提出了信號(hào)子空間維數(shù)估計(jì)法、噪聲子空間加權(quán)法和擴(kuò)展MUSIC法三種修正的寬帶信號(hào)子空間譜估計(jì)方法，它們均有效地解決了寬帶信號(hào)子空間譜估計(jì)法所存在的信號(hào)子空間維數(shù)擴(kuò)展問題。信號(hào)子空間維數(shù)估計(jì)法用包含信號(hào)99.9%以上功率的特征值數(shù)目來(lái)估計(jì)信號(hào)子空間維數(shù)，正確地劃分了子空間。噪聲子空間加權(quán)法和擴(kuò)展MUSIC法不用劃分子空間，而是給噪聲子空間特征向量或全空間特征向量加權(quán)，減小了子空間維數(shù)擴(kuò)展的影響。仿真實(shí)驗(yàn)結(jié)果表明：三種修正方法是有效的，并具有良好的統(tǒng)計(jì)性能。To overcome the problem of signal-subspace dimension expanding, three different improved methods for wideband signal-subspace spatial-spectrum estimation are presented. The first method, called the signal-subspace dimension estimation method, estimates signal-subspace dimension by a number of eigenvalues, which include 99.9% signal power; thus this method can make a correct division between signal-subspace and noise-subspace. The other two methods. weighted noise-subspace method and extended MUSIC method, do not need to make a correct division between the two subspaces. Instead. These two methods can reduce the effect of signal-subspace dimension expanding directly by using weighted eigenvectors in the noise-subspace or the entire space. Computer simulations show that all these improved methods can overcome effectively the effect of signal-subspace dimension expanding of wideband signal-subspace spatial-spectrum estimation and possess good statistical performance.