基于互相關(guān)協(xié)方差矩陣的改進(jìn)多重信號(hào)分類高分辨波達(dá)方位估計(jì)方法
doi: 10.11999/JEIT141208 cstr: 32379.14.JEIT141208
基金項(xiàng)目:
國(guó)家自然科學(xué)基金(61271415)
Improved Multiple Signal Classification Algorithm for Direction of Arrival Estimation Based on Covariance Matrix of Cross-correlation
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摘要: 針對(duì)經(jīng)典高分辨波達(dá)方位(DOA)估計(jì)方法在低信噪比下分辨性能較差的問(wèn)題，該文提出一種適用于主動(dòng)探測(cè)系統(tǒng)的基于互相關(guān)矩陣的改進(jìn)多重信號(hào)分類(MUSIC)高分辨方位估計(jì)方法(I-MUSIC)。該方法首先利用主動(dòng)聲吶發(fā)射信號(hào)已知的特性，將發(fā)射信號(hào)與陣元接收信號(hào)進(jìn)行互相關(guān)，利用互相關(guān)序列形成新的空域協(xié)方差矩陣，再進(jìn)行特征分解。理論分析表明，互相關(guān)處理在抑制噪聲的同時(shí)保留了陣元之間的相位信息，可以得到比MUSIC方法更準(zhǔn)確的子空間劃分，進(jìn)而提高低信噪比方位估計(jì)性能。在此基礎(chǔ)上，提出一種基于相關(guān)時(shí)間門限的改進(jìn)MUSIC高分辨方位估計(jì)(T-MUSIC)方法，通過(guò)對(duì)互相關(guān)序列設(shè)置時(shí)間門限進(jìn)一步提高方位估計(jì)信噪比。仿真結(jié)果表明，與MUSIC方法相比，I-MUSIC與T-MUSIC可以分別使低信噪比時(shí)的估計(jì)性能提高3 dB和6 dB，相應(yīng)平均估計(jì)誤差分別為原方法的77%和53%。在陣元間接收噪聲存在相關(guān)性時(shí)，T-MUSIC與I-MUSIC方法相比可獲得8 dB的估計(jì)增益，估計(jì)性能更優(yōu)。I-MUSIC與T-MUSIC應(yīng)用于多目標(biāo)主動(dòng)探測(cè)，可大幅提高探測(cè)系統(tǒng)在低信噪比下的方位估計(jì)性能。
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關(guān)鍵詞:
- 信號(hào)處理 /
- 波達(dá)方位估計(jì) /
- 互相關(guān) /
- 協(xié)方差矩陣 /
- 多重信號(hào)分類
Abstract: In view of the poor performance of traditional Direction of Arrival (DOA) methods at low signal-to-noise ratios, an improved MUltiple SIgnal Classification (MUSIC) algorithm for DOA estimation applied to active detection system based on covariance matrix decomposition of cross-correlation (I-MUSIC) is proposed. Exploiting the transmission feature of active sonar, cross-correlation sequence between the transmitted signal and the array output is formulated. The spatial covariance matrix is then constructed from the sequence. Then matrix decomposition is implemented over the new spatial covariance matrix to estimate the DOA. It is proved that cross-correlation can suppress noise while preserving the phase information between array elements, which facilitate the subspace separation at low SNRs. Furthermore, another novel method based on correlation Time threshold (T-MUSIC) is proposed to further improve the DOA performance. Simulation results indicate that I-MUSIC and T-MUSIC can obtain a performance gain of 3 dB and 6 dB, with the estimate error being 77% and 53% of the original method respectively. Due to data selection via time threshold, T-MUSIC is not appreciably affected by noise, and thus outperforms IM-MUISC for 8 dB at low SNRs. I-MUSIC and T-MUSIC can improve the DOA performance at low SNRs significantly if applied to active multi-target detection system. -
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