广义自适应相干累积算法改进及其在线谱增强中的应用

Improving generalized adaptive coherent integration with application to adaptive line enhancement

文章在广义的自适应相干累积(IGACI)算法的基础上,提出了修正系数的IGACI算法。即在相应原权系数基础上乘以修正系数,修正原则是提升末端权系数的幅值,同时可根据信噪比的变化作适当的调整。并将其用于白色噪声下的线谱增强,理论分析和仿真结果证明了在低信噪比的情况下,其性能要优于IGACI算法。文章还讨论了自适应线谱增强器的两种改进形式,并将IGACI算法应用于其中,仿真结果证明了其优越性。

We propose an improved generalized adaptive coherent integrator （IGACI） using coefficient adjustment. In this algorithm, the coefficients are changed with SNR. It can be used to detect linear frequency modulation （LFM） signal in white Gaussian noise. Our study confirms that the IGACI algorithm based on coefficient adjustment is better than the original IGACL The technique is used in the adaptive line enhancer （ALE）. Simulation results show feasibility of the proposed algorithm.