常规通信信号调制识别系统的设计与硬件实现

发布时间：2018-09-19 18:05

【摘要】：调制类型是通信信号的一个重要的特征,随着无线通信技术的发展,调制类型日益复杂。传统基于人工的调制识别技术已经不能满足实际的需求,使用DSP、FPGA和软件无线电技术的自动调制识别成为一种趋势。自动调制识别技术被广泛运用于舰船电磁干扰监测、无线电监听等领域。本文研究了通信信号调制参数估计和调制识别的基本原理。针对2ASK、4ASK、2FSK、4FSK、2PSK、AM、FM、LSB和USB共九种调制信号,提出了一种基于瞬时统计特征和决策树分类器的调制识别算法。相比以往的算法,本文的算法优势在于能够满足实际硬件实现时所需的速度快、所需采样点少、适合随机码元条件。识别算法使用一种新的中心化参数,改善了{2ASK,4ASK}和{2FSK,4FSK}识别效果。使用一种门限自动调节算法,通过选取信噪比参考参数,实现信噪比的粗估计,使得判决门限可以自动调整,提高了识别算法对信噪比的适应性。相比于以往很多算法,本算法在载波频率未知的情况下依然有效,利用高精度的载频估计算法-CZT变换法获取信号的载波频率,以满足提取非线性相位的精度要求。通过MATLAB仿真,在采样点为1024(16个随机码元)、未知载频条件下,验证了本算法具有较好的效果。在信噪比不小于10dB时,平均识别正确率达到93.27%,在SNR不小于15dB时,平均识别率超过99.0%。设计完成了基于DSP+FPGA结构的调制识别的硬件平台,完成了硬件电路的原理图和PCB设计工作。对DSP板进行了信号完整性分析(SI),使用SigXploer完成了部分电路的SI仿真,以保证硬件电路运行的稳定性和可靠性,并完成了硬件平台的调试工作。在CCS平台下对识别算法的C语言程序进行了软件仿真,统计了识别算法的识别率。最后使用所设计硬件平台对信号发生器产生的5种调制信号进行了实时识别,达到了预期效果。
[Abstract]:Modulation type is an important characteristic of communication signal. With the development of wireless communication technology, modulation type is becoming more and more complex. The traditional manual modulation recognition technology can not meet the actual needs. Automatic modulation recognition using DSP,FPGA and software radio technology has become a trend. Automatic modulation recognition technology is widely used in ship electromagnetic interference monitoring, radio monitoring and other fields. The basic principle of modulation parameter estimation and modulation recognition of communication signal is studied in this paper. This paper presents a modulation recognition algorithm based on instantaneous statistical features and decision tree classifier for nine kinds of modulation signals, 2ASK / 4ASK / 2FSKC / 4FSKK / 2PSK / AMK / FM / USB, which are based on instantaneous statistical features and decision tree classifier. Compared with the previous algorithms, the advantage of this algorithm is that it can meet the needs of fast hardware implementation, less sampling points, and suitable for random symbol conditions. The recognition algorithm uses a new centralization parameter to improve the recognition effect of {2ASK _ 4ASK} and {2FSKN _ 4FSK}. A threshold automatic adjustment algorithm is used to estimate the SNR by selecting the reference parameters of SNR. The decision threshold can be adjusted automatically and the adaptability of the recognition algorithm to SNR is improved. Compared with many previous algorithms, this algorithm is still effective in the case of unknown carrier frequency. The high accuracy carrier frequency estimation algorithm CZT transform is used to obtain the carrier frequency of the signal to satisfy the precision requirement of extracting nonlinear phase. The MATLAB simulation shows that the proposed algorithm is effective under the condition that the sampling point is 1024 (16 random symbols) and the carrier frequency is unknown. The average recognition accuracy is 93.27 when the SNR is not less than 10dB, and 99.0 when SNR is not less than 15dB. The hardware platform of modulation recognition based on DSP FPGA structure is designed. The schematic diagram of hardware circuit and the design of PCB are completed. Signal Integrity Analysis of DSP Board (SI), completes the SI simulation of part of the circuit using SigXploer to ensure the stability and reliability of the hardware circuit, and completes the debugging of the hardware platform. The C language program of the recognition algorithm is simulated on the CCS platform, and the recognition rate of the recognition algorithm is calculated. Finally, the designed hardware platform is used to identify the five modulation signals produced by the signal generator in real time, and the desired results are achieved.
【学位授予单位】：哈尔滨工程大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TN911.3

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