中文摘要：

传统常模盲均衡算法应用广泛但是其收敛速率很慢。为了满足在短突发数据条件下的信道盲均衡,提出一种基于数据重用的集员滤波拟仿射投影盲均衡算法。该算法将仿射投影思想结合到常模算法中,利用多数据向量同时提取信道信息,再附加改进的集员滤波算法有效减小了运算量,并结合数据重用思想重新设计所匹配的数据重用方式。仿真结果证明所提算法具有较快的收敛速率,与同类算法相比能提前700个迭代点收敛,且在信噪比为10 d B以上的信道环境中也有较好的效果,能够在短突发数据信道均衡中有效发挥作用。

英文摘要：

The traditional constant modulus blind equalization algorithm is widely used but its convergence rate is very slow. In order to satisfy the channel blind equalization under short burst data condition, this pa- per proposes a set-membership like-affine-projection blind equalization algorithm based on data reuse. This algorithm introduces the idea of affine projection into constant modulus algorithm （CMA） and uses multiple data vectors to extract channel information. By using additional improved set-membership filtering algorithm, the proposed algorithm can effectively reduce the computational complexity. In addition, it combines the data reuse idea to redesign the mode of data reuse. Simulation results show that the proposed al- gorithm has a high convergence rate. Compared with other similar algorithms, the algorithm can converge to 700 points in advance, has a better performance in the channel environment of 10 dB above, and can effectively play the role in the short burst data channel equalization.