一种广义的自适应相干累积算法

Improved generalized adaptive coherent integration algorithm

根据最小均方误差算法(LMS)、自适应相干累积算法(ACI)及推广的自适应相干累积算法(Generalized Adaptive Coherent Integrator,GACI)在原理上的相关性和推广关系,提出了广义的自适应相干累积算法(IGACI)。以GACI为基础,在权系数迭代公式中引入更多的动量因子,即利用权系数的更多的历史信息,使被检测的单频或调频脉冲信号,在脉冲持续期间实现自适应相干累积,从而完成低输入信噪比条件下的信号检测,而无需或很少需要知道信号的先验信息。理论分析和仿真结果证明在低信噪比情况下,其性能优于GACI算法。

GACI （Generalized Adaptive Coherent Integrator） algorithm is effective in pulse signals detection. In an improved style, called IGACI, more momentum factors than those in GACI algorithm, are introduced into the iteration formulas for weight coefficients. Such processing allows the utilization of more history information available in weight coefficients within the impulse, and accordingly the sinusoidal and LFM （Linear Frequency Modulated） signals to be detected can be adaptively coherent integrated. Thus, under the condition of low input SNR （signal to noise ratio）, signal detection can be accomplished without knowing of a priori or with only a little knowledge of a priori. Both GACI and IGACI algorithms are used for detecting the LFM signals in white Gaussian noise. Simulations show that IGACI could get better performances.