{ "id": "epp3vg77he", "slug": "interferometric-imaging", "title": "Interferometric imaging", "updated": "2026-10-15", "topic_path": [ { "id": "physical", "label": "Physical world and mathematics", "api_url": "https://www.edgepedia.org/api/v1/topics/physical" }, { "id": "physical.astronomy", "label": "Astronomy", "api_url": "https://www.edgepedia.org/api/v1/topics/physical.astronomy" }, { "id": "physical.astronomy.cosmos", "label": "Cosmology and observation", "api_url": "https://www.edgepedia.org/api/v1/topics/physical.astronomy.cosmos" }, { "id": "physical.astronomy.cosmos.cosmos.techniques", "label": "Observational techniques: astrometry, photometry, spectroscopy", "api_url": "https://www.edgepedia.org/api/v1/topics/physical.astronomy.cosmos.cosmos.techniques" } ], "geo": [ { "id": "geo.nongeo.t1800.physical.astronomy", "label": "Non-geographic · 1800 to 1945: Astronomy", "api_url": "https://www.edgepedia.org/api/v1/geo/geo.nongeo.t1800.physical.astronomy", "path": [ { "id": "geo.nongeo", "label": "Non-geographic", "api_url": "https://www.edgepedia.org/api/v1/geo/geo.nongeo" }, { "id": "geo.nongeo.t1800", "label": "Non-geographic · 1800 to 1945", "api_url": "https://www.edgepedia.org/api/v1/geo/geo.nongeo.t1800" }, { "id": "geo.nongeo.t1800.physical", "label": "Physical world and mathematics", "api_url": "https://www.edgepedia.org/api/v1/geo/geo.nongeo.t1800.physical" }, { "id": "geo.nongeo.t1800.physical.astronomy", "label": "Astronomy", "api_url": "https://www.edgepedia.org/api/v1/geo/geo.nongeo.t1800.physical.astronomy" } ] }, { "id": "geo.nongeo.t1946.physical.astronomy.cosmos", "label": "Non-geographic · 1946 to 2000: Cosmology and observation", "api_url": "https://www.edgepedia.org/api/v1/geo/geo.nongeo.t1946.physical.astronomy.cosmos", "path": [ { "id": "geo.nongeo", "label": "Non-geographic", "api_url": "https://www.edgepedia.org/api/v1/geo/geo.nongeo" }, { "id": "geo.nongeo.t1946", "label": "Non-geographic · 1946 to 2000", "api_url": "https://www.edgepedia.org/api/v1/geo/geo.nongeo.t1946" }, { "id": "geo.nongeo.t1946.physical", "label": "Physical world and mathematics", "api_url": "https://www.edgepedia.org/api/v1/geo/geo.nongeo.t1946.physical" }, { "id": "geo.nongeo.t1946.physical.astronomy", "label": "Astronomy", "api_url": "https://www.edgepedia.org/api/v1/geo/geo.nongeo.t1946.physical.astronomy" }, { "id": "geo.nongeo.t1946.physical.astronomy.cosmos", "label": "Cosmology and observation", "api_url": "https://www.edgepedia.org/api/v1/geo/geo.nongeo.t1946.physical.astronomy.cosmos" } ] } ], "excerpt": "Interferometric imaging reconstructs an image of a distant or large object by coherently combining signals from separated antennas or apertures, a technique central to radio astronomy and used in InSAR.", "snippet": "Interferometric imaging reconstructs an image of a distant or large object by coherently combining signals from separated antennas or apertures, a technique central to radio astronomy and used in InSAR.", "node": "physical.astronomy.cosmos.cosmos.techniques", "markdown": "# Interferometric imaging\n\nInterferometric imaging reconstructs an image of a distant or large-scale object by coherently combining the signals collected at separated antennas or apertures. Each pair of antennas measures a complex visibility, a sample of the spatial [Fourier transform](https://www.edgepedia.org/fourier-transform) of the image obtained through the mutual coherence function; the van Cittert–Zernike theorem (theorem linking fringe contrast to the image's Fourier components) makes this the basis of interferometric imaging.[1](https://arxiv.org/pdf/0902.0817) An interferometer therefore acts as a Fourier-transform machine, converting a sky intensity distribution into per-baseline Fourier components.[2](https://ar5iv.labs.arxiv.org/html/1201.2963) The same principle, transferred from radio astronomy, underlies interferometric synthetic aperture radar (InSAR), which measures Earth-surface topography and its changes over time.[3](https://igppweb.ucsd.edu/~fialko/insar/rosen_IEEE.pdf)\n\n| Key fact | Value |\n|---|---|\n| Measured quantity | Complex visibility \\( V(u,v) \\), the 2D Fourier transform of sky brightness for small fields, in units of flux density (W m⁻² Hz⁻¹)[4](https://link.springer.com/chapter/10.1007/978-3-319-44431-4_2) |\n| Angular resolution | \\( \\theta = \\lambda/(2B) \\), half the fringe spacing, for wavelength \\( \\lambda \\) and baseline \\( B \\)[5](https://arxiv.org/pdf/2303.00453) |\n| Baselines | \\( n(n-1)/2 \\) for \\( n \\) antennas; Earth's rotation fills the uv-plane[1](https://arxiv.org/pdf/0902.0817) |\n| Dynamic range | CLEAN-processed synthesis images have exceeded \\( 10^{5} \\) to 1[4](https://link.springer.com/chapter/10.1007/978-3-319-44431-4_2) |\n| VLBI resolution | ~7 mas at 1.4 GHz, 200 µas at 43 GHz, 30 µas at 230 GHz for an 8,000 km baseline[6](http://www.aoc.nrao.edu/events/synthesis/2022/slides/SIW2022_Deller_VLBI.pdf) |\n| ALMA | 66 antennas, baselines 15 m to ~16 km, 35–950 GHz (8.5–0.32 mm)[7](https://almascience.hq.eso.org/documents-and-tools/cycle13/alma-technical-handbook) |\n| InSAR displacement sensitivity | ~5 mm for 0.1 rad phase uncertainty; 5 mm/yr for a one-year interferogram[3](https://igppweb.ucsd.edu/~fialko/insar/rosen_IEEE.pdf) |\n\n## How it works\n\nFor small fields of view the complex visibility \\( V(u,v) \\) is the two-dimensional Fourier transform of the brightness on the sky.[4](https://link.springer.com/chapter/10.1007/978-3-319-44431-4_2) The van Cittert–Zernike theorem relates the contrast of an interferometer's fringes to a unique Fourier component of the brightness distribution, the visibility being proportional to the amplitude of the image Fourier component at spatial frequency \\( u = b/\\lambda \\ \\mathrm{rad}^{-1}\\).[8](https://ar5iv.labs.arxiv.org/html/astro-ph/0307036) Two small apertures separated by a baseline \\( B \\) are equivalent in angular resolution to a single aperture of diameter \\( B \\)[9](https://ar5iv.labs.arxiv.org/html/1907.07443); the effective resolution is half the fringe spacing, \\( \\theta = \\lambda/(2B) \\).[5](https://arxiv.org/pdf/2303.00453) Separated apertures can thus match a giant monolithic aperture in resolution.[9](https://ar5iv.labs.arxiv.org/html/1907.07443) As Earth rotates, each projected baseline traces an ellipse in the \\( (u,v) \\) plane whose parameters depend on source declination, baseline length and orientation, and latitude[4](https://link.springer.com/chapter/10.1007/978-3-319-44431-4_2), while \\( n \\) antennas provide \\( n(n-1)/2 \\) simultaneous baselines.[1](https://arxiv.org/pdf/0902.0817)\n\n## How it is done\n\nReference-source calibration, using a comparison source to eliminate both atmospheric and instrumental phase, was first used at Jodrell Bank for OH maser line sources at \\( \\lambda = 18 \\) cm.[10](https://www.nobelprize.org/uploads/2018/06/ryle-lecture.pdf) Self-calibration iteratively solves for antenna-based gains and an improved source model: \\( N \\) antennas give \\( N \\) complex gains but \\( N(N-1)/2 \\) visibilities, a highly overconstrained problem when \\( N \\) is large.[11](https://www.atnf.csiro.au/Radio%20School/2012/lectures/tue/RVU_ImagingDeconvolution.pdf) Weighted visibilities are then convolutionally resampled onto a uv grid with a prolate-spheroidal gridding function, Fourier-inverted, and normalized by the sum of weights.[12](https://casadocs.readthedocs.io/en/stable/notebooks/synthesis_imaging.html)\n\n**Deconvolution** separates the point-spread function from the sky: \\( I_{\\mathrm{obs}} = I_{\\mathrm{PSF}} \\ast I_{\\mathrm{sky}} \\).[11](https://www.atnf.csiro.au/Radio%20School/2012/lectures/tue/RVU_ImagingDeconvolution.pdf) The problem is underdetermined, because any two solutions differ by an \"invisible distribution\" containing only unmeasured spatial frequencies.[13](https://www.gmrt.ncra.tifr.res.in/doc/WEBLF/LFRA/pdf/ch12.pdf) The CASA iterative framework is based on the Cotton-Schwab CLEAN algorithm, with Högbom and Clark CLEAN as subsets; major cycles predict visibilities and construct residual images, minor cycles deconvolve in the image domain.[12](https://casadocs.readthedocs.io/en/stable/notebooks/synthesis_imaging.html) The Maximum Entropy Method is used in astronomy, alongside CLEAN.[13](https://www.gmrt.ncra.tifr.res.in/doc/WEBLF/LFRA/pdf/ch12.pdf) Regularized maximum-likelihood pipelines typically progress from the bispectrum, most robust to errors, to amplitude plus closure phase, to self-calibrated visibilities.[14](https://eris2026.ira.inaf.it/imagingalgorithms.html) The final component list is restored by smoothing with a Gaussian matching the PSF main lobe and adding back the residual image[12](https://casadocs.readthedocs.io/en/stable/notebooks/synthesis_imaging.html); because of this restoring step, CLEAN cannot achieve super-resolution beyond the PSF resolution.[15](https://www.arxiv.org/pdf/2603.09162)\n\n## Origin\n\nMeasuring stellar sizes can be done by dividing a telescope pupil into sub-apertures.[5](https://arxiv.org/pdf/2303.00453) Fringe visibility and the Fourier equations for measuring stellar diameters were defined.[16](https://link.springer.com/chapter/10.1007/978-3-031-07916-0_37) Michelson and Pease measured the diameter of [Betelgeuse](https://www.edgepedia.org/betelgeuse), 0.047 arcsec, with a baseline reported as 7 m on the Mount Wilson 2.5 m telescope.[9](https://ar5iv.labs.arxiv.org/html/1907.07443) In 1946 a two-element radio interferometer with about 0.5 km maximum spacing was built in Cambridge to measure the diameter of the Sun[17](https://people.ast.cam.ac.uk/~bothwell/Files/annurev.astro.39.1.457.pdf), and Solar interferometric observations were published in Nature that year.[16](https://link.springer.com/chapter/10.1007/978-3-031-07916-0_37) The first synthesis instrument capable of mapping an arbitrary field of sources was built at Cambridge in 1954, its observations reduced on EDSAC I at about 15 hours of computing per 38-point transform.[10](https://www.nobelprize.org/uploads/2018/06/ryle-lecture.pdf) [The One](https://www.edgepedia.org/the-one)-Mile Telescope synthesized an effective aperture 1 mile in diameter from 64 locations spaced 23.5 m apart.[17](https://people.ast.cam.ac.uk/~bothwell/Files/annurev.astro.39.1.457.pdf) • [18](https://www.sciencedirect.com/science/article/abs/pii/S1387647310000060) The analysis of the intensity interferometer for stellar diameters was published in the Proceedings of the Royal Society A, showing the technique should be substantially unaffected by atmospheric scintillation.[19](https://royalsocietypublishing.org/doi/10.1098/rspa.1958.0239) The phase-closure relations apply for three or more antennas.[16](https://link.springer.com/chapter/10.1007/978-3-031-07916-0_37)\n\n## Variants\n\nConnected-element arrays such as ALMA, a 66-antenna aperture-synthesis array with baselines from 15 m to ~16 km covering 35–950 GHz[7](https://almascience.hq.eso.org/documents-and-tools/cycle13/alma-technical-handbook), and the VLA[20](https://science.nrao.edu/facilities/vla/docs/manuals/oss2024A/performance/resolution) exemplify connected-element interferometry. In very long baseline interferometry (VLBI), current arrays include the VLBA (ten 25 m antennas, 0.3–86 GHz, ~8,000 km baselines), the EVN (~25 stations, 0.3–43 GHz), and the GMVA (sub-mas at 86 GHz with ALMA available).[6](http://www.aoc.nrao.edu/events/synthesis/2022/slides/SIW2022_Deller_VLBI.pdf) In optical/IR interferometry, the first successful direct interference of stellar light beams from separated telescopes was achieved in 1974[2](https://ar5iv.labs.arxiv.org/html/1201.2963), and the COAST interferometer produced the first image from an optical aperture-synthesis array.[8](https://ar5iv.labs.arxiv.org/html/astro-ph/0307036) [Intensity interferometry](https://www.edgepedia.org/intensity-interferometry) measures second-order spatial coherence (squared visibility) and is insensitive to atmospheric turbulence.[21](https://arxiv.org/pdf/1607.03490) InSAR variants include cross-track interferometry, first applied to Earth observation with an airborne displaced antenna; along-track interferometry for surface motion; and repeat-pass orbital interferometry.[3](https://igppweb.ucsd.edu/~fialko/insar/rosen_IEEE.pdf)\n\nAmong reconstruction algorithms, Multi-Scale CLEAN was introduced by Cornwell (2008) in arXiv[22](https://doi.org/10.48550/arxiv.0806.2228), and Multi-Scale Multi-[Frequency synthesis](https://www.edgepedia.org/frequency-synthesis) (MSMFS) models the wideband sky as inverted tapered [paraboloids](https://www.edgepedia.org/paraboloid) of different scale sizes whose amplitudes follow a polynomial in frequency.[12](https://casadocs.readthedocs.io/en/stable/notebooks/synthesis_imaging.html) A unified formalism for interferometric image reconstruction using closure invariants and machine learning was reported by Thyagarajan, Hoefs, and Wong (2023) in arXiv.[23](https://doi.org/10.48550/arxiv.2311.06349) The kine algorithm reconstructs polarimetric time-continuous videos from VLBI observations of variable sources using a neural representation, working with complex visibilities, closure phases \\( \\Phi_{ABC} := \\arg(V_{AB} \\cdot V_{BC} \\cdot V_{CA}) \\), and closure amplitudes \\( A_{ABCD} := |V_{AB} \\cdot V_{CD}| / |V_{AC} \\cdot V_{BD}| \\).[24](https://www.nature.com/articles/s41586-026-10988-5) Hierarchical Interferometric Bayesian Imaging (HIBI) enables uncertainty quantification for all parameters and simultaneous imaging and calibration; where the original EHT publications could not constrain the ring width of M87*, HIBI measures 9.3 ± 1.3 µas.[25](https://iopscience.iop.org/article/10.3847/1538-4357/ae2749) KRISP reconstructs the complete Fourier map by kernel regression, inserting zero-visibility \"ghost\" points between \\( b_{\\max} \\) and \\( 2 b_{\\max} \\) to suppress unobserved high spatial frequencies.[26](https://arxiv.org/html/2412.01908)\n\n## Applications\n\nVLBI astrometry centroids sources to the ~0.01 mas level, and global geodesy measures participating telescope positions to the millimeter level and [Earth's rotation](https://www.edgepedia.org/earths-rotation) phase (UT1−UTC) to ~4 microseconds daily.[6](http://www.aoc.nrao.edu/events/synthesis/2022/slides/SIW2022_Deller_VLBI.pdf) Optical/IR arrays resolve stellar surfaces and diameters, as the Narrabri intensity interferometer did for 32 blue stars.[9](https://ar5iv.labs.arxiv.org/html/1907.07443) InSAR measures surface topography and change: a 0.1 rad phase uncertainty corresponds to ~5 mm of displacement, and a one-year interferogram gives 5 mm/yr sensitivity.[3](https://igppweb.ucsd.edu/~fialko/insar/rosen_IEEE.pdf)\n\n## Limitations and alternatives\n\n**Missing short spacings.** Without total-power (zero-spacing) data a synthesis image integrates to zero and sits on a negative \"floor\" or \"bowl\", the short-spacing problem, which degrades photometric accuracy.[2](https://ar5iv.labs.arxiv.org/html/1201.2963) An interferometer cannot measure scales larger than \\( \\theta_{\\max} \\sim \\lambda/b_{\\min} \\), and because baselines cannot be shorter than the dish diameter \\( D \\), \\( \\theta_{\\max} \\) can never exceed \\( \\lambda/D \\).[27](https://ar5iv.labs.arxiv.org/html/2006.06549) Remedies include ALMA's 7 m and total-power antennas, which bridge the zero-spacing gap[7](https://almascience.hq.eso.org/documents-and-tools/cycle13/alma-technical-handbook); single-dish combination methods that significantly improve flux recovery[28](https://beta.iopscience.iop.org/article/10.1088/1538-3873/acb9bd); mosaicking, which reaches spatial frequencies down to \\( (b_{\\min} - D)/\\lambda \\)[27](https://ar5iv.labs.arxiv.org/html/2006.06549); and feathering of single-dish and interferometric maps in the uv plane.[27](https://ar5iv.labs.arxiv.org/html/2006.06549)\n\n**Atmospheric decoherence.** At 500 nm the Fried parameter \\( r_{0} \\) is typically 10 cm toward zenith at average sites.[8](https://ar5iv.labs.arxiv.org/html/astro-ph/0307036) Atmospheric turbulence corrupts fringe phase so it can no longer be directly associated with the Fourier phase of the sky, but closure-phase techniques allow reconstruction of images of asymmetric objects.[8](https://ar5iv.labs.arxiv.org/html/astro-ph/0307036) • [31](https://www.quantastro.bnl.gov/sites/default/files/2023-05/InterferometryReveiewMonnier2303.00453.pdf) The product of coherence length and coherence time in the O/IR is about \\( 10^{6} \\)–\\( 10^{8} \\) smaller than in the radio, and there are no low-noise heterodyne mixers, making O/IR interferometry far more demanding.[5](https://arxiv.org/pdf/2303.00453)\n\n**Sparse coverage and calibration.** Optical arrays recombine few telescopes, giving sparse Fourier coverage and a non-convex inverse problem built on non-linear observables such as closure phase.[29](https://ar5iv.labs.arxiv.org/html/1708.08390) Closure-phase imaging allows only modest dynamic ranges, whereas radio-style phase referencing should theoretically do better for the same number of telescopes.[30](https://ar5iv.labs.arxiv.org/html/0810.0545) Compared with direct imaging by a large monolithic telescope, interferometry matches its resolution with small apertures[9](https://ar5iv.labs.arxiv.org/html/1907.07443) but pays a large sensitivity penalty.[2](https://ar5iv.labs.arxiv.org/html/1201.2963)\n\n## References\n\n1. [Advances in Calibration and Imaging Techniques in Radio Interferometry](https://arxiv.org/pdf/0902.0817)\n2. [Radio & Optical Interferometry: Basic Observing Techniques and Data Analysis](https://ar5iv.labs.arxiv.org/html/1201.2963)\n3. [Synthetic Aperture Radar Interferometry (Proceedings of the IEEE)](https://igppweb.ucsd.edu/~fialko/insar/rosen_IEEE.pdf)\n4. [Introductory Theory of Interferometry and Synthesis Imaging (Thompson, Moran & Swenson, 3rd ed., Ch. 2)](https://link.springer.com/chapter/10.1007/978-3-319-44431-4_2)\n5. [Infrared Interferometry (review)](https://arxiv.org/pdf/2303.00453)\n6. [Very Long Baseline Interferometry (Adam Deller, 18th NRAO Synthesis Imaging Workshop, May 2022)](http://www.aoc.nrao.edu/events/synthesis/2022/slides/SIW2022_Deller_VLBI.pdf)\n7. [ALMA Cycle 13 Technical Handbook](https://almascience.hq.eso.org/documents-and-tools/cycle13/alma-technical-handbook)\n8. [Optical Interferometry in Astronomy](https://ar5iv.labs.arxiv.org/html/astro-ph/0307036)\n9. [Introduction to optical/IR interferometry: history and basic principles](https://ar5iv.labs.arxiv.org/html/1907.07443)\n10. [Martin Ryle - Nobel Lecture](https://www.nobelprize.org/uploads/2018/06/ryle-lecture.pdf)\n11. [Imaging and Deconvolution (Ravi V. U., ATNF Radio School 2012)](https://www.atnf.csiro.au/Radio%20School/2012/lectures/tue/RVU_ImagingDeconvolution.pdf)\n12. [CASA Documentation: Synthesis Imaging and Image Reconstruction](https://casadocs.readthedocs.io/en/stable/notebooks/synthesis_imaging.html)\n13. [Deconvolution in synthesis imaging – an introduction (GMRT low-frequency radio astronomy chapter)](https://www.gmrt.ncra.tifr.res.in/doc/WEBLF/LFRA/pdf/ch12.pdf)\n14. [ERIS2026, New generation imaging algorithms: Hands-on with eht-imaging](https://eris2026.ira.inaf.it/imagingalgorithms.html)\n15. [POLISH++: deep learning radio interferometric imaging](https://www.arxiv.org/pdf/2603.09162)\n16. [The Evolution of Aperture Synthesis Imaging](https://link.springer.com/chapter/10.1007/978-3-031-07916-0_37)\n17. [High-Resolution Radio Astronomy (Annual Review of Astronomy and Astrophysics)](https://people.ast.cam.ac.uk/~bothwell/Files/annurev.astro.39.1.457.pdf)\n18. [A short introduction to radio interferometric image reconstruction](https://www.sciencedirect.com/science/article/abs/pii/S1387647310000060)\n19. [Interferometry of the intensity fluctuations in light III. Applications to astronomy (Hanbury Brown & Twiss)](https://royalsocietypublishing.org/doi/10.1098/rspa.1958.0239)\n20. [Resolution, NRAO Science Site (VLA Observational Status Summary 2024A)](https://science.nrao.edu/facilities/vla/docs/manuals/oss2024A/performance/resolution)\n21. [Intensity interferometry: Optical imaging with kilometer baselines](https://arxiv.org/pdf/1607.03490)\n22. [Cornwell, T. J. (2008). Multi-Scale CLEAN deconvolution of radio synthesis images. arXiv (Cornell University).](https://doi.org/10.48550/arxiv.0806.2228)\n23. [Thyagarajan, Nithyanandan, Hoefs, Lucas, Wong, O. Ivy (2023). Interferometric Image Reconstruction using Closure Invariants and Machine Learning. arXiv (Cornell University).](https://doi.org/10.48550/arxiv.2311.06349)\n24. [Video reconstruction of variable VLBI observations with neural fields (kine)](https://www.nature.com/articles/s41586-026-10988-5)\n25. [Hierarchical Interferometric Bayesian Imaging (HIBI)](https://iopscience.iop.org/article/10.3847/1538-4357/ae2749)\n26. [Kernel Methods for Interferometric Imaging (KRISP)](https://arxiv.org/html/2412.01908)\n27. [Imaging Spatially Extended Objects with Interferometers: Mosaicking and the Short Spacing Correction](https://ar5iv.labs.arxiv.org/html/2006.06549)\n28. [Data Combination: Interferometry and Single-dish Imaging in Radio Astronomy (PASP)](https://beta.iopscience.iop.org/article/10.1088/1538-3873/acb9bd)\n29. [Principles of image reconstruction in optical interferometry: tutorial](https://ar5iv.labs.arxiv.org/html/1708.08390)\n30. [Phase Referencing in Optical Interferometry](https://ar5iv.labs.arxiv.org/html/0810.0545)\n31. [quantastro.bnl.gov](https://www.quantastro.bnl.gov/sites/default/files/2023-05/InterferometryReveiewMonnier2303.00453.pdf)\n\n---\n*Topic: Encyclopedia › Physical world and mathematics › Astronomy › Cosmology and observation › Observational techniques: astrometry, photometry, spectroscopy*\n\n*Initially written Sep 29, 2026 · Edited: Oct 15, 2026*\n\n*Copyright 2026 EdgeChat AI, a subsidiary of Biostate AI.*\n\nLicense: Edgepedia Community License 1.0, https://www.edgepedia.org/edgepedia/license\n", "same_as": [ "https://igppweb.ucsd.edu/~fialko/insar/rosen_IEEE.pdf" ], "url": "https://www.edgepedia.org/interferometric-imaging", "markdown_url": "https://www.edgepedia.org/interferometric-imaging.md", "license": { "name": "Edgepedia Community License 1.0", "url": "https://www.edgepedia.org/edgepedia/license", "summary": "Free with credit, commercial use included. AI training is open to everyone. For other uses, organizations over USD 100M in revenue or 100M monthly users license separately.", "spdx": "LicenseRef-Edgepedia-Community-1.0" }, "credit": "\"Interferometric imaging\", Edgepedia (EdgeChat), https://www.edgepedia.org/interferometric-imaging. Edgepedia Community License 1.0.", "credit_md": "\"[Interferometric imaging](https://www.edgepedia.org/interferometric-imaging)\", Edgepedia (EdgeChat), [https://www.edgepedia.org/interferometric-imaging](https://www.edgepedia.org/interferometric-imaging). [Edgepedia Community License 1.0](https://www.edgepedia.org/edgepedia/license).", "credit_html": "\"Interferometric imaging\", Edgepedia (EdgeChat), https://www.edgepedia.org/interferometric-imaging. Edgepedia Community License 1.0.", "speakable": "Interferometric imaging reconstructs an image of a distant or large object by coherently combining signals from separated antennas or apertures, a technique central to radio astronomy and used in InSAR." }