摘要
近年来,天线阵列信号处理技术由于在消除空域干扰、提高无线通信容量和质量方面的突出表现而引起了广泛的关注。天线阵列信号处理技术应用于扩频通信系统将提高扩频通信系统的抗干扰性能,目前已有大量的研究集中在直扩信号的天线阵列接收技术。已有文献证明了在部分频带干扰环境下多载波扩频技术比直扩技术具有更好的性能。本文以增强干扰抑制能力为目标,研究了多天线接收多载波扩频信号的若干问题,利用多载波扩频信号的频率分集特性增强天线阵列抑制干扰能力,取得了一定的有益结果。
本文首先研究了拥挤干扰环境下的多载波扩频信号的天线阵列接收问题,并提出了一种针对多载波扩频信号的天线阵列接收算法。拥挤干扰环境指干扰个数大于波束形成波束形成自由度的环境。拥挤干扰环境下阵列往往难以保证对期望信号有足够强的增益,不利于信号的检测和判决。该算法利用期望信号在不同子载波信道中的相关性估计到达方向,然后利用空间谱分析估计干扰信号的空间分布,最后按照最大输出信噪比准则计算天线阵列加权矢量。该算法保证对期望信号有足够强度响应,并将方向图零点放置在干扰信号成簇的方向。仿真实验表明在相同的拥挤干扰环境下,本文的算法的误码率性能明显优于最佳波束形成器。
针对实际应用中一种典型的干扰信号一随机跳时干扰,本文提出了一种用于多载波扩频信号的空域最小二乘算法。随机跳时干扰信号在时间上随机出现,常常是非平稳的,传统的基于信号统计信息的算法无法有效将其抑制。空域最小二乘算法针对一次抽样数据进行处理,主要应用于雷达系统,本文算法将其应用于通信系统,与应用于雷达系统的算法相比较具有以下特点:(1)不需要估计期望信号的到达方向,因此也不受到达方向估计误差的影响;(2)实现相干多径的相干合并。该算法将不同子信道的滤波输出互相作为参考信号,由于期望信号的相关性,不同子载波信道的滤波输出将同时渐进收敛于期望信号。
本文最后给出了一种针对多载波直扩信号的空-时二维最小输出能量算法,结合空-时二维处理与频率分集合并处理,为干扰抑制问题提供更多的滤波自由度。空-时二维滤波同时利用信号的空间方向性和时间相关性,比单独利用信号空间方向性具有更优的滤波解。最小输出能量算法在保持输出期望信号强度的约束下使输出能量最小化,被证明了与基于训练序列的MMSE算法具有等价的性能,且仅要求期望信号的扩频码信息和码片定时,不需要训练过程,适合于抗干扰通信下的盲干扰抑制问题。本文提出的算法将空-时二维滤波处理与多载波信号频率分集合并处理相结合,当多载波直扩调制使用通用方案时进行非相干合并,在某些特定多载波直扩调制方案下进行相干合并。计算机仿真验证了该方法比单载波直扩信号的空-时最小输出能量算法具有更好的适用范围和干扰抑制能力。
Recently, technology for antenna arrays signal processing has been widely considered due to its strong ability to eliminate spatial interference and to improve the system performance. The incorporation of spectrum spread technology and antenna array is expected to enhance the ability to combat interference, and existing researches mainly focus on the direct-sequence spectrum spread (DS-SS) antenna array system. Multi-carrier spectrum spread (MC-SS) technology has been proven to outperform DS-SS under partial-band interference. Aiming to achieve better performance under jamming, several problems on receiving multi-carrier signal with antenna array have been studied in this dissertation, and the frequency diversity is exploited to construct the relevant receiving algorithms.
First, the antenna array receiving for multi-carrier signal in crowded interference environment is studied, and a receiving algorithm is proposed for this condition. In crowded interference, the number of interference saturates the degree of freedom of beamforming, and the response to the desired signal is not guaranteed, and this results in the difficulty for signal detection and decision. The proposed algorithm estimates the direction of arrival (DoA) using the correlation between the desired components in different sub-carrier channels, and then estimates the spatial distribution of interference with spatial spectrum analysis, and forms the weight vector according to maximum signal-to-jamming-and-noise (SJNR) ratio. The proposed algorithm guarantees a unit response to the desired signal, and place nulls of beampattern in the directions of the clusters of interference. Relevant simulations and discussion are also provided to exam the performance of the proposed algorithm.
To combat a typical jammer in real world - intermittent jammer, a spatial-domain Least Square (LS) algorithm for receiving multi-carrier signal is proposed. Intermittent jammer is randomly on and off at a particular snapshot, and is usually nonstationary, which makes it difficult for statistics-based beamformer to eliminate interference of this kind. Spatial-domain LS methodology processes data of a single snapshot, and was originally designed for RADAR system. The methodology is developed to apply in communications system in this dissertation, with some new advantages: DoA estimate is not necessary, thus the impact of estimate error is eliminated, moreover, coherent multipath is combined to improve the signal quality. In the proposed algorithm, a filter for one sub-channel uses the output of another filter for another sub-channel as the reference, and the outputs of all the filters converge to the desired signal asymptotically and simultaneously due to the correlated desired component in different sub-channels. Simulations show that proposed algorithm meets the expected performance.
Finally, a spatial-temporal constrained minimum output energy (STCMOE) algorithm for multi-carrier signal, spatial-temporal-frequency CMOE (STFCMOE), is proposed, which combines the spatial-temporal (S-T) processing and frequency diversity to provide more degree of freedom for interference suppression. S-T processing employs the spatial directivity and temporal correlation of the desired signal to improve the performance. Constrained minimum output energy (CMOE) methodology minimizes the output energy with the constraint of unit response to the desired signal, which has been proven to have the same performance as training-based MMSE algorithm but only requires the information of spreading code and chip timing for the desired signal, thus CMOE methodology is suitable for blind interference suppression in anti-jamming applications. The proposed algorithm combines the signals from different sub-channels while performing S-T processing. The scheme of noncoherent combining is proposed for generalized multi-carrier system, and the scheme of coherent combining is also given for some specific multi-carrier systems. The simulations present the improvement of the proposed STFCMOE algorithm over STCMOE algorithm, and imply that the proposed STFCMOE algorithm has stronger ability to suppress undesired jamming in much more cases.
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