基于稀疏表示的不相關(guān)分布式信源參數(shù)估計(jì)算法
doi: 10.11999/JEIT150340 cstr: 32379.14.JEIT150340
基金項(xiàng)目:
中央高?；究蒲袠I(yè)務(wù)費(fèi)專項(xiàng)基金(K5051202047)
Parameter Estimation Method of Incoherently Distributed Source via Sparse Representation
Funds:
The Fundamental Research Fund for the Central Universities of China (K5051202047)
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摘要: 在分析不相關(guān)分布式信源(Incoherently Distributed Source, IDS)信號(hào)模型的基礎(chǔ)上，該文給出一種基于稀疏表示的IDS參數(shù)估計(jì)方法。該方法利用IDS協(xié)方差矩陣的Toeplitz性質(zhì)，結(jié)合IDS協(xié)方差矩陣的兩點(diǎn)近似及Jacobi-Anger級(jí)數(shù)展開模型，分別采用兩個(gè)1維稀疏表示問題對(duì)IDS的角度擴(kuò)展及中心入射角度進(jìn)行估計(jì)。同現(xiàn)有算法相比，該文方法不需要進(jìn)行2維搜索，計(jì)算量較小。仿真結(jié)果表明，該文算法在低信噪比及小快拍情況下具有良好的參數(shù)估計(jì)性能。
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關(guān)鍵詞:
- 信號(hào)處理 /
- 參數(shù)估計(jì) /
- 稀疏表示 /
- 不相關(guān)分布式信源
Abstract: By analyzing the signal model of the Incoherently Distribute Source (IDS), a sparse representation based parameter estimation method of IDS is presented. Through using the Toeplitz characteristic and the two point approximation model as well as the Jacobi-Anger expansion model of the covariance matrix of the IDS, the angle spread and the central direction angle of the IDS is estimated by adopting two sparse representation problems. Compared with the present method, the proposed method does not need two dimensional searches and has low computational burden. Simulation results show that the proposed method has good parameter estimation performance in the low signal-to-noise ratio and small snapshot number scenario. -
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