Vol. 83
Latest Volume
All Volumes
PIERL 123 [2025] PIERL 122 [2024] PIERL 121 [2024] PIERL 120 [2024] PIERL 119 [2024] PIERL 118 [2024] PIERL 117 [2024] PIERL 116 [2024] PIERL 115 [2024] PIERL 114 [2023] PIERL 113 [2023] PIERL 112 [2023] PIERL 111 [2023] PIERL 110 [2023] PIERL 109 [2023] PIERL 108 [2023] PIERL 107 [2022] PIERL 106 [2022] PIERL 105 [2022] PIERL 104 [2022] PIERL 103 [2022] PIERL 102 [2022] PIERL 101 [2021] PIERL 100 [2021] PIERL 99 [2021] PIERL 98 [2021] PIERL 97 [2021] PIERL 96 [2021] PIERL 95 [2021] PIERL 94 [2020] PIERL 93 [2020] PIERL 92 [2020] PIERL 91 [2020] PIERL 90 [2020] PIERL 89 [2020] PIERL 88 [2020] PIERL 87 [2019] PIERL 86 [2019] PIERL 85 [2019] PIERL 84 [2019] PIERL 83 [2019] PIERL 82 [2019] PIERL 81 [2019] PIERL 80 [2018] PIERL 79 [2018] PIERL 78 [2018] PIERL 77 [2018] PIERL 76 [2018] PIERL 75 [2018] PIERL 74 [2018] PIERL 73 [2018] PIERL 72 [2018] PIERL 71 [2017] PIERL 70 [2017] PIERL 69 [2017] PIERL 68 [2017] PIERL 67 [2017] PIERL 66 [2017] PIERL 65 [2017] PIERL 64 [2016] PIERL 63 [2016] PIERL 62 [2016] PIERL 61 [2016] PIERL 60 [2016] PIERL 59 [2016] PIERL 58 [2016] PIERL 57 [2015] PIERL 56 [2015] PIERL 55 [2015] PIERL 54 [2015] PIERL 53 [2015] PIERL 52 [2015] PIERL 51 [2015] PIERL 50 [2014] PIERL 49 [2014] PIERL 48 [2014] PIERL 47 [2014] PIERL 46 [2014] PIERL 45 [2014] PIERL 44 [2014] PIERL 43 [2013] PIERL 42 [2013] PIERL 41 [2013] PIERL 40 [2013] PIERL 39 [2013] PIERL 38 [2013] PIERL 37 [2013] PIERL 36 [2013] PIERL 35 [2012] PIERL 34 [2012] PIERL 33 [2012] PIERL 32 [2012] PIERL 31 [2012] PIERL 30 [2012] PIERL 29 [2012] PIERL 28 [2012] PIERL 27 [2011] PIERL 26 [2011] PIERL 25 [2011] PIERL 24 [2011] PIERL 23 [2011] PIERL 22 [2011] PIERL 21 [2011] PIERL 20 [2011] PIERL 19 [2010] PIERL 18 [2010] PIERL 17 [2010] PIERL 16 [2010] PIERL 15 [2010] PIERL 14 [2010] PIERL 13 [2010] PIERL 12 [2009] PIERL 11 [2009] PIERL 10 [2009] PIERL 9 [2009] PIERL 8 [2009] PIERL 7 [2009] PIERL 6 [2009] PIERL 5 [2008] PIERL 4 [2008] PIERL 3 [2008] PIERL 2 [2008] PIERL 1 [2008]
2019-04-15
An Improved Calibration Algorithm for the L-Band 1-d Synthetic Aperture Radiometer
By
Progress In Electromagnetics Research Letters, Vol. 83, 107-114, 2019
Abstract
L-band one-dimensional (1-D) synthetic aperture radiometer is a passive microwave imager that aims to produce global sea surface salinity and soil moisture maps. Two instrument concepts for the L-band 1-D synthetic aperture radiometer have been proposed and selected as candidate payloads for future Chinese space missions, including MICAP (Microwave Imager Combined Active and Passive) for the Chinese Ocean Salinity Mission and IMI (Interferometric Microwave Imager) for the Water Cycle Observation Mission (WCOM). For a synthetic aperture radiometer, spatial imaging error is defined as the difference between the original brightness temperature (BT) and the retrieved BT images within the alias-free field of view (AF-FOV). The main causes of image spatial error in the L-band 1-D system are antenna elements spacing and antenna patterns error. Flat target transformation (FTT) algorithm is always useful for correcting radiometer imaging, but there is still a concave residual error in the retrieved image. An improved calibration algorithm is proposed, which replaces the cold sky view in the FTT with a stable reference scene BT image. A task simulator has been set up to evaluate the new method. The proposed calibration algorithm is shown to reduce the spatial bias and improve the quality of the retrieved BT image.
Citation
Aili Zhang, Hao Liu, and Ji Wu, "An Improved Calibration Algorithm for the L-Band 1-d Synthetic Aperture Radiometer," Progress In Electromagnetics Research Letters, Vol. 83, 107-114, 2019.
doi:10.2528/PIERL19021705
References

1. Corbella, I., "TMIRAS calibration and performance: Results from the SMOS in-orbit commissioning phase," IEEE Transactions on Geoscience and Remote Sensing, Vol. 49, No. 9, 3147-3155, 2011.
doi:10.1109/TGRS.2010.2102769

2. Vine, D. M. L., "Aquarius: An instrument to monitor sea surface salinity from space," IEEE Transactions on Geoscience and Remote Sensing, Vol. 45, No. 7, 2040-2050, 2007.
doi:10.1109/TGRS.2007.898092

3. Piepmeier, J. R., "SMAP L-band microwave radiometer: Instrument design and first year on orbit," IEEE Transactions on Geoscience and Remote Sensing, Vol. 55, No. 4, 1954-1966, 2017.
doi:10.1109/TGRS.2016.2631978

4. Liu, H., X. Zhang, L. Niu, et al. "combined L-band synthetic aperture radiometer and fan-beam scatterometer for soil moisture and Ocean salinity measurement ," 2012 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 4644-4647, Munich, 2012.
doi:10.1109/IGARSS.2012.6350430

5. Niu, L., L. Hao, W. Lin, et al. "Experimental study of an L-band synthetic aperture radiometer for ocean salinity measurement," 2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 418-421, Beijing, 2016.
doi:10.1109/IGARSS.2016.7729103

6. Camps, A., M. Vall-Llossera, I. Corbella, et al. "Improved image reconstruction algorithms for aperture synthesis radiometers," IEEE Transactions on Geoscience and Remote Sensing, Vol. 46, No. 1, 146-158, 2008.
doi:10.1109/TGRS.2007.907603

7. Corbella, I., N. Duffo, et al. "The visibility function in interferometric aperture synthesis radiometry," IEEE Transactions on Geoscience and Remote Sensing, Vol. 42, No. 8, 1677-1682, 2004.
doi:10.1109/TGRS.2004.830641

8. Diez-Garcia, R. and M. Martin-Neira, "Antenna spacing and pattern differences: Their impact in MIRAS reconstruction error," 2016 14th Specialist Meeting on Microwave Radiometry and Remote Sensing of the Environment (MicroRad), 19-24, Espoo, 2016.

9. Martin-Neira, M., M. Suess, J. Kainulainen, et al. "The flat target transformation," IEEE Transactions on Geoscience and Remote Sensing, Vol. 46, No. 3, 613-620, 2008.
doi:10.1109/TGRS.2008.916259

10. Corbella, I., A. Camps, and F. Torres, "Analysis of noise-injection networks for interferometric-radiometer calibration," IEEE Transactions on Microwave Theory and Techniques, Vol. 48, No. 4, 545-552, 2000.
doi:10.1109/22.842026

11. Moreno-Galbis, P., J. Kainulainen, and M. Martin-Neira, "Experimental demonstration of the Corbella equation for aperture synthesis microwave radiometry," IEEE Transactions on Geoscience and Remote Sensing, Vol. 45, No. 4, 945-957, 2007.
doi:10.1109/TGRS.2006.888863

12. Tanner, A. B. and C. T. Swift, "Calibration of a synthetic aperture radiometer," IEEE Transactions on Geoscience and Remote Sensing, Vol. 31, No. 1, 257-267, 1993.
doi:10.1109/36.210465

13. Corbella, I., F. Torres, et al. "Brightness-temperature retrieval methods in synthetic aperture radiometers," IEEE Transactions on Geoscience and Remote Sensing, Vol. 47, No. 1, 285-294, 2009.
doi:10.1109/TGRS.2008.2002911

14. Gourrion, J., R. Sabia, M. Portabella, et al. "Characterization of the SMOS instrumental error pattern correction over the ocean," IEEE Geoscience and Remote Sensing Letters, Vol. 9, No. 4, 793-797, 2012.
doi:10.1109/LGRS.2011.2181990

15. Yin, X., J. Boutin, and P. Spurgeon, "Biases between measured and simulated SMOS brightness temperatures over ocean: Influence of sun," IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol. 6, No. 3, 1341-1350, 2013.
doi:10.1109/JSTARS.2013.2252602