计算机工程与应用
計算機工程與應用
계산궤공정여응용
COMPUTER ENGINEERING AND APPLICATIONS
2013年
16期
209-212
,共4页
短波突发通信%无辅助数据%粒子滤波
短波突髮通信%無輔助數據%粒子濾波
단파돌발통신%무보조수거%입자려파
HF burst-mode communication%Non Data Aided%particle filter
针对传统短波突发通信中载波恢复及符号检测问题,提出了一种基于粒子滤波的无辅助数据的算法。首先利用贝叶斯准则实现收发频率差的最大后验估计,然后通过粒子滤波算法实现载波相位和调制符号的最小均方误差估计。算法中使用了序列重要性采样技术实现粒子权值的迭代更新和系统重采样技术防止粒子权重的衰退。仿真分析了高斯白噪声信道下的载波恢复性能,结果表明,基于粒子滤波的载波恢复算法载波恢复时间短,同步速度快,恢复频率范围广。建立以Watterson模型为基础的短波通信系统模型,通过该模型在不同的信道状态、信噪比和频偏条件下进行了仿真实验。结果表明在大频差的条件下,算法也具有良好的符号检测性能。
針對傳統短波突髮通信中載波恢複及符號檢測問題,提齣瞭一種基于粒子濾波的無輔助數據的算法。首先利用貝葉斯準則實現收髮頻率差的最大後驗估計,然後通過粒子濾波算法實現載波相位和調製符號的最小均方誤差估計。算法中使用瞭序列重要性採樣技術實現粒子權值的迭代更新和繫統重採樣技術防止粒子權重的衰退。倣真分析瞭高斯白譟聲信道下的載波恢複性能,結果錶明,基于粒子濾波的載波恢複算法載波恢複時間短,同步速度快,恢複頻率範圍廣。建立以Watterson模型為基礎的短波通信繫統模型,通過該模型在不同的信道狀態、信譟比和頻偏條件下進行瞭倣真實驗。結果錶明在大頻差的條件下,算法也具有良好的符號檢測性能。
침대전통단파돌발통신중재파회복급부호검측문제,제출료일충기우입자려파적무보조수거적산법。수선이용패협사준칙실현수발빈솔차적최대후험고계,연후통과입자려파산법실현재파상위화조제부호적최소균방오차고계。산법중사용료서렬중요성채양기술실현입자권치적질대경신화계통중채양기술방지입자권중적쇠퇴。방진분석료고사백조성신도하적재파회복성능,결과표명,기우입자려파적재파회복산법재파회복시간단,동보속도쾌,회복빈솔범위엄。건립이Watterson모형위기출적단파통신계통모형,통과해모형재불동적신도상태、신조비화빈편조건하진행료방진실험。결과표명재대빈차적조건하,산법야구유량호적부호검측성능。
To solve the problem of carrier frequency synchronization in HF burst-mode communication, a Non Data Aided (NDA)algorithm based on particle filter is proposed. The Maximum A Posterior(MAP)estimation of carrier frequency offset is made based on Bayesian formulation. And the minimum mean square error(MMSE)estimation of carrier phase and modulat-ed symbols are obtained by particle filter algorithm. The particle weights are recursively computed using Sequential Importance Sampling(SIS). Systematic resampling is employed for the reduction of particle weights degeneration. The carrier recovery perfor-mance of the algorithm for the channel with Gaussian white noise is simulated. The results show that the algorithm has short carrier recovery time and wide carrier recovery range. A HF communication simulation model is built based on Watterson model. Signals are simulated through this model under different channels, Signal-to-Noise Ratio(SNR)and frequency offset conditions. The re-sult shows good performance of symbol detection even for large frequency offset.