Yunjun Zhang

Aerospace Engineering · 2019

A researcher in the Science corpus: 1 paper; trusts 10 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Yunjun Zhang trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

  1. Curtis W. Chen
  2. Rowena Lohman
  3. Andrea Virgilio Monti-Guarnieri
  4. Xiaopeng Tong
  5. Howard Allan Zebker
  6. Zhenhong Li
  7. Mark Simons
  8. Stefano Tebaldini
  9. Riccardo Lanari
  10. David T. Sandwell

Papers from Yunjun Zhang's perspective

Ordered by how strongly the researchers Yunjun Zhang trusts endorse each paper. Same corpus, a different order for every researcher.

  1. Radar Interferometry: Data Interpretation and Error Analysis
  2. A new algorithm for surface deformation monitoring based on small baseline differential SAR interferograms (IEEE Transactions on Geoscience and Remote Sensing)
  3. Some thoughts on the use of InSAR data to constrain models of surface deformation: Noise structure and data downsampling
  4. Two-dimensional phase unwrapping with use of statistical models for cost functions in nonlinear optimization. (Journal of The Optical Society of America A-optics Image Science and Vision)
  5. A small-baseline approach for investigating deformations on full-resolution differential SAR interferograms (IEEE Transactions on Geoscience and Remote Sensing)
  6. Advanced InSAR atmospheric correction: MERIS/MODIS combination and stacked water vapour models
  7. On the Exploitation of Target Statistics for SAR Interferometry Applications (IEEE Transactions on Geoscience and Remote Sensing)
  8. Phase unwrapping for large SAR interferograms: statistical segmentation and generalized network models (IEEE Transactions on Geoscience and Remote Sensing)
  9. High‐resolution interseismic velocity data along the San Andreas Fault from GPS and InSAR
  10. Repeat-Pass SAR Interferometry With Partially Coherent Targets (IEEE Transactions on Geoscience and Remote Sensing)

Their papers