Agile Satellite Planning for Multi-Payload Observations for Earth Science

TL;DR

This paper introduces a model-based planning approach for agile satellite systems with multiple payloads, enabling adaptive earth observation through coordinated, real-time plan updates based on sensor data.

Contribution

It presents a novel heuristic constraint optimization planner for multi-satellite, multi-instrument coordination in adaptive remote sensing.

Findings

Planner effectively coordinates satellite maneuvers and payloads.

Preliminary results show promising performance in soil moisture monitoring.

The approach adapts plans dynamically based on sensor feedback.

Abstract

We present planning challenges, methods and preliminary results for a new model-based paradigm for earth observing systems in adaptive remote sensing. Our heuristically guided constraint optimization planner produces coordinated plans for multiple satellites, each with multiple instruments (payloads). The satellites are agile, meaning they can quickly maneuver to change viewing angles in response to rapidly changing phenomena. The planner operates in a closed-loop context, updating the plan as it receives regular sensor data and updated predictions. We describe the planner's search space and search procedure, and present preliminary experiment results. Contributions include initial identification of the planner's search space, constraints, heuristics, and performance metrics applied to a soil moisture monitoring scenario using spaceborne radars.