基于压缩感知的雷达信号处理应用研究

发布时间：2018-10-05 08:05

【摘要】：当前各种雷达体制如相控阵雷达、宽带/超宽带雷达、合成孔径与逆合成孔径雷达等,都采用数字化处理技术从回波中提取目标参数信息。压缩感知理论能够用远低于奈奎斯特(Nyquist)理论的采样速率采集信号、获取离散数据,然后通过非线性重构算法重建信号,是信号处理领域的一个革命性突破。本文对压缩感知在雷达信号处理中的应用展开研究,拟解决目前雷达信号处理中存在的若干问题,主要内容有： (1)远程雷达及多目标跟踪的相控阵雷达对目标跟踪数据率较低,多普勒频率的估计存在模糊问题。本文采用了一种基于压缩感知的随机稀疏脉冲多普勒解模糊新方法。雷达系统只需随机发射稀疏的探测脉冲,通过设计相应的感知矩阵,运用压缩感知重构算法进行信号重建,从而获得无模糊的多普勒频率值。研究分析得出,应用中随机稀疏脉冲的发射时刻设置并非完全随机,还应考虑目标的观测数目和无模糊距离的影响。仿真表明,该方法可以解决远程雷达的多普勒模糊问题,而且大大节省了相控阵雷达的时间资源。 (2)宽带雷达信号的应用需要高速的模拟数字转换器,造成雷达数据量剧增。本文通过采用宽带逆合成孔径雷达成像信号的方位向稀疏脉冲和距离向压缩采样相结合的方法,既节省了雷达时间资源,同时降低了信号采样率和存储传输代价。在成像时运用压缩感知重构算法重建原始信号,再对重构后的成像数据在距离向和方位向分别作信号预测,从而获得超分辨率的雷达图像。 (3)低目标跟踪数据率也给远程雷达的微多普勒测量带来较大困难。本文对低脉冲重复频率条件下的微多普勒提取问题进行研究,提出了一种基于压缩感知的低PRF微多普勒提取方法。该方法仅需对雷达时间资源调度进行微调,通过发射随机探测脉冲串,然后对回波进行压缩感知信号重构和时频分析,获得雷达的微动特征曲线。仿真表明,压缩感知应用于微多普勒特征提取是可行的。
[Abstract]:At present, various radar systems such as phased array radar, wideband / ultra-wideband radar, synthetic aperture radar and inverse synthetic aperture radar all use digital processing technology to extract target parameter information from echo. Compression sensing theory can acquire discrete data at a sampling rate much lower than that of Nyquist (Nyquist) theory, and then reconstruct signals by nonlinear reconstruction algorithm, which is a revolutionary breakthrough in the field of signal processing. In this paper, the application of compressed sensing in radar signal processing is studied, and some problems existing in radar signal processing are solved. The main contents are as follows: (1) the tracking data rate of remote radar and multi-target tracking phased array radar is low, and the estimation of Doppler frequency is fuzzy. In this paper, a new method of random sparse pulse Doppler ambiguity based on compressed sensing is proposed. The radar system only needs to transmit sparse detection pulse randomly. By designing the corresponding sensing matrix and using the compression perception reconstruction algorithm to reconstruct the signal, the Doppler frequency value is obtained without ambiguity. It is concluded that the emission time of the random sparse pulse is not completely random in application, and the effect of the number of observations and the non-fuzzy distance should be taken into account. Simulation results show that this method can solve the Doppler ambiguity problem of remote radar and save the time resource of phased array radar greatly. (2) the application of wideband radar signals requires high speed analog to digital converters, resulting in a sharp increase in radar data. In this paper, the method of combining azimuth sparse pulse and range compression sampling of wideband inverse synthetic aperture radar imaging signal is used to save radar time resource and reduce signal sampling rate and storage transmission cost. The original signal is reconstructed by compression perception reconstruction algorithm, and then the reconstructed image is predicted in the range and azimuth directions respectively, and the super-resolution radar image is obtained. (3) low target tracking data rate also brings great difficulty to micro Doppler measurement of remote radar. In this paper, the problem of micro-Doppler extraction under low pulse repetition rate is studied, and a low PRF micro-Doppler extraction method based on compression sensing is proposed. This method only needs to fine-tune the time resource scheduling of radar and obtain the fretting characteristic curve of radar by transmitting a random detection pulse train and then reconstructing the echo by compressed sensing signal and time-frequency analysis. Simulation results show that compression sensing is feasible for feature extraction of micro Doppler.
【学位授予单位】：厦门大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TN957.51

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