基于柯西分布的跳頻信號(hào)參數(shù)最大似然估計(jì)方法
doi: 10.11999/JEIT151029
基金項(xiàng)目:
國(guó)家自然科學(xué)基金(61201286)，陜西省自然科學(xué)基金(2014JM8304)，中央高校基本科研業(yè)務(wù)費(fèi)專項(xiàng)資金(K5051202013)
Maximum-likelihood Estimation for Frequency-hopping Parameters by Cauchy Distribution
Funds:
The National Natural Science Foundation of China (61201286), The Natural Science Foundation of Shaanxi Province of China (2014JM8304), The Fundamental Research Funds for the Central Universities (K5051202013)
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摘要: 該文針對(duì)傳統(tǒng)的跳頻信號(hào)參數(shù)估計(jì)方法在alpha穩(wěn)定分布噪聲下性能嚴(yán)重退化的問(wèn)題，引入基于柯西分布的最大似然估計(jì)方法。將跳頻信號(hào)分解到由信號(hào)包絡(luò)參數(shù)和頻率參數(shù)構(gòu)成的2維平面，基于柯西分布建立最大似然函數(shù)，在抑制alpha穩(wěn)定分布噪聲的同時(shí)，直接對(duì)信號(hào)的頻率參數(shù)進(jìn)行估計(jì)。在構(gòu)建的最大似然函數(shù)基礎(chǔ)上，該方法依據(jù)跳頻信號(hào)的短時(shí)平穩(wěn)性，對(duì)信號(hào)進(jìn)行加窗，有效獲得信號(hào)的跳頻頻率及其跳變次序，進(jìn)而實(shí)現(xiàn)對(duì)信號(hào)的跳變時(shí)刻和跳頻周期等參數(shù)的估計(jì)。仿真結(jié)果表明，在alpha穩(wěn)定分布噪聲環(huán)境中，相比基于分?jǐn)?shù)低階統(tǒng)計(jì)量及基于Myriad濾波的時(shí)頻分析方法，該文所提方法提高了跳頻信號(hào)的參數(shù)估計(jì)精度，具有良好的穩(wěn)健性。
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關(guān)鍵詞:
- alpha穩(wěn)定分布噪聲 /
- 最大似然估計(jì) /
- 跳頻信號(hào) /
- 參數(shù)估計(jì) /
- 2維平面
Abstract: In view that conventional methods for Frequency Hopping (FH) signal parameter estimation suffer from performance degradation in alpha stable noise environment, the Cauchy based maximum likelihood estimation method is introduced in this paper. The FH signal is decomposed into the two-dimensional envelope versus frequency plane, and then a maximum-likelihood function based on Cauchy distribution is established to extract the frequency parameter directly. For the short-time stationarity of FH signals, the maximum-likelihood function is windowed in order to estimate the specific values and sequence of frequency-hopping, after that the hopping timing and the duration can be estimated. Simulation results show that compared with the fractional lower order statistics as well as the Myriad filter based time frequency analysis methods, the proposed method improves the estimation accuracy of FH signal parameters and is robust to the alpha stable distribution noise. -
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