基于激光多普勒测速雷达自相关检测算法研究
发布时间：2018-10-22 17:18
【摘要】：为提高车载激光多普勒测速低信噪比时的测速精度,同时保持较好的实时性,基于自相关检测算法在车载激光多普勒测速中的应用进行了理论与实验研究。从速度估计的克拉美罗下限(CRLB)出发,将自相关后信噪比与采样点数的关系和频域内信噪比估计相结合;不同原始信号的信噪比,可以选取最优重数和采样点数以便对信号进行自相关处理,从而减小计算量,实现系统信噪比和探测概率的提高。仿真和实验结果表明,在信噪比不低于-10dB时,二重自相关可以使系统速度估计精度接近CRLB。
[Abstract]:In order to improve the accuracy of vehicle laser Doppler velocimetry with low signal-to-noise ratio (SNR) and to maintain good real-time performance, the application of auto-correlation detection algorithm in vehicle laser Doppler velocimetry is studied theoretically and experimentally. Based on the Clemero lower bound (CRLB) of velocity estimation, the relationship between autocorrelation post-SNR and sampling points and the estimation of SNR in frequency domain are combined. The optimal number of duplicates and sampling points can be selected for autocorrelation processing of the signal, thus reducing the computational complexity and improving the signal-to-noise ratio and detection probability of the system. The simulation and experimental results show that when SNR is not lower than-10dB, dual autocorrelation can make the system speed estimation accuracy close to CRLB..
【作者单位】： 北京航空航天大学仪器科学与光电工程学院;
【分类号】：TN957.51
本文编号：2287806
[Abstract]:In order to improve the accuracy of vehicle laser Doppler velocimetry with low signal-to-noise ratio (SNR) and to maintain good real-time performance, the application of auto-correlation detection algorithm in vehicle laser Doppler velocimetry is studied theoretically and experimentally. Based on the Clemero lower bound (CRLB) of velocity estimation, the relationship between autocorrelation post-SNR and sampling points and the estimation of SNR in frequency domain are combined. The optimal number of duplicates and sampling points can be selected for autocorrelation processing of the signal, thus reducing the computational complexity and improving the signal-to-noise ratio and detection probability of the system. The simulation and experimental results show that when SNR is not lower than-10dB, dual autocorrelation can make the system speed estimation accuracy close to CRLB..
【作者单位】： 北京航空航天大学仪器科学与光电工程学院;
【分类号】：TN957.51
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