Survey of Resource Scheduling Technologies for Ground-Based Space Target Surveillance Radar Networks Focused on Cataloging Tasks

Cataloging task resource scheduling is a key technology for the efficient utilization of ground-based radar networks and for supporting space situational awareness. This problem is highly challenging due to the large scale of tasks, strict time window constraints, and complex resource-task mapping relationships. It requires algorithms to effectively balance multiple conflicting optimization objectives within a huge and sparse solution space, placing extremely high demands on the convergence, diversity maintenance, and computational efficiency of the algorithms. This paper presents a systematic review of the latest research progress in cataloging resource scheduling methods. First, commonly used optimization objectives and constraint conditions in this field are outlined, and two key subproblems-priority modeling and conflict resolution-are analyzed in depth. Subsequently, following the trajectory of technological evolution, the application paradigms, performance characteristics, and limitations of mainstream algorithms are reviewed. Given the inherent multi-objective optimization nature of the problem, the advantages and challenges of multi-objective optimization algorithms are discussed. Finally, based on a unified problem context, the performance and operational boundaries of existing algorithms are compared and analyzed, and future research directions and core challenges in the field are presented.