应用形态学的自适应门限干扰检测算法

该文针对通信信号中背景噪声复杂的问题，应用数字形态学的信号预处理方法，能较好地滤除背景噪声；又由于单一门限值难以实现对不同宽度干扰的检测，提出一种应用形态学自适应门限的干扰检测算法。此算法首先对信号谱线进行功率谱估计，然后利用形态学的方法进行预处理，再根据信号功率谱的分布情况，选取不同的门限值，实现门限的自适应，为检测不同占有用信号带宽大小的窄带干扰提供了有效的方法。该文提出的方法不会受噪底变化的影响，计算量小，复杂度较低，适用于星上卫星通信的实时频谱监测。经过Matlab仿真实验得出，当采用结构元素长度为25的扁平型结构元素时，通过形态学中的膨胀预处理方法以及自适应门限可以得到检测效果比传统的连续均值去除算法(CME)算法有6dB以上的提升。 

Application of morphology of adaptive threshold interference detection algorithm

In order to solve the problem of the background noise in the communication signals, the preprocessing method based on digital morphology can filter the background noise well. Because it is difficult to detect the interferences of different widths with a signal threshold, a narrow-band interference detection algorithm based on morphological adaptive threshold is proposed. Firstly this algorithm estimates the spectrum of signals, and then preprocesses them by morphological method. Then, according to the distribution of signal power spectrum, different threshold values were selected to realize adaptive threshold, which provided an effective method for detecting narrow-band interference of different signal bandwidths. The method proposed in this paper is not affected by the change of the noise base, and it has low computation and complexity, which is suitable for the real-time spectrum monitoring of on-board satellite communication. Through Matlab simulation experiments, it is concluded that the detection effect of flat structural elements with a length of 25 is improved by more than 6dB compared with the traditional continuous mean removal algorithm (CME) through the expansion preprocessing method and adaptive threshold.