Fast Resource Management Algorithm for Passive Surveillance Systems

TL;DR

This paper introduces ResourceTune, a novel algorithm for optimizing frequency observation schedules in passive surveillance systems, significantly improving resource utilization and detection performance.

Contribution

The paper presents a new resource management algorithm that optimizes receiver configurations using a heuristic and linear programming, outperforming existing methods.

Findings

ResourceTune outperforms greedy and state-of-the-art algorithms in most scenarios.

In extreme cases, ResourceTune's objective value is over 2.7 times better.

The approach effectively enhances passive surveillance system efficiency.

Abstract

Passive surveillance systems (PSS) detect and track objects that emit electromagnetic signals from hundreds of kilometers away. These systems have a limited number of receivers and can only observe a fraction of the frequencies of interest simultaneously. To improve its behavior, we propose the ResourceTune algorithm, which iteratively constructs optimized schedules to determine which frequencies each receiver should observe at a given time step. The algorithm's main component is the optimization of receiver configurations using a left-right heuristic combined with linear programming. Our approach is unique because, unlike others, we focus on optimizing available resources and observed frequencies, which was never done before. We experimentally compared the proposed algorithm with a greedy and the state-of-the-art method for construction of PSS schedules. In most of the considered scenarios, ResourceTune outperformed both algorithms, and in the most extreme case, its objective value was more than 2.7 times better than the values reached by other methods.