Impact of Ocean Waves on Guanlan’s IRA Measurement Error

Bai, Yining; Wang, Yunhua; Zhang, Yanmin; Zhao, Chunjiang; Chen, Ge

doi:10.3390/rs12101534

Cited by 9 publications

(9 citation statements)

References 38 publications

(62 reference statements)

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“…However, in contrast to land, ocean waves have their unique characteristics of movement. According to the InIRA system, the primary factors [44] affecting the ocean waves inversion are velocity bunching and the layover effect. Velocity bunching can produce a substantial nonlinear effect on imaging, and the nonlinear effect is minimized when the WPD along with the ground range.…”

Section: Discussionmentioning

confidence: 99%

Ocean Wave Inversion Based on a Ku/Ka Dual-Band Airborne Interferometric Imaging Radar Altimeter

Pan

Qiu

et al. 2022

Remote Sensing

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Ocean wave parameters (OWPs), including wave propagation direction (WPD), significant wave height (SWH), and main wave wavelength (MWW) can be typically retrieved using an interferometric imaging radar altimeter (InIRA). However, the inversion accuracy of ocean waves in Ku (15.8 GHz) and Ka (35.8 GHz) bands has not yet been evaluated due to the lack of field observation data. In this paper, to assess the inversion accuracy of OWPs in Ku and Ka bands, an airborne observation experiment using simultaneous Ku and Ka bands was carried out for the first time in Rizhao, Shandong Province, China. A dual-band InIRA (DInIRA) was configured with small incidence angles (4°–18°) and a Global Navigation Satellite System (GNSS) buoy; a mobile weather station was placed at the intersection of the plane routes for validation. Afterward, the WPD, SWH, and MWW were retrieved based on the imaging of sea surface height. As compared with the field in situ data, the WPD inversion results of main wind wave were found to be consistent with the measurement environmental wind direction. The SWH inversion biases, retrieved by the Ku and Ka bands, were 0.38 m and 0.27 m; the MWW inversion biases for the swells were equal to 16.75 m and 3.67 m; and the MWW inversion biases about the wind waves were 2.32 m and 0.57 m. Ultimately, it was established that the OWPs could be effectively retrieved by the DInIRA, and the inversion accuracy of the SWH and the MWW in the Ka band outperformed that in the Ku band.

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Section: Discussionmentioning

confidence: 99%

Ocean Wave Inversion Based on a Ku/Ka Dual-Band Airborne Interferometric Imaging Radar Altimeter

Pan

Qiu

et al. 2022

Remote Sensing

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“…Compared with the traditional nadir altimeter, spaceborne near-nadir InSAR can improve the spatial-temporal resolution of SSH observations and effectively make up for the lack of existing ocean observation tools [37]. Currently, many international institutions begin to develop their own wide-swath InSAR altimetry satellites (e.g., SWOT by the NASA [18], InIRA by the NSSCCAS [25], and Guanlan by the NLMSTC [28]), and this is the most promising instrument for future ocean topography measurement. To fulfill the targeted measurement accuracy for ocean scientific research, the error budget and analysis of InSAR altimetry are relatively essential at present.…”

Section: Discussionmentioning

confidence: 99%

“…This will cause differences in the measurement accuracy of InSAR altimetry and is a factor to be considered. Additionally, sea states have a great influence on the accuracy of the SSH retrieved by InSAR [28]. Based on the simulated wave spectrum, the wave height field and wave velocity field of different sea states can be calculated.…”

Section: Experiments Under Multiple Scenariosmentioning

confidence: 99%

“…For the dual-band (Ku-band and Ka-band) IRA on the Guanlan project proposed by the National Laboratory for Marine Science and Technology of China (NLMSTC), the airborne experiments are carried out, and the measurement error of the SSH is ~3 cm under a calm sea state where the significant wave height (SWH) is only 0.2 to 0.3 m. This shows that IRA has great potential for high-accuracy measurement, but it is only under an extreme calm sea state, and also the theoretical error mechanism has not yet been clearly studied [27]. Moreover, the impact of waves on Guanlan's IRA is analyzed and the effects of velocity bunching and layover are numerically simulated [28]. The results demonstrate that the layover has an impact on the interferometric correlation and the velocity bunching will further interfere with the inversion of SSH.…”

Section: Introductionmentioning

confidence: 99%

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An Analytical Method for Dynamic Wave-Related Errors of Interferometric SAR Ocean Altimetry under Multiple Sea States

et al. 2021

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The spaceborne interferometric synthetic aperture radar (InSAR) is expected to measure the sea surface height (SSH) with high accuracy over a wide swath. Since centimeter-level accuracy is required to monitor the ocean sub-mesoscale dynamics, the high accuracy implies that the altimetric errors should be totally understood and strictly controlled. However, for the dynamic waves, they move randomly all the time, and this will lead to significant altimetric errors. This study proposes an analytical method for the dynamic wave-related errors of InSAR SSH measurement based on the wave spectrum and electromagnetic scattering model. Additionally, the mechanisms of the dynamic wave-related errors of InSAR altimetry are analyzed, and the detailed numerical model is derived. The proposed analytical method is validated with NASA’s Surface Water and Ocean Topography (SWOT) project error budget, and the Root-Mean-Square Errors (RMSEs) are in good agreement (0.2486 and 0.2470 cm on a 0.5 km2 grid, respectively). Instead of analysis for a typical project, the proposed method can be applied to different radar parameters under multiple sea states. The RMSEs of Ka-band under low sea state, moderate sea state, and high sea state are 0.2670, 1.3154, and 6.6361 cm, respectively. Moreover, the RMSEs of X-band and Ku-band are also simulated and presented. The experimental results demonstrate that the dynamic wave-related errors of InSAR altimetry are not sensitive to the frequencies but are sensitive to the sea states. The error compensation method is necessary for moderate and higher sea states for centimetric accuracy requirements. This can provide feasible suggestions on system design and error budget for the future interferometric wide-swath altimeter.

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“…Second, the observation errors, especially the Sea-State Bias (SSB) related to surface waves, are under-estimated by the error document and SWOT simulator. Bai et al [37] analyze the impact of sea-state on 2D altimeter measurement errors, and they find that the SSH would be significantly underestimated due to velocity bunching. However, there is no sophisticated error model for SSB to use here.…”

Section: Underlying Assumptions and Biasesmentioning

confidence: 99%

An Investigation of the Influences of SWOT Sampling and Errors on Ocean Eddy Observation

Guo

Zhang

et al. 2020

Remote Sensing

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The mission of Surface Water and Ocean Topography (SWOT) is scheduled to be launchedin 2022, and global ocean eddies with radius scales of larger than 10 km are expected to be observedfrom space. However, there are still open questions about the capability of SWOT to detect oceaneddies. Based on ocean model data and SWOT orbit, this study simulates along-track observationof SWOT. Two eddy datasets are derived from simulated observation data via mapping and eddyidentification procedures, one of which includes SWOT errors and the other does not. The thirdeddy dataset is generated from the original model data. Through comparing these three eddydatasets, it is found that 34% (40%) eddies are lost due to insufficient temporal sampling and errorsin the Kuroshio Extension (South China Sea) region, and numerous artifact eddies are generated.To further explain the influence of SWOT errors on smaller-scale eddies, two eddies (a cyclonic eddyand an anticyclonic eddy) with the radius of about 10 km are repeatedly observed 100 times usingthe SWOT-simulator. The cyclonic eddy with larger amplitude has been detected 84 times, whilethe anticyclonic eddy is visible 76 times. Therefore, the influence of the SWOT sampling and errorson ocean eddy observation is revealed by the results of these observing system simulationexperiments (OSSEs).

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Impact of Ocean Waves on Guanlan’s IRA Measurement Error

Cited by 9 publications

References 38 publications

Ocean Wave Inversion Based on a Ku/Ka Dual-Band Airborne Interferometric Imaging Radar Altimeter

Ocean Wave Inversion Based on a Ku/Ka Dual-Band Airborne Interferometric Imaging Radar Altimeter

An Analytical Method for Dynamic Wave-Related Errors of Interferometric SAR Ocean Altimetry under Multiple Sea States

An Investigation of the Influences of SWOT Sampling and Errors on Ocean Eddy Observation

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