Debris Sensing Based on Leo Constellation: An Intersatellite Channel Parameter Estimation Approach

Space debris detection and tracking, a key enabler for Space Situational Awareness (SSA), poses two inherent challenges: (1) small-sized targets (e.g., 1 − 10 cm) posing detection difficulties for conventional ground-based radars (GBRs) and optical measurements; (2) large number resulting in a costly tracking exercise. To address these, this work utilizes intersatellite link (ISL) in the emerging low earth orbit (LEO) constellations to opportunistically sense debris. The spatially dense-distributed debris is modeled as a cluster to reduce the number of quantities estimated. Using a stochastic geometry-based channel model, a nested expectationbased SAGE 2 is proposed, building on space-alternativegeneration-estimation-maximization (SAGE) to estimate the cluster-based channel parameters. Finally, the debris clusters are localized using the ISL forming a bistatic sensing setup. Simulation results validate the proposed approach and show the proposed SAGE 2 is faster than the conventional SAGE in clustered multipath channels.