In this paper, the blind signal separation problem of complex baseband signal is addressed. A widely linear complex autoregressive process of order one is employed to represent the temporal structure of complex sources. We formulate a new contrast function by a convex combination of generalized autocorrelations and the statistics of the innovation. And the proposed contrast function is optimized by gradient method. Simulation results show that the proposed algorithm is better than the comparison algorithm in convergence speed and convergence accuracy.

中文翻译：

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基于一阶宽线性复杂自回归过程的盲信号分离

本文解决了复杂基带信号的盲信号分离问题。采用一阶广泛线性复杂的自回归过程来表示复杂源的时间结构。我们通过广义自相关和创新统计的凸组合来制定新的对比函数。并通过梯度法对提出的对比度函数进行了优化。仿真结果表明，该算法在收敛速度和收敛精度上均优于比较算法。