多节点协同信号调制识别与参数估计关键技术研究与实现

发布时间：2019-02-12 07:06

【摘要】：随着无线通信技术的快速发展,电磁环境日益复杂,电磁频谱监测对于频谱资源的优化管理发挥着越来越重要的作用,而网络化的电磁频谱监测因其独特优势日益受到关注。调制识别和参数估计是电磁频谱监测中的关键技术,而现有研究大都基于单个监测节点。如何在网络化的监测系统中利用多个节点进行协同式的调制识别和参数估计已经成为了一个重要问题。本文围绕这一问题,研究了利用信号特征层信息的多节点协同调制识别和参数估计方法,并进行了相关工程实现。论文主要工作和创新点有以下三个方面：1.针对基于特征层的多节点协同方法在低信噪比时性能提升有限和监测节点能量受限的问题,提出了一种基于高阶累积量特征的改进方法。本章首先针对信号集合{4ASK、 2PSK、4PSK、8PSK、6QAM}提出了四个高阶累积量特征,在单节点时分别利用决策树分类器和支持向量机分类器对特征组合完成了分类,并进行了性能比较。然后结合已提出的高阶累积量特征,针对已有多节点方法的不足,提出了一种改进的多节点协同方法。根据高阶累积量特征的抗噪声性能和计算特点来设计协同策略,能够在保证性能的前提下最小化节点平均运算量,并且每个特征只被提取一次。仿真结果表明,在不同信噪比环境下改进方法的识别性能优于原方法,并且降低了运算量。2.针对低信噪比时已有符号速率估计方法性能较差的问题,提出了一种含有符号速率信息的信号特征谱,通过提取特征谱线完成符号速率估计。并结合此特征谱对时延、频偏、相偏不敏感的特性,设计了基于谱合成的多节点协同符号速率估计方法。首先利用模平方后信号的频谱在符号速率处存在离散谱线的特点,计算模平方后信号以采样倍数为横坐标、傅立叶系数模值为纵坐标的特征谱,通过特定的谱线提取方法搜索对应符号速率的特征谱线,进而完成符号速率估计。该方法适用于MASK、MPSK、MQAM信号。仿真结果表明,本文方法的符号速率估计性能优于haar小波变换和循环谱方法；相比循环谱方法有效降低了运算量。然后利用此特征谱提出了一种基于谱合成的多节点协同符号速率估计方法。根据各节点接收信号的信噪比计算权值并对多个节点的特征谱加权合成,利用合成谱进行符号速率估计。仿真结果表明,特征谱合成方法的估计性能优于特征值合成方法和单节点方法。3.多节点协同电磁频谱监测系统的设计与实现。本章在前文理论研究的基础上,结合电磁频谱监测的功能需求,设计并实现了多节点协同电磁频谱监测系统。首先设计了系统总体方案,包括网络结构、监测节点结构、信号处理单元的处理流程和硬件平台；然后针对信号处理流程,完成了信号检测、调制识别、参数估计等算法的DSP程序设计。结合系统功能需求,设计了DSP的接口模块和多任务模块,并进行了相应调试。最后通过功能测试和实际业务测试对系统进行了检验,检验结果符合理论研究,并达到了预期的指标要求,验证了整套系统的可行性。
[Abstract]:With the rapid development of the wireless communication technology, the electromagnetic environment is becoming more and more complex, and the electromagnetic spectrum monitoring plays a more and more important role in the optimization management of the spectrum resources, and the network-based electromagnetic spectrum monitoring is increasingly concerned by its unique advantages. Modulation identification and parameter estimation are the key technologies in electromagnetic spectrum monitoring, and most of the existing research is based on a single monitoring node. How to use multiple nodes in the networked monitoring system to carry out cooperative modulation identification and parameter estimation has become an important problem. In this paper, the method of multi-node cooperative modulation recognition and parameter estimation using signal characteristic layer information is studied in this paper, and the related engineering implementation is carried out. The main work and innovation point of the thesis have the following three aspects: 1. In order to solve the problem of limited performance and limited energy of the monitoring node in the low signal-to-noise ratio of the multi-node cooperative method based on the characteristic layer, an improved method based on the high-order cumulant feature is proposed. In this chapter, four high-order cumulant features are proposed for signal set {4ASK, 2PSK, 4PSK, 8PSK, and 6QAM}. and then combining the proposed high-order cumulant features, aiming at the shortcomings of the existing multi-node method, an improved multi-node coordination method is proposed. according to the anti-noise performance and the calculation characteristic of the high-order cumulant feature, the average operation amount of the node can be minimized under the premise of ensuring the performance, and each feature is only extracted once. The simulation results show that the improved method is better than the original method in the different signal-to-noise ratio environment, and the calculation amount is reduced. Aiming at the problem of poor performance of the existing symbol rate estimation method in low signal-to-noise ratio, a signal characteristic spectrum with symbol rate information is proposed, and the symbol rate estimation is completed by extracting the characteristic spectrum line. and combining the characteristic spectrum to the characteristics of time delay, frequency offset and phase deviation, and the method for estimating the multi-node cooperative symbol rate based on the spectrum synthesis is designed. firstly, the characteristic of a discrete spectral line is existed at the symbol rate by utilizing the frequency spectrum of the signal after the square of the mould, the signal is taken as the abscissa and the Fourier coefficient mode value is the characteristic spectrum of the ordinate, the characteristic spectrum line corresponding to the symbol rate is searched by a specific spectral line extraction method, and then the symbol rate estimation is completed. The method is suitable for MASK, MPSK and MQAM signals. The simulation results show that the symbol rate estimation performance of the method is better than the haar wavelet transform and the cyclic spectrum method, and the calculation amount is effectively reduced compared with the cyclic spectrum method. and then a multi-node cooperative symbol rate estimation method based on the spectrum synthesis is provided by using the characteristic spectrum. according to the signal-to-noise ratio calculation weight value of each node receiving signal and weighting the characteristic spectrum of a plurality of nodes, and carrying out symbol rate estimation by using the composite spectrum. The simulation results show that the estimation performance of the characteristic spectrum synthesis method is better than that of the feature value synthesis method and the single node method. Design and implementation of multi-node cooperative electromagnetic spectrum monitoring system. In this chapter, based on the research of the previous text, the multi-node cooperative electromagnetic spectrum monitoring system is designed and implemented in combination with the function requirement of the electromagnetic spectrum monitoring. The general scheme of the system is firstly designed, including the network structure, the monitoring node structure, the processing flow and the hardware platform of the signal processing unit, and then the DSP programming of the algorithm such as signal detection, modulation recognition and parameter estimation is completed for the signal processing flow. Based on the functional requirements of the system, the interface module and the multi-task module of the DSP are designed, and the corresponding debugging is carried out. Finally, the system is tested by the function test and the actual service test, the result of the test is in accordance with the theoretical study, and the expected index requirements are met, and the feasibility of the whole system is verified.
【学位授予单位】：解放军信息工程大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TN911.3

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