低信噪比下的雷达关联成像技术研究

发布时间：2018-06-02 09:26

本文选题：雷达关联成像 + 低信噪比　；参考：《国防科学技术大学》2014年硕士论文

【摘要】：雷达关联成像是一种新颖的凝视高分辨成像方法,其在低信噪比条件下的成像算法是一个难点问题,具有重要的理论意义和工程实践价值。本文围绕正在组建的雷达关联成像实验系统,建立了噪声条件下的雷达关联成像模型,分析了成像误差影响因素和实验系统噪声环境,研究了低信噪比下对静止目标和运动目标的脉冲积累方法,为实验系统在低信噪比条件下实现对目标准确重构提供了理论参考和方法指导。第一章系统介绍了雷达关联成像的课题背景和研究意义,阐述了雷达关联成像的产生和发展历程,介绍了本文的工作和结构安排。第二章阐述了雷达关联成像的基本理论。首先介绍了雷达关联成像的基本原理,分析了雷达阵列发射的随机调制信号的时间相关性和空间相关性,然后推演了目标所在平面的空时二维随机辐射场,最后分析了理想条件下通过参数化关联成像方法获得目标图像的可行性。第三章分析了噪声条件下的雷达关联成像误差。首先建立了噪声条件下雷达关联成像的参数化模型,通过理论推导得出参数估计误差与接收信号的信噪比、发射信号带宽、目标散射点个数以及回波时延等因素有关,通过仿真实验验证了以上观点的正确性。最后结合系统参数分析了发射通道和接收通道的噪声水平,为稀疏重构算法提供了噪声先验。第四章研究了低信噪比下的雷达关联成像算法。首先分析了稀疏重构算法对低信噪比下雷达关联成像的适用性,然后针对静止目标分析了相参积累的效果,仿真结果和理论推导结果吻合,最后提出了对运动目标的非相参积累方法,解释了脉冲积累没有获得信噪比增益的原因,一定数量的脉冲积累可以提高目标重构质量。最后对全文进行了总结,并提出了下一步的研究方向。
[Abstract]:Radar correlation imaging is a novel staring high-resolution imaging method. Its imaging algorithm under low signal-to-noise ratio (SNR) is a difficult problem and has important theoretical significance and practical value. In this paper, the radar correlation imaging model under the noise condition is established around the radar correlation imaging experimental system, and the influence factors of the imaging error and the noise environment of the experimental system are analyzed. The method of pulse accumulation for stationary and moving targets at low SNR is studied, which provides a theoretical reference and method guidance for the experimental system to realize accurate target reconstruction under low SNR. In the first chapter, the background and significance of radar correlation imaging are introduced systematically, the generation and development of radar correlation imaging are described, and the work and structure of this paper are introduced. The second chapter describes the basic theory of radar correlation imaging. Firstly, the basic principle of radar correlation imaging is introduced, and the temporal and spatial correlation of random modulated signals transmitted by radar array is analyzed, and then the space-time two-dimensional random radiation field of the target plane is deduced. Finally, the feasibility of obtaining target images by parameterized correlation imaging under ideal conditions is analyzed. In chapter 3, the radar correlation imaging error under noise condition is analyzed. Firstly, the parameterized model of radar correlation imaging under noise condition is established. By theoretical derivation, it is concluded that the parameter estimation error is related to the SNR of received signal, the bandwidth of transmitted signal, the number of scattering points of target, and the time delay of echo, etc. The correctness of the above views is verified by simulation experiments. Finally, the noise level of the transmission channel and the receiving channel is analyzed with the system parameters, which provides a noise priori for the sparse reconstruction algorithm. In chapter 4, the algorithm of radar correlation imaging under low signal-to-noise ratio (SNR) is studied. Firstly, the applicability of sparse reconstruction algorithm to radar correlation imaging under low SNR is analyzed, and then the effect of coherent accumulation is analyzed for stationary targets. The simulation results are consistent with the theoretical results. Finally, a non-coherent accumulation method for moving targets is proposed, which explains why the signal to noise ratio gain is not obtained by pulse accumulation, and a certain number of pulse accumulations can improve the quality of target reconstruction. Finally, the paper summarizes the full text and puts forward the next research direction.
【学位授予单位】：国防科学技术大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TN957.52

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