Suppr超能文献

激光多普勒测速仪参数估计及其克拉美-罗下界

Estimation of parameters of a laser Doppler velocimeter and their Cramer-Rao lower bounds.

作者信息

Zhou Jian, Long Xingwu

机构信息

College of Optoelectronic Science and Engineering, National University of Defense Technology, Changsha, China.

出版信息

Appl Opt. 2011 Aug 10;50(23):4594-603. doi: 10.1364/AO.50.004594.

Abstract

Considering the influence of acceleration and the Gaussian envelope for a laser Doppler velocimeter (LDV), parameter estimation of a Doppler signal with a Gaussian envelope was investigated based on introducing acceleration. According to the theory of mathematics statistics, the Cramer-Rao lower bounds (CRLBs) of Doppler circular frequency and its first order rate were analyzed, formulas of CRLBs were given, and the power spectrum estimation with adjustment was discussed. The results of theory and the simulation show that the CRLBs are related to the data length, the signal-to-noise ratio (SNR), and the width of the Gaussian envelope, and they can be decreased by increasing the data length or improving the SNR; the larger the acceleration is and the narrower the Gaussian envelope is, the larger the CRLBs of Doppler circular frequency and its first order rate are; the gap between the variances of the measuring results and the CRLBs narrows when the SNR of the signal is improved, and is almost eliminated when the SNR is higher than 6 dB. It is concluded that the model presented is much more suitable for a LDV than that acquired by Rife and Boorstyn [IEEE Trans. Inform. Theory 20, 591 (1974)].

摘要

考虑到加速度和高斯包络对激光多普勒测速仪(LDV)的影响,基于引入加速度研究了具有高斯包络的多普勒信号的参数估计。根据数理统计理论,分析了多普勒圆频率及其一阶导数的克拉美-罗下界(CRLBs),给出了CRLBs的公式,并讨论了有调整的功率谱估计。理论和仿真结果表明,CRLBs与数据长度、信噪比(SNR)和高斯包络宽度有关,通过增加数据长度或提高SNR可以减小CRLBs;加速度越大且高斯包络越窄,多普勒圆频率及其一阶导数的CRLBs越大;当信号的SNR提高时,测量结果方差与CRLBs之间的差距缩小,当SNR高于6dB时几乎消除。得出的结论是,所提出的模型比Rife和Boorstyn [《IEEE信息论汇刊》20, 591 (1974)] 获得的模型更适合于LDV。

相似文献

1
Estimation of parameters of a laser Doppler velocimeter and their Cramer-Rao lower bounds.
Appl Opt. 2011 Aug 10;50(23):4594-603. doi: 10.1364/AO.50.004594.
2
Cramér-Rao Bounds for DoA Estimation of Sparse Bayesian Learning with the Laplace Prior.
Sensors (Basel). 2022 Dec 28;23(1):307. doi: 10.3390/s23010307.
3
Cramer-Rao bounds for intensity interferometry measurements.
Appl Opt. 2013 Jul 20;52(21):5235-46. doi: 10.1364/AO.52.005235.
4
Self-mixing dual-frequency laser Doppler velocimeter.
Opt Express. 2014 Feb 10;22(3):3600-10. doi: 10.1364/OE.22.003600.
9
Parameter estimation in the magnitude-only and complex-valued fMRI data models.
Neuroimage. 2005 May 1;25(4):1124-32. doi: 10.1016/j.neuroimage.2004.12.048.
10
Cramér-Rao bounds for parametric shape estimation in inverse problems.
IEEE Trans Image Process. 2003;12(1):71-84. doi: 10.1109/TIP.2002.806249.

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验