我们开发了一种分散化算法，来协调一组移动机器人搜索未知瞬时射电源。除了移动能力和通信及传感范围有限，机器人团队还必须应对信号源匿名性、短暂的传输时间和可变的发射功率带来的挑战。我们提出了一种两步式方法：首先，基于检查站的同步功能，对机器人用于追踪信号源位置的可信度函数进行了分散化；其次，提出了一种用于协调机器人的分散化规划策略，以确保存在检查站。我们分析了该算法的内存使用情况、通信数据量和搜索时间。实现了该算法，并将其与其他两种探索式算法进行了比较。实验结果显示，在三种算法中，分散化算法用最少的内存换来了最快的搜索时间。

In this paper, we develop a decentralized algorithm to coordinate a group of mobile robots to search for unknown and transient radio sources. In addition to limited mobility and ranges of communication and sensing, the robot team has to deal with challenges from signal source anonymity, short transmission duration, and variable transmission power. We propose a two-step approach: First, we decentralize belief functions that robots use to track source locations using checkpoint-based synchronization, and second, we propose a decentralized planning strategy to coordinate robots to ensure the existence of checkpoints. We analyze memory usage, data amount in communication, and searching time for the proposed algorithm. We have implemented the proposed algorithm and compared it with two heuristics. The experimental results show that our algorithm successfully trades a modest amount of memory for the fastest searching time among the three methods.