【摘要】：波束成形作為智能天線中的關鍵技術,可以有效地解決頻譜資源匱乏的問題。它在通信系統(tǒng)中引入了空時處理的自由度,利用用戶信號到達方向的不同,采用空分多址,將同時、同頻、同碼的信號區(qū)分開了,大幅度地提高了頻譜利用率,擴展了系統(tǒng)容量。然而波束成形的精度會受到噪聲的干擾,在低信噪比下,陣列的性能和輸出信噪比會大幅度下降,陣列天線形成的波束已經(jīng)不能準確地對準期望用戶的方向,波束成形就失去了在空域上分離用戶,并且抑制干擾的作用。因此,在低信噪比下提高波束成形的準確度就成為一個值得研究的課題。針對以上問題,本論文將研究基于隨機共振波束成形結構和算法。在提出的結構中,接收信號先經(jīng)過隨機共振系統(tǒng)的處理,將淹沒在強噪聲背景中的微弱信號提取出來,然后進行自適應的波束成形算法。針對隨機共振系統(tǒng)對采樣率較高的要求,本文主要研究在高頻段(3~30M)的波束成形問題。本文的主要內(nèi)容為以下幾個方面:1本文先詳細介紹了基于朗之萬方程的隨機共振系統(tǒng)模型,并對隨機共振的理論分析做了詳細介紹。2由于絕熱近似理論下的非線性隨機共振系統(tǒng)(參數(shù)a=1 b=1)在檢測微弱信號時受小頻率參數(shù)的約束,給實際應用帶來很大困難。針對這一情況,提出二次采樣方法和調(diào)整系數(shù)法來檢測任意大頻率的微弱信號。以調(diào)節(jié)參數(shù)雙穩(wěn)態(tài)系統(tǒng)的基礎上,研究了雙穩(wěn)態(tài)系統(tǒng)參數(shù)和信號頻率之間的相互關系。對于淹沒在噪聲中的不同頻率的輸入信號,提出一種自適應調(diào)節(jié)參數(shù)的方法,使輸入信號頻率和雙穩(wěn)態(tài)系統(tǒng)達到最佳共振效果。3本文詳細介紹了自適應波束成形的概念、算法準則和常用算法。重點介紹并推導了兩種CDMA系統(tǒng)中的多目標自適應解擴重擴波束成形算法。4在以上研究的基礎上,本文提出了一種自適應的陣列天線信號處理結構,將自適應隨機共振應用在多目標自適應解擴重擴波束成形算法中,通過仿真在極低信噪比下使算法性能得到大幅度提高。
[Abstract]:Beamforming, as the key technology of smart antenna, can effectively solve the problem of lack of spectrum resources. It introduces the degree of freedom of space-time processing in the communication system, makes use of the different direction of arrival of the user signal, adopts the space division multiple access, distinguishes the signals of the same frequency and the same code at the same time, and greatly improves the spectrum utilization. The system capacity is expanded. However, the precision of beamforming will be interfered by noise. At low SNR, the performance and output signal-to-noise ratio (SNR) of the array will be greatly reduced, and the beam formed by the array antenna will no longer be able to accurately target the direction of the desired user. Beamforming loses the role of separating users in spatial space and suppressing interference. Therefore, improving the accuracy of beamforming at low signal-to-noise ratio becomes a subject worth studying. In order to solve the above problems, this paper will study the structure and algorithm based on stochastic resonance beamforming. In the proposed structure, the received signal is processed by stochastic resonance system, and the weak signal submerged in the strong noise background is extracted, and then an adaptive beamforming algorithm is carried out. In order to meet the requirement of high sampling rate for stochastic resonance system, the beamforming problem in high frequency band (3 鈮，

本文編號：2472292