arXiv subjects

Shenshen Luan

Publications and source records attributed to Shenshen Luan.

3 recordsLinked to original sources

arXiv2026

Sub-Pixel Affine Registration of Space Debris Images via the Radon Point Spread Function

Inter-frame affine misalignment caused by platform jitter and attitude adjustments poses a fundamental challenge for multi-frame analysis of point targets in optical surveillance. Conventional registration methods rely on spatial intensity correlations or distinctive image features, both of which are largely absent in low-signal-to-noise-ratio point target imagery. We introduce the Radon Point Spread Function (RPSF) to characterize point targets in the Radon-transformed domain, and derive a closed-form framework that jointly estimates inter-frame translation and rotation from as few as four scalar RPSF samples per frame pair. The method requires no iterative optimization, feature extraction or interpolation, which is suitable for resource-constrained onboard processing. Simulation results confirm sub-pixel translation accuracy and a mean rotation error of 0.2556{\deg} at 1{\deg} Radon angular resolution. Validation on five real space debris datasets including both ground-based and in-orbit observations yields a mean calibration error below 0.5 pixels, substantially exceeding the precision required for reliable multi-frame processing.

cs.CV↗

arXiv2025

Symmetry-Driven Asynchronous Forwarding for Reliable Distributed Coordination in Toroidal Networks

The proliferation of large-scale distributed systems, such as satellite constellations and high-performance computing clusters, demands robust communication primitives that maintain coordination under unreliable links. The torus topology, with its inherent rotational and reflection symmetries, is a prevalent architecture in these domains. However, conventional routing schemes suffer from substantial packet loss during control-plane synchronization after link failures. This paper introduces a symmetry-driven asynchronous forwarding mechanism that leverages the torus's geometric properties to achieve reliable packet delivery without control-plane coordination. We model packet flow using a topological potential gradient and demonstrate that symmetry-breaking failures naturally induce a reverse flow, which we harness for fault circumvention. We propose two local forwarding strategies, Reverse Flow with Counter-facing Priority (RF-CF) and Lateral-facing Priority (RF-LF), that guarantee reachability to the destination via forward-flow phase transition points, without protocol modifications or additional in-packet overhead. Through percolation analysis and packet-level simulations on a 16 x 16 torus, we show that our mechanism reduces packet loss by up to 17.5% under a 1% link failure rate, with the RF-LF strategy contributing to 28% of successfully delivered packets. This work establishes a foundational link between topological symmetry and communication resilience, providing a lightweight, protocol-agnostic substrate for enhancing distributed systems.

cs.NI↗

arXiv2024

A Fast Percolation-Dijkstra Routing Method for Mega-Constellation Backbone Network

The real-time routing for satellite communication of the mega-constellations is being challenged due to the large-scale of network nodes, especially on devices with limited computation such as onboard embedded systems. In this paper, a fast routing method is proposed for mega-constellation backbone networks. Firstly, inspired by the regularity and sparse characteristics of mega-constellations, the 4-degree percolation theory is proposed to describe the node search process. Then, dynamic minimum search and mapping methods are used to narrow down the traversal range. The proposed method performs as well as the heap-optimized Dijkstra algorithm with less memory space and dynamic access. The experimental results show that the method proposed in this paper can significantly reduce routing computation time, especially on the onboard, edge-computing or other computation-limited devices.

cs.NI↗