a稳定分布噪声下基于Merid滤波的跳频信号参数估计

Parameter Estimation of Frequency-hopping Signals Based on Merid Filter in a Stable Noise Environment

常规时频分析方法是处理跳频(FH)信号的有力工具,但在a稳定分布噪声环境下无法有效地实现参数估计。该文提出基于Merid滤波的时频分析方法对跳频信号进行参数估计。Merid滤波器可以有效地抑制a稳定分布噪声,该文先对观测信号进行Merid滤波,再采用短时傅里叶变换(STFT)进行参数估计。仿真结果表明,在a稳定分布噪声环境中,该方法的跳频信号参数估计性能优于基于分数低阶和基于Myriad滤波的两种时频分析方法。

Conventional time-frequency analysis is a powerful tool for Frequency-Hopping（FH） signal processing, however, it fails to realize the parameter estimation in α stable noise environment. Time-frequency analysis based on Merid filter is proposed for FH signal parameter estimation. Merid filter can suppress effectively the α stable noise. The observed signal is processed by Merid filter at first, then the FH signal parameters are estimated by Short-Time Fourier Transform（STFT）. Simulation results show that the proposed method has better parameter estimation performance for FH signals than the fractional lower order statistics as well as the Myriad filter based time frequency analysis methods in α stable noise environment.