基于多测量矢量模型的压缩感知雷达时延-多普勒估计

Title  Time Delay and Doppler Estimation of Compressed Sensing Radar
Based on Multiple Measurement Vectors Model
Abstract
Time delay and Doppler estimation is important for radar applications. Compressed sensing (CS) radar can acquire the radar echo with the sub-Nyquist sampling and estimate time delay and Doppler by using sparse reconstruction algorithms. Most of time delay and Doppler estimation for compressed sensing radar is conducted by single measurement vector (SMV) model. However, the SMV model used to estimate the time delay and Doppler information is time-consuming and noise-affected. In radar applications, radar emits continuous pulse train signal with certain pulse repetition interval. The acquired radar echo signal is not only sparse but also   has some inherent structure. It is more suitable to use the Multiple Measurement Vector (MMV) model-based method. In this paper, we apply the MMV model to the time delay and Doppler estimation for compressive sensing radar. According to the MMV model, we firstly recover the coefficient matrix with the same sparse structure by using the MMV-based method. Then the time delay can be estimated by choosing positions of the nonzero coefficients. After that, we estimate Doppler by performing DFT transform on the nonzero coefficients. The performance of the MMV-based time delay and Doppler estimation is analyzed by experiment. It is shown that proves that the estimation based on MMV is superior to that based on SMV both on time-consuming and estimation accuracy. 源自/六"维:论'文;网(加7位QQ3249"114 www.lwfree.cn
Keywords: Compressed Sensing(CS); Single Measurement Vector(SMV)；Multiple Measurement Vector(MMV)；Time Delay Estimation；Doppler Estimation

1  引言1
2  压缩感知模型3
2.1  压缩感知理论的SMV模型3
2.2  压缩感知理论的MMV模型4
3  雷达信号正交压缩采样处理8
3.1  雷达信号模型8
3.2  正交压缩采样9
4  基于MMV模型的雷达时延-多普勒估计 12
4.1  多脉冲雷达信号的MMV模型12
4.2  基于MMV模型的时延-多普勒估计 13
5  仿真15
5.1  仿真环境和参数设置15
5.2  估计性能15

1  引言

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