A Novel Grid Point Approach for Efficiently Solving the Constellation-to-Ground Regional Coverage Problem

Song, Zhiming; Dai, Guangming; Wang, Maocai; Chen, Xiaoyu

doi:10.1109/access.2018.2864181

Cited by 24 publications

(5 citation statements)

References 28 publications

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“…Thus, this method is usually unsuitable for large regions under high accuracy requirements. Overall, the net point division method exhibits a low computational efficiency and little reliability of the results [30], [32]. c) Orbit propagation: Orbit propagation accounts for much of the computation time needed for coverage analysis.…”

Section: Earthmentioning

confidence: 99%

“…Table I summarizes each of the relevant characteristics of this work, denoted by its corresponding reference, alongside Agi's STK (System Tool Kit) and our proposal. Since net-point division analysis algorithms are commonly used in coverage analysis [30], and they fulfill several of the relevant characteristics, in the following section, we will present how this method works with some of its advantages and downsides.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Polygon-Based Algorithms for N-Satellite Constellations Coverage Computing

Henn

Fraire

Hermanns

2023

IEEE Trans. Aerosp. Electron. Syst.

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Satellite Coverage Analysis is a fundamental performance assessment element in remote sensing and communications services projects. Coverage is a key parameter in the constellation operation and design for missions relying on several satellites. Since coverage areas over the surface of the Earth change with time, intersecting and drifting apart, the dynamics of every satellite influence the constellation's behavior as a whole. For this reason, every configuration change, be it in the number of satellites or their relative positions, heavily impacts the cost/performance of the mission. This paper presents a constellation-to-ground coverage analysis model that enables the rapid evaluation of areas on the surface of the Earth. The method leverages geodetic projections and an oblate Earth model and uses dynamic transformation and anti-transformation techniques combined with polygon Boolean operations. Timestamped datasets are obtained to account for the dynamics of the scenario, which can be exploited in statistical coverage analysis of the constellation. Our empirical evaluations show that this approach is superior in accuracy and computation effort compared to traditional net-point techniques. While net-point approaches are at the core of state-of-the-art commercial software, they are approximate. We show that, for finer grid granularity, the netpoint schemes converge to our polygon-based results.

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Section: Earthmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Polygon-Based Algorithms for N-Satellite Constellations Coverage Computing

Henn

Fraire

Hermanns

2023

IEEE Trans. Aerosp. Electron. Syst.

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show abstract

“…Initially, the RoI set RI = {ri j |1 ≤ j ≤ J } are predefined by ground centers. Taking advantage of priori knowledge of S rs orbit parameters and RI location coordinates, the mutual visibility and illumination condition can be estimated according to geometry [4]. Thus, image acquisition tasks plan are scheduled at ground center GC and uploaded to competent satellite s m 1 rs , with assigned task ri j .…”

Section: Task Delivery Delaymentioning

confidence: 99%

A Task-Driven Updated Discrete Graph Assisted Minimum Delivery Delay Routing for Remote Sensing Disruption-Tolerant Networks

et al. 2019

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Benefiting from the extensive coverage, remote sensing satellites have been playing important roles in surveillance for regions on the earth surface. In order to accommodate with intermittent connected and partitioned characteristics of satellite topology, disruption-tolerant network (DTN) develops a feasible solution for networking among such satellites. However, utilized widely and frequently in the future, numerous image covering hundreds of spectral bands and kilometers width is supposed to be delivered simultaneously. Due to the timeliness constrain, efficient routing design with minimum delivery delay for bulk and concurrent image data has become the bottleneck of remote sensing application. Considering data transmission initiated as different tasks, therefore, the Task-driven Updated Discrete Graph (TUDG) is designed to depict the topology evolution, with task data and edge capacity model for BP/LTP incorporated Remote Sensing DTN Network (RS-DTNet). In particular, the multitask-based delivery delay analytical framework is proposed based on the TUDG graph model, by solving a mixed integer Max-Min optimization problem. The Multi-Task Minimum Delay Routing (MTMDR) is designed with the delay-optimal flow distribution, dispatching appropriate bundle data to edges in the TUDG. This flow-based routing avoids the path selection procedure, which may degenerate the delivery delay performance. Through numerical simulation based on the representative RS-DTNet scene, the proposed MTMDR routing strategy shows to advantage on delivery delay, compared with typical path-based routing. INDEX TERMS Delivery delay, disruption-tolerant network, min-max optimization, remote sensing.

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“…E et al [25] suggested a method combining coarse calculation with a precise binary search based on boundary discretization. Song et al [26] proposed a grid method, discretizing regional targets into a grid and traversing to identify covered grid moments. Wang et al [27] introduced a method based on map segmentation, traversing sub-points within a specific range by segmenting maps and trajectories.…”

Section: Introductionmentioning

confidence: 99%

Triple Time Interval Hybridization Strategy for Rapidly Calculating Regional Target–Visible Time Window of Earth Observation Payloads on Space Station

Shan,

Du,

et al. 2024

Applied Sciences

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Earth observation payloads deployed outside the space station play a pivotal role in remote sensing and atmospheric monitoring. Calculating the visible time window (VTW) for regional targets is a fundamental aspect of payload observation and operational mission planning. Aiming to address the challenge of rapidly calculating the VTW for regional targets, this paper introduces the Triple Time Interval Hybridization Strategy (TTIHS). By integrating orbit filtering, large-step angle calculation, and a short interval binary search, the TTIHS adapts different strategies within global, coarse search, and precise search time intervals, effectively reducing computational workload and improving speed. Simultaneously, optimization analysis is conducted on the time step in the coarse search, achieving a balance between computation speed and accuracy. Simulation results, based on real data from the China Space Station, highlight a significant improvement in computational speed while ensuring accuracy. Specifically, the proposed rapid algorithm exhibits a 2.73-fold enhancement in speed compared to the existing rapid algorithm.

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A Novel Grid Point Approach for Efficiently Solving the Constellation-to-Ground Regional Coverage Problem

Cited by 24 publications

References 28 publications

Polygon-Based Algorithms for N-Satellite Constellations Coverage Computing

Polygon-Based Algorithms for N-Satellite Constellations Coverage Computing

A Task-Driven Updated Discrete Graph Assisted Minimum Delivery Delay Routing for Remote Sensing Disruption-Tolerant Networks

Triple Time Interval Hybridization Strategy for Rapidly Calculating Regional Target–Visible Time Window of Earth Observation Payloads on Space Station

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