【摘要】：作為信號處理領(lǐng)域的一個重要分支,麥克風(fēng)陣列由于其特有的優(yōu)越性被逐漸應(yīng)用于視頻會議、聲紋識別、人工智能等方面。作為超分辨算法之一的多重信號分類(MUSIC)算法由于突破了瑞利限而具有很好的精度。但是為了解決目前應(yīng)用環(huán)境中存在的“多徑衰落”、“多址干擾”等問題,要求DOA(波達(dá)方向估計)算法精度更高,系統(tǒng)響應(yīng)更快,適應(yīng)性更強(qiáng),因此必須對MUSIC算法進(jìn)行改進(jìn)。然而,麥克風(fēng)陣列的幅度相位和位置誤差又影響著DOA估計精度。故本文就是在充分考慮麥克風(fēng)陣列幅度相位和位置誤差的情況下,研究了 DOA估計算法。本文的主要工作包括:1.對MUSIC算法進(jìn)行改進(jìn)。MUSIC算法精度雖高,但是計算量過大。針對這一缺點(diǎn),引入MSCS(MUSIC對稱壓縮譜)算法在其中做均衡處理。當(dāng)MSCS算法搜索到譜峰附近時,以該極值點(diǎn)為中心重新劃定一個小區(qū)域的搜索范圍,在此范圍內(nèi)替換成MUSIC算法進(jìn)行譜峰搜索,從而在降低運(yùn)算量的同時,有效地提高了算法精度。仿真實(shí)驗(yàn)表明,在較高信噪比(大概25dB以上)時,該算法估計精度與MUSIC算法基本保持一致,系統(tǒng)響應(yīng)時間卻降低為原來的2/3,由此可見,算法的性能得到較大改善。2.麥克風(fēng)陣列存在幅度相位誤差時的DOA估計。研究了存在幅度相位誤差時的麥克風(fēng)自校正方法,該方法不像常規(guī)方法一樣需要獲取聲源的精確位置,僅需在關(guān)于陣列鏡像對稱的位置各放置一個校正聲源即可,然后對獲取的數(shù)據(jù)進(jìn)行矩陣分解等操作即可估計出誤差。通過消聲室實(shí)驗(yàn)獲取實(shí)測數(shù)據(jù)進(jìn)行實(shí)驗(yàn)驗(yàn)證,結(jié)果表明,即使是在0-4000Hz這種幅度相位誤差不大的語音頻段,該自校正方法的估計偏差依然很小。3.麥克風(fēng)陣列存在位置誤差時的DOA估計。在陣列位置誤差校正的研究中引入遺傳算法的思想,先通過理想陣元情況下的MUSIC算法獲取估計角的初始值,然后對這一初始群體中的個體進(jìn)行適應(yīng)度評價獲取最優(yōu)個體,再通過選擇、變異、交叉等操作產(chǎn)生下一代搜索群體,重復(fù)評優(yōu)過程并減小偏差因子直至找出最優(yōu)個體,代入MUSIC譜公式,獲取最終的估計角度。實(shí)驗(yàn)和仿真結(jié)果表明,最大的估計偏差不超過0.1cm,絕大多數(shù)位置的估計偏差都在0.02cm以內(nèi)。
[Abstract]:As an important branch of signal processing, microphone array has been gradually applied to video conferencing, voiceprint recognition, artificial intelligence and so on because of its unique advantages. As one of the super-resolution algorithms, the multi-signal classification (MUSIC) algorithm has good accuracy because it breaks through the Rayleigh limit. However, in order to solve the problems of "multi-path fading" and "multiple access interference" in the current application environment, DOA (Direction of arrival estimation) algorithm is required to have higher accuracy, faster system response and stronger adaptability, so it is necessary to improve the MUSIC algorithm. However, the amplitude phase and position error of microphone array affect the accuracy of DOA estimation. Therefore, this paper studies the DOA estimation algorithm under the condition of fully considering the amplitude phase and position error of microphone array. The main work of this paper includes: 1. The MUSIC algorithm is improved. Music algorithm has high accuracy, but the amount of computation is too large. In order to solve this problem, MSCS (MUSIC symmetric compression spectrum algorithm is introduced to equalize it. When the MSCS algorithm searches near the spectral peak, the search range of a small region is redefined with the extreme point as the center, and the spectral peak search is replaced by the MUSIC algorithm in this range, which not only reduces the computational complexity, but also effectively improves the accuracy of the algorithm. The simulation results show that the estimation accuracy of the algorithm is basically consistent with that of the MUSIC algorithm, but the response time of the system is reduced to 2 鈮，

本文編號：2479206