Radargrammetric 3D Positioning of Pseudo Corner-Reflector Scatterers in KOMPSAT-5 Stacks with Per-Target Conditioning Diagnostics.
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| Title: | Radargrammetric 3D Positioning of Pseudo Corner-Reflector Scatterers in KOMPSAT-5 Stacks with Per-Target Conditioning Diagnostics. |
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| Authors: | Han, Dongyeob1 (AUTHOR), Lee, Hyoseong2 (AUTHOR), Yang, Dochul3 (AUTHOR) dcyang@kari.re.kr |
| Source: | Remote Sensing. Sep2026, Vol. 18 Issue 17, p2889. 24p. |
| Subjects: | Synthetic aperture radar, Constant false alarm rate (Data processing) |
| Geographic Terms: | South Korea, Mongolia |
| Abstract: | Highlights: What are the main findings? An integrated pseudo-CR pipeline (CFAR ranked by local contrast, multi-scale templates, and multi-look range-Doppler triangulation with per-target conditioning diagnostics) reaches 0.7–2.9 m 3D accuracy on nine KOMPSAT-5 Mongolia corner reflectors. At a corner-reflector-absent suburban site, 16 surveyed distribution poles that formed stable multi-scene responses are positioned to a mean horizontal difference of 3.19 m from the surveyed pole base; on that response-enriched set, ranking candidates by local contrast retains more of those responses than ranking by absolute power at equal candidate budgets. What are the implications? Natural pole-like scatterers that form stable multi-scene responses and can be associated with a specific structure are candidate reference features where no dedicated CRs exist. Per-target conditioning diagnostics, adapted from stereo-SAR practice to mid-resolution KOMPSAT-5 stacks, describe how well the observing geometry determines each solution and flag weak conditioning where no ground control is available. Spaceborne synthetic aperture radar (SAR) needs point-like reference targets for co-registration, calibration, and absolute geolocation, but real corner reflectors (CRs) exist only at a few dedicated sites. We present a detection and three-dimensional (3D) positioning pipeline for naturally occurring corner-reflector-like (pseudo-CR) scatterers in KOMPSAT-5 stacks, combining constant false alarm rate (CFAR) detection ranked by local contrast rather than absolute power, a multi-scale template bank, multi-look range-Doppler bundle triangulation, and a per-target conditioning diagnostic vector. At the nine-CR Mongolia calibration field, all nine are recovered, with a mean horizontal error of 1.37 m and a mean 3D error of 2.01 m. At a CR-absent suburban site in Suncheon, Republic of Korea, 18 scenes yield 39,822 clusters, 26,659 of which pass the conditioning gate. Over 16 response-enriched poles retained by author adjudication, the difference to the nearest conditioning-filtered cluster averages 3.19 m horizontally and 1.45 m vertically relative to the surveyed pole base. Because part of that set was selected after inspecting preliminary responses, these are conditional nearest-cluster agreements, not verified target accuracies, and no detection probability is claimed. In an exploratory comparison on the same set, contrast ranking retains more evaluation targets than power ranking at equal budgets, 16 against 9 of 16. Removing robust weighting and pruning degrades the mean Mongolia 3D error to 7.39 m; the DEM prior is non-critical, whereas the clustering radius is consequential in the dense pole field, with the count within 20 m falling from 16 to 9 as the radius grows from 15 m to 30 m. In a leave-scene-out check, 85.8% of 254 evaluable clusters persist in a scene excluded from their solutions, against 35.2% of 270 evaluable random positions: a complete-case enrichment of 78%, or 53–82% under cross-arm worst-case imputation of the unevaluable targets; neither estimate measures catalogue precision. Limited KOMPSAT-5 stacks can therefore yield few-metre nearest-cluster agreement at selected pole locations where stable multi-scene responses form. [ABSTRACT FROM AUTHOR] |
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| Database: | Engineering Source |
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| Abstract: | Highlights: What are the main findings? An integrated pseudo-CR pipeline (CFAR ranked by local contrast, multi-scale templates, and multi-look range-Doppler triangulation with per-target conditioning diagnostics) reaches 0.7–2.9 m 3D accuracy on nine KOMPSAT-5 Mongolia corner reflectors. At a corner-reflector-absent suburban site, 16 surveyed distribution poles that formed stable multi-scene responses are positioned to a mean horizontal difference of 3.19 m from the surveyed pole base; on that response-enriched set, ranking candidates by local contrast retains more of those responses than ranking by absolute power at equal candidate budgets. What are the implications? Natural pole-like scatterers that form stable multi-scene responses and can be associated with a specific structure are candidate reference features where no dedicated CRs exist. Per-target conditioning diagnostics, adapted from stereo-SAR practice to mid-resolution KOMPSAT-5 stacks, describe how well the observing geometry determines each solution and flag weak conditioning where no ground control is available. Spaceborne synthetic aperture radar (SAR) needs point-like reference targets for co-registration, calibration, and absolute geolocation, but real corner reflectors (CRs) exist only at a few dedicated sites. We present a detection and three-dimensional (3D) positioning pipeline for naturally occurring corner-reflector-like (pseudo-CR) scatterers in KOMPSAT-5 stacks, combining constant false alarm rate (CFAR) detection ranked by local contrast rather than absolute power, a multi-scale template bank, multi-look range-Doppler bundle triangulation, and a per-target conditioning diagnostic vector. At the nine-CR Mongolia calibration field, all nine are recovered, with a mean horizontal error of 1.37 m and a mean 3D error of 2.01 m. At a CR-absent suburban site in Suncheon, Republic of Korea, 18 scenes yield 39,822 clusters, 26,659 of which pass the conditioning gate. Over 16 response-enriched poles retained by author adjudication, the difference to the nearest conditioning-filtered cluster averages 3.19 m horizontally and 1.45 m vertically relative to the surveyed pole base. Because part of that set was selected after inspecting preliminary responses, these are conditional nearest-cluster agreements, not verified target accuracies, and no detection probability is claimed. In an exploratory comparison on the same set, contrast ranking retains more evaluation targets than power ranking at equal budgets, 16 against 9 of 16. Removing robust weighting and pruning degrades the mean Mongolia 3D error to 7.39 m; the DEM prior is non-critical, whereas the clustering radius is consequential in the dense pole field, with the count within 20 m falling from 16 to 9 as the radius grows from 15 m to 30 m. In a leave-scene-out check, 85.8% of 254 evaluable clusters persist in a scene excluded from their solutions, against 35.2% of 270 evaluable random positions: a complete-case enrichment of 78%, or 53–82% under cross-arm worst-case imputation of the unevaluable targets; neither estimate measures catalogue precision. Limited KOMPSAT-5 stacks can therefore yield few-metre nearest-cluster agreement at selected pole locations where stable multi-scene responses form. [ABSTRACT FROM AUTHOR] |
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| ISSN: | 20724292 |
| DOI: | 10.3390/rs18172889 |
