Adaptive filtering method for removing engine interference frequency

Author(s):  
Baolin Yu ◽  
Hui Liu ◽  
Yi Zhong
2020 ◽  
Vol 39 (4) ◽  
pp. 5311-5318
Author(s):  
Zhengquan Hu ◽  
Yu Liu ◽  
Xiaowei Niu ◽  
Guoping Lei

As aerospace technology, computer technology, network communication technology and information technology become more and more perfect, a variety of sensors for measurement and remote sensing are constantly emerging, and the ability to acquire remote sensing data is also continuously enhanced. Synthetic Aperture Radar Interferometry (InSAR) technology greatly expands the function and application field of imaging radar. Differential InSAR (DInSAR) developed based on InSAR technology has the advantages of high precision and all-weather compared with traditional measurement methods. However, DInSAR-based deformation monitoring is susceptible to spatiotemporal coherence, orbital errors, atmospheric delays, and elevation errors. Since phase noise is the main error of InSAR, to determine the appropriate filtering parameters, an iterative adaptive filtering method for interferogram is proposed. For the limitation of conventional DInSAR, to improve the accuracy of deformation monitoring as much as possible, this paper proposes a deformation modeling based on ridge estimation and regularization as a constraint condition, and introduces a variance component estimation to optimize the deformation results. The simulation experiment of the iterative adaptive filtering method and the deformation modeling proposed in this paper shows that the deformation information extraction method based on differential synthetic aperture radar has high precision and feasibility.


2018 ◽  
Vol 8 (10) ◽  
pp. 1954 ◽  
Author(s):  
Xing-Ting Xiong ◽  
Xing-Hua Qu ◽  
Fu-Min Zhang

In our frequency scanning interferometry-based (FSI-based) absolute distance measurement system, a frequency sampling method is used to eliminate the influence of laser tuning nonlinearity. However, because the external cavity laser (ECL) has been used for five years, factors such as the mode hopping of the ECL and the low signal-to-noise ratio (SNR) in a non-cooperative target measurement bring new problems, including erroneous sampling points, phase jumps, and interfering signals. This article analyzes the impacts of the erroneous sampling points and interfering signals on the accuracy of measurement, and then proposes an adaptive filtering method to eliminate the influence. In addition, a phase-matching mosaic algorithm is used to eliminate the phase jump, and a segmentation mosaic algorithm is used to improve the data processing speed. The result of the simulation proves the efficiency of our method. In experiments, the measured target was located at eight different positions on a precise guide rail, and the incident angle was 12 degrees. The maximum deviation of the measured results between the FSI-based system and the He-Ne interferometer was 9.6 μm, and the maximum mean square error of our method was 2.4 μm, which approached the Cramer-Rao lower bound (CRLB) of 0.8 μm.


2011 ◽  
Vol 40 (10) ◽  
pp. 1452-1458
Author(s):  
母一宁 MU Yi-ning ◽  
李平 LI Ping ◽  
于林韬 YU Lin-tao ◽  
张国玉 ZHANG Guo-yu ◽  
申春明 SHEN Chun-ming

2017 ◽  
Vol 64 (2) ◽  
pp. 471-478 ◽  
Author(s):  
Yushun Gong ◽  
Peng Gao ◽  
Liang Wei ◽  
Chenxi Dai ◽  
Lei Zhang ◽  
...  

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