣大學/電機資訊學院/電信工程學研究所/碩士(2022年)

https://doi.org/10.6342/NTU202201865

摘要

本篇論文討論在多輸入多輸出雙基地雷達架構下，並當現實環境中有陣列誤差發生時的強健式波束賦型設計。我們提出了基於重建干擾加雜訊自相關矩陣的三種方法。我們的第一種方法首先利用Capon 頻譜估計干擾指引向量的方法，此方法在低信噪比下有很好的表現，但在高信噪比下效能有所下降。接著，我們再次提出第二種方法，此方法利用雜訊子空間來估計干擾指引向量，此方法在高信噪比下此方法擁有良好的效能，但在低信噪比會有比第一種方法略為降低的性能。因此，最後我們提出的第三種方法結合了前兩種方法，實驗結果表明我們的第三種方法融合了前兩者方法的優勢，在實驗中的整個信噪比區間中有著優於其他方法的平均效能表現。

關鍵字

多輸入多輸出雙基地雷達 ； 強健式波束賦形 ； 干擾加雜訊自相關矩陣 ； 指引向量估計 ； 凸函數最佳化

並列摘要

We discuss the design of robust beamforming on bistatic MIMO radar architecture and in multiple mismatch scenario. We propose three methods based on IPNC matrix reconstruction. The first method uses the Capon spatial spectrum to estimate the inference steering vectors; the method has great performance at low SNR, but the performance decreases at high SNR. Then, we propose the second method in which the noise subspace spatial spectrum is adopted; the second method perform well at high SNR but poorly at low SNR. Accordingly, the third proposed method combine the preceding ones; the experiment result shows that the third scheme combine the advantages from both schemes and has the superior average performance among the methods in the simulation across a wide range of SNR.

並列關鍵字

MIMO bistatic radar ； robust beamforming ； interference plus noise covariance matrix ； steering vector estimation ； convex optimization

參考文獻

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