Acta Geodaetica et Cartographica Sinica ›› 2020, Vol. 49 ›› Issue (8): 1023-1031.doi: 10.11947/j.AGCS.2020.20190385

• Photogrammetry and Remote Sensing • Previous Articles     Next Articles

Recursive estimation method of cubature Kalman filtering local polynomial coefficients for phase unwrapping

XIE Xianming, SUN Yuzheng, LIANG Xiaoxing, ZENG Qingning, ZHENG Zhanheng   

  1. School of Information and Communication Engineering, Guilin University of Electronic Technology, Guilin 541004, China
  • Received:2019-09-18 Revised:2020-06-04 Published:2020-08-25
  • Supported by:
    The National Natural Science Foundation of China (NSFC) (Nos. 41661092;61961009);The Guangxi Natural Science Foundation (Nos. 2018GXNSFAA281196;2016GXNSFDA380018);The Ministry of Education Key Lab. Of Cognitive Radio and Information Processing (No. CRK170108);The Dean Project of Guangxi Key Laboratory of Wireless Broadband Communication and Signal Processing (No. GXKL06180102)

Abstract: Recursive estimation method of cubature kalman filtering(CKF) local polynomial coefficients for phase unwrapping is proposed to retrieve unambiguous unwrapping phase from noisy wrapped phase. First, phase gradient information required is obtained using amended matrix pencil model (AMPM), and then the initial state estimation value of the polynomial coefficients is obtained. Finally, the polynomial coefficients are recursively estimated to obtain the unambiguous unwrapping phase by using the cubature Kalman filter. According to the density of the fringes of the interferograms and the signal-to-noise ratio (SNR) of the interferograms, the row-by-row (or column-by-column) scanning modes or the quality-guide strategy applied in traditional algorithms can be used to guide the cubature Kalman filter to unwrap the wrapped pixels along the suitable paths. The results with the simulated data and the measured data demonstrate that the algorithm in this paper can obtain robust solutions from noisy interferograms, with respect to some other similar algorithms.

Key words: phase unwrapping, local polynomial approximation, cubature Kalman filter, gradient estimate

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