中文摘要：

基于特征分解的子空间类测向算法均要知道信源个数，但在小快拍数、低信噪比，且信源间的信号强度差异明显的场合中，传统的AJC信息准则和MDL准则均不能准确判断信源个数．这直接恶化了基于特征分解类算法（如MUSIC法）的测向性能．针对该问题，提出了一种利用信源先验特征的混合测向算法。该算法既利用了信源在角度上呈稀疏分布的信息提高了信源数判决的准确性，也利用了信源的非圆特性改进了测向性能。计算机仿真证实了该方法的正确性。

英文摘要：

The number of sources must be known for eigen-decomposition subspace direction finding algorithms. However, in small number of snapshots and low signal-to-noise ratio （SNR） case, and when different signal strength between sources are occurred, both conventional AIC information criterion and MDL criterion are not able to judge the source number correctly and the performance of eigen-decomposition subspace direction finding algorithms （such as MUSIC method） deteriorates. To solve the problem, a hybrid direction finding approach using priori information of sources is proposed. With the proposed approach, the number of sources can be determined by using the fact that sources are sparse in angle domain. Furthermore, with the priori information that sources are non-circular, the direction finding performance is improved. Finally, computer simulations illustrate correction of the proposed approach..