基于自适应形态学的低截获概率信号检测预处理算法

Theory and Numerical Research on the Flamelet Model in Laminar Non-premixed Combustion

针对传统算法在面对复杂环境中低截获概率(lour probability of intercept,LPI)信号检测时不能对噪声进行有效的滤波,提出了一种基于自适应形态学的LPI信号检测预处理方法。首先建立单一尺度形态学滤波模型;其次在单一尺度形态学频谱数据做分段插值处理时,在每段采用加入比例系数的改进形态学腐蚀和膨胀机理,再将插值后的序列与原信号相减来对其进行修正;最后通过算法仿真,验证了改进的算法在弱化结构元素尺度选择矛盾对不同带宽处的噪声基底估计的影响的同时,还能大大降低整个算法运算量的效果,取得了良好的滤波效果。

Aiming at the problem that the traditional algorithm can not effectively filter the noise in the face of complex LPI signal detection,a preprocessing method of LPI signal detection based on adaptive morphology is proposed. First,a single scale morphological filter model is established. Then when the single-scale morphological spectral data is segmented,the modified morphological corrosion and expansion mechanism is added to each segment,and then the interpolated sequence is subtracted from the original signal to correct it. Finally,through the simulation of the algorithm,it is verified that the improved algorithm can reduce the influence of the contradiction on the noise base estimation at different bandwidths while weakening the structural element scale,and can greatly reduce the effect of the whole algorithm and achieve good filtering effect.