关键词: 无线定位技术, 指纹定位, Spark计算引擎, 加权KNN, 分布式计算

Abstract: Fingerprint localization is a simple and efficient wireless localization technology. It is free from interference caused by multipath effect and reflection of wireless signals, and achieves high accuracy. However, fingerprint localization technology requires a large offline fingerprint database for better accuracy. With the expansion of fingerprint database scale, traditional fingerprint localization algorithms have been difficult to meet the real-time requirements of large data applications. Therefore, combining fingerprint localization algorithm and in-memory computing engine Spark, a fingerprint localization data processing method based on Spark is designed and implemented. In the Map phase, the K neighbors of query point are found respectively. In the Reduce stage, the K neighbors of each partition are reduced to the global K nearest neighbors. Finally, the result coordinates are found by weighted mean. Cluster experiments show that the Spark based fingerprint localization data processing method has a good speedup in certain parallelism, and has the capability of real-time localization processing in large-scale fingerprint database.

Key words: wireless localization technology, fingerprint localization, Spark computing engine, weighted KNN, distributed computation