【摘要】：自適應(yīng)波束形成技術(shù)是一種空域的自適應(yīng)濾波技術(shù),作為陣列信號(hào)處理的一個(gè)重要的研究方向,自適應(yīng)波束形成技術(shù)經(jīng)過(guò)幾十年的發(fā)展,其基本理論與算法已經(jīng)相當(dāng)成熟,但在其工程化實(shí)現(xiàn)的過(guò)程當(dāng)中,還存在大量問(wèn)題沒(méi)有得到解決。本文依托課題,以工程化實(shí)現(xiàn)為目標(biāo),針對(duì)波束形成過(guò)程中算法運(yùn)算量與傳輸數(shù)據(jù)量大的問(wèn)題,圍繞著波束域降維、子空間降秩和寬帶恒定束寬等幾個(gè)方面對(duì)自適應(yīng)波束形成算法進(jìn)行了研究,并基于多核DSP硬件平臺(tái)對(duì)提出的算法進(jìn)行工程化實(shí)現(xiàn)。主要工作概括如下:1.采用波束域降維與子空間降秩的方式來(lái)解決窄帶自適應(yīng)波束形成算法計(jì)算量大的問(wèn)題。首先,把最小方差無(wú)失真響應(yīng)波束形成算法(MVDR)與廣義旁瓣相消器(GSC)推廣到波束域,在獲得與傳統(tǒng)算法相同的波束形成性能的同時(shí),通過(guò)波束域降維處理來(lái)降低算法的計(jì)算量。然后,在GSC的框架下,將波束域降維方法與子空間降秩方法結(jié)合起來(lái),提出了一種GSC框架下波束域快速自適應(yīng)波束形成算法,并給出了該算法的實(shí)現(xiàn)結(jié)構(gòu)。該算法通過(guò)一次特征分解降低了矩陣求逆的計(jì)算量,并通過(guò)子空間投影來(lái)改善算法性能。2.采用頻域?qū)拵Ш愣ㄊ鴮挼牟ㄊ纬煞椒▉?lái)解決寬帶信號(hào)波束形成之后發(fā)生畸變的問(wèn)題,并用窄帶快速算法來(lái)降低寬帶自適應(yīng)波束形成的計(jì)算量。首先,給出了兩種頻率不變寬帶波束形成算法——空間重采樣法與FFT插值法,通過(guò)比較發(fā)現(xiàn)空間重采樣法的聚焦性能要優(yōu)于FFT插值法。然后,將頻域?qū)拵Ш愣ㄊ鴮挷ㄊ纬杉夹g(shù)與窄帶快速自適應(yīng)波束形成技術(shù)結(jié)合起來(lái),提出了一種寬帶恒定束寬快速自適應(yīng)波束形成算法,并給出了其兩種實(shí)現(xiàn)結(jié)構(gòu)。算法在保證恒定束寬性能的前提下,顯著降低了計(jì)算量。3.依托課題背景,在多核DSP高速信號(hào)處理平臺(tái)上對(duì)提出的算法進(jìn)行工程化實(shí)現(xiàn),設(shè)計(jì)了主從模式與數(shù)據(jù)流模式相結(jié)合的多核DSP并行處理過(guò)程。處理結(jié)果表明該方法求權(quán)精度高,波束形成速度快,易于在多核DSP上實(shí)現(xiàn)。
[Abstract]:Adaptive beamforming technology is a spatial adaptive filtering technology. As an important research direction of array signal processing, adaptive beamforming technology has been developed for decades, its basic theory and algorithm has been quite mature. However, in the process of its engineering, there are still a lot of problems have not been solved. Based on the subject, this paper aims at engineering realization, aiming at the problem of large amount of computation and transmission data in the beamforming process, focusing on the dimension reduction of beamspace. Adaptive beamforming algorithm is studied in several aspects, such as subspace rank reduction and broadband constant beam width, and the proposed algorithm is realized by engineering based on multi-core DSP hardware platform. The main work is summarized as follows: 1. Beamspace dimensionality reduction and subspace rank reduction are used to solve the problem of large computational complexity of narrowband adaptive beamforming algorithm. Firstly, the minimum variance distortionless response beamforming algorithm (MVDR) and the generalized sidelobe canceller (GSC) are extended to beamspace. The beamspace dimensionality reduction process is used to reduce the computational complexity of the beam-space algorithm while obtaining the same beamforming performance as the traditional beamforming algorithm. Then, a fast adaptive beamspace beamforming algorithm under GSC framework is proposed by combining beamspace dimensionality reduction method with subspace rank reduction method, and its implementation structure is given. The algorithm reduces the computation cost of matrix inversion and improves the performance of the algorithm by subspace projection. A frequency-domain beamforming method with constant beamwidth is used to solve the problem of distortion after beamforming of wideband signals, and narrow band fast algorithm is used to reduce the computational complexity of wideband adaptive beamforming. Firstly, two frequency invariant wideband beamforming algorithms, spatial resampling and FFT interpolation, are presented. It is found that the focusing performance of spatial resampling is better than that of FFT interpolation. Then, combining the frequency domain constant beamwidth beamforming technology with narrow band fast adaptive beamforming technology, a broadband constant beamwidth fast adaptive beamforming algorithm is proposed, and its two implementation structures are given. On the premise of guaranteeing the constant beam width performance, the algorithm reduces the computation cost by 3. 3. Based on the background of the project, the proposed algorithm is implemented on the multi-core DSP high-speed signal processing platform, and the parallel processing process of multi-core DSP is designed based on the combination of master-slave mode and data flow mode. The processing results show that this method has high weight accuracy, fast beamforming speed and is easy to be implemented on multi-core DSP.
【學(xué)位授予單位】：國(guó)防科學(xué)技術(shù)大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2014
【分類號(hào)】：TN957.51

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