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讨论了一种利用Gibbs采样方法的贝叶斯多目标高分辨定向新方法(BDGS),给出了这种贝叶斯定向新方法的推导过程。该方法将一种新方法Gibbs采样应用于贝叶斯高分辨方法的计算过程。新方法不仅具有贝叶斯多目标高分辨定向方法的优越性能,而且还降低了原贝叶斯方法计算的复杂程度。并在最后给出了新方法的性能分析,与MUSIC(子空间法)和MLE(最大似然法)的比较结果表明新方法有更高的分辨率,在低信噪比情况下性能也较好。
A new Bayesian multiobjective high resolution orientation method (BDGS) using Gibbs sampling method is discussed. The derivation of this new Bayesian orientation method is given. This method applies a new method of Gibbs sampling to the Bayesian high resolution method. The new method not only has the superior performance of the Bayesian multi-target high-resolution orientation method, but also reduces the complexity of the original Bayesian method. Finally, the performance analysis of the new method is given. Compared with MUSIC (subspace method) and MLE (maximum likelihood method), the results show that the new method has higher resolution and lower performance under low SNR it is good.