【摘要】：自適應(yīng)波束形成算法是信號(hào)源定位的關(guān)鍵技術(shù),影響自適應(yīng)波束形成算法性能的主要因素是算法的收斂速度和穩(wěn)定性,良好的自適應(yīng)算法收斂速度快、計(jì)算復(fù)雜度低和有穩(wěn)定魯棒性。針對(duì)傳統(tǒng)自適應(yīng)波束形成算法收斂速度慢和抗干擾性能差的問題,通過理論推導(dǎo)和仿真對(duì)比分析最小均方算法(LMS)和遞推最小二乘算法(RLS)的性能,并提出一種改進(jìn)的RLS算法。通過施加二次型約束,對(duì)期望信號(hào)波達(dá)方向附近范圍內(nèi)的方向向量的誤差值進(jìn)行約束,來提高算法的魯棒性,并在約束條件下對(duì)權(quán)重向量進(jìn)行優(yōu)化求解,經(jīng)Matlab仿真分析,結(jié)果表明改進(jìn)算法有更快的收斂速度和更好抗干擾性能。
[Abstract]:Adaptive beamforming algorithm is the key technology of signal source location. The main factor affecting the performance of adaptive beamforming algorithm is the convergence speed and stability of the algorithm. Low computational complexity and stable robustness. Aiming at the problems of slow convergence speed and poor anti-jamming performance of traditional adaptive beamforming algorithm, the performance of minimum mean square algorithm (LMS) and recursive least square algorithm (RLS) are analyzed by theoretical derivation and simulation, and an improved RLS algorithm is proposed. In order to improve the robustness of the algorithm, the quadratic constraint is applied to constrain the error of the direction vector in the range of the direction of arrival of the desired signal, and the weight vector is optimized under the constraint conditions, and analyzed by Matlab simulation. The results show that the improved algorithm has faster convergence speed and better anti-jamming performance.
【作者單位】： 上海工程技術(shù)大學(xué)汽車工程學(xué)院;
【基金】：國(guó)家自然科學(xué)基金項(xiàng)目(51675324,51175320) 上海市自然科學(xué)基金項(xiàng)目(14ZR1418600)
【分類號(hào)】：TN911.7

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