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中文摘要：
将马尔可夫蒙特卡罗方法与MUSIC方法估计相结合,提出一种基于吉布斯抽样的频率-方位联合估计新方法（MUSIC FREQ-DOA joint Estimator Based on Gibbs Sampling,简称Gibbs-MUSIC）。并用该方法联合估计多个目标的频率和方位。这种方法将MUSIC方法的谱函数作为频率和方位的联合概率密度函数,并采用马尔可夫蒙特卡罗（MCMC）吉布斯抽样方法对该联合概率密度函数进行采样。仿真实验显示在目标个数较少时,该方法不仅保持了常规MUSIC方法的高分辨能力,而且降低了计算量,减少了存储量。
英文摘要：
A new Gibbs sampling DOA estimator based on MUSIC method （Gibbs-MUSIC） is proposed to joint estimate the frequency and directions of multiple sources. The method regards the power of MUSIC spectrum function as target distribution up to a constant of proportionality, and uses Gibbs sample, one of the most popular Markov Chain Monte Carlo （MCMC） technique, to sample from it. Simulations show that the new method not only possesses the performance of high-resolution frequency and direction finding in conventional MUSIC method but also provides a less computation and storage costs than that of conventional MUSIC method under the condition where the number of signal sources is small.
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同项目期刊论文
An Adaptive Differentially Coherent Detection and Phase Compensation Algorithm in Underwater Acousti
Real-time Parallel Processing System Design and Implementation for Underwater Acoustic Communication
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