Jul 2026· ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences· Vol XI-2-2026, pp. 235-241· 0 citations
Abstract
Abstract. The emergence of satellite constellations enables near-synchronous multi-view optical imaging, offering new opportunities for large-scale 3D city modeling. Yet a practically promising configuration, in which a primary near-nadir view is complemented by multiple oblique side-looking viewpoints, remains under-examined. This study develops a controlled semi-simulation framework to analyze how multi-view imaging geometry affects the recoverability of urban 3D structures. Under idealized conditions with imaging perturbations removed, e.g., radiometric, illumination, and sensor model errors, the experiments focus on three practical factors: the number of side-looking views, view obliqueness, and the constellation’s azimuthal orientation relative to the scene. With parameter sweep analysis, it reveals an asymmetric U-shaped trend between reconstruction performance and both the view count and the obliqueness: moderate angular diversity markedly strengthens urban scene recoverability. In contrast, large obliqueness reduces inter-view overlap and destabilizes matching, while excessive redundancy introduces consistency issues that ultimately degrade reconstruction performance. Furthermore, the results shows that geometric accuracy, completeness, and texture appearance each peak at different parameter combinations, revealing intrinsic trade-offs in multi-view urban reconstruction, as different evaluation criteria favor distinct optimal configurations. The study provides practical guidance for the geometric design and mission planning of multi-satellite constellations aimed at improving satellite-based 3D modeling in urban areas.
A fundamental challenge in space-based optical surveillance constellation design is the quantitative evaluation of coverage capability across the entire low-Earth-orbit (LEO) space. A phase-volume coverage model in the 4D (a,i,Ω,u) phase-space is proposed, and the multi-coverage ratio Rmulti, mean covering satellite count N¯sat, and Observation Geometry Quality Index (OGQI) are introduced to overcome the limitations of single-metric coverage evaluation. A theoretical motivation for the relationship between OGQI components and orbit determination error covariance is provided via Fisher information matrix theory. Spherical-shell 3D spatial and phase-space 4D orbital frameworks are compared: the two frameworks are shown to be mathematically non-equivalent, and phase-space evaluation provides orbit-type-based diagnostic capability unavailable in spatial methods. Within the Walker-Delta framework with Sun-synchronous dawn–dusk orbits, camera pointing and constellation configuration are systematically optimized, yielding a preferred altitude of 1700 km and a P=6-plane layout with coverage saturation at T≥18. Validation against the Space-Track TLE catalog (22,471 LEO objects) yields 95.49% coverage and 83.47% multi-coverage within a 1-h window. The phase-volume framework unifies coverage evaluation and constellation design in a common orbital element space, enabling systematic space-based optical surveillance constellation design.
Bridging the simulation-to-reality gap in roadside LiDAR requires addressing several coupled discrepancies, including scene geometry, sampling density, return patterns, and pedestrian scale. This report presents a multi-source collaborative training and class-aware fusion framework for Sim2Real 3D detection. The method organizes digital-twin scans, diffusion-redrawn scans, density-stabilized scans, and pedestrian morphology-aligned samples into a unified training pool with complementary roles. Within a common DSVT detection formulation, source-specialized expert branches preserve those roles while optimizing for the same detection objective. At inference, a predefined class-aware fusion pathway integrates geometry-stable and calibration-aware branches for vehicles, sampling-complementary branches for trucks, and morphology-consistent evidence for pedestrians. A label-free point-cloud center blend then refines geometric localization. On the UrbanTwin V2X-Real hidden test set, the unified system achieves a combined score of 0.7421, with 3D mAP@0.5 of 0.4518 and a realism score of 0.8871. The results indicate that a stable, interpretable collaboration among data sources is more valuable than unconstrained aggregation of model outputs.
The results support the conclusion that a lightweight 3D geometric prior improves viewpoint adherence for controllable SAR generation; it is intended as generation guidance rather than high-fidelity electromagnetic construction.
Fan Zhang, Xuanting Wu, Fei Ma et al.· arXiv.org· 0 citations
High-definition (HD) road maps are critical for autonomous navigation and intelligent transportation systems. However, single front-view pipelines suffer from unilateral occlusions and a narrow field of view (FoV), whereas conventional multi-sensor bird's-eye-view (BEV) systems improve coverage at the cost of increased hardware requirements, calibration complexity, and computation. This work addresses the problem of achieving robust, wide-coverage HD mapping under urban occlusions using a single, low-cost panoramic camera. A lightweight dual-view fusion framework is introduced for incremental road mapping from panoramic images. The method introduces three technical contributions: (1) a single-sensor dual-view construction that extracts front and rear perspective views from one panoramic camera via FoV-aware projection; (2) a geometry-consistent BEV fusion module that integrates inverse perspective mapping (IPM), pose-stabilized stitching, and patch-level merging to suppress parallax and motion jitter while recovering markings occluded in one view but visible in the other; and (3) a lightweight incremental pipeline that reduces deployment and inter-sensor calibration overhead relative to ring-camera systems. Experiments on a self-built dataset of 80 test panoramas with five road-element classes under unilateral or moderate occlusion show that dual-view fusion improves marking completeness by 33.3%, reduces geometric deviation (PSC) by 26.7%, and improves shape regularity (RARC) by 7.7% over a front-view-only baseline. The results support panoramic dual-view fusion as a practical low-cost compromise between limited single-view coverage and high-complexity multi-sensor platforms.
Terrestrial base stations (BSs) are typically configured with fixed downtilt to serve ground users, resulting in weak illumination of low-altitude airspace even under line-of-sight (LoS) propagation. In this paper, we establish a channel model that incorporates BS and intelligent reflecting surface (IRS) radiation patterns for three-dimensional (3D) low-altitude coverage while preserving the existing BS configuration. We formulate a budget-constrained IRS deployment problem that jointly determines candidate-site selection, IRS orientations, and phase shifts to maximize the worst-case signal-to-noise ratio (SNR) over the 3D low-altitude airspace. The selected sites and optimized IRS parameters remain fixed after deployment, yielding a quasi-static IRS configuration. We characterize the illumination geometry between the fixed-downtilt BS and rooftop candidates by deriving the nonnegative installation-height range satisfying the BS main-lobe condition. The separation between the mapped main-lobe height boundaries grows linearly with horizontal BS-to-site distance and decreases inversely with the number of BS antennas. We further derive an analytical lower bound on the regional worst-case normalized array gain achievable through IRS phase design over served directions with different direction spans. The resulting sufficient direction span decreases inversely with the square root of the number of IRS elements when the same worst-case normalized gain guarantee is maintained. We develop a mixed-integer alternating optimization (AO) algorithm to solve the resulting problem. Simulation results validate the analytical characterizations and show that the proposed scheme achieves higher worst-case SNR than benchmarks across different deployment budgets.
Guo-Ying Zhang, Qingqing Wu, Ai-Ling Zheng et al.· 0 citations
Abstract. The generation of Level of Detail 3 (LoD3) building models is essential for applications such as urban digital twins, energy analysis, and smart city planning. However, conventional approaches based on terrestrial LiDAR or UAV photogrammetry remain costly, labor-intensive, and difficult to scale. This paper presents a scalable framework for transforming LoD1 building models into LoD3 façade representations using openly available urban data, including OpenStreetMap footprints, street-level spherical imagery, and weak point-cloud priors. The proposed method formulates the reconstruction problem as a facet-based modeling task, where each façade is processed independently in a local coordinate system derived from LoD1 geometry. A rectification strategy is introduced to generate fronto-parallel façade images directly from spherical panoramas, avoiding perspective distortions and facilitating image analysis. To address the challenges of unstructured data acquisition, a visibility-driven view selection scheme and a multi-view fusion framework are developed to construct robust façade evidence maps. The 3D geometry is estimated as a depth field through a multi-resolution optimization framework integrating ray consistency, appearance cues, point-cloud support, and structural regularization. Planar segmentation, polygonization, and geometric regularization are subsequently applied to derive structured façade elements. Openings such as windows and doors are detected using combined geometric and image-based evidence and further refined through architectural constraints. Experimental results demonstrate that the proposed framework enables reliable reconstruction of façade geometry and structural details using only open and low-cost data sources, providing a practical pathway for large-scale LoD3 generation in real urban environments.
M. Saadatseresht, Hossein Arefi, Qazale Askari· The International Archives o...· 0 citations
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