Indoor Fingerprint Localization Algorithms: NN, KNN, and WKNN Implementation and Comparison

In this article, we explore various indoor fingerprint localization algorithms, including NN, KNN, and WKNN, and conduct comparative analysis between them. The implementation features distance calculation functions using Euclidean metric, fingerprint database management, and real-time positioning estimation. We provide well-commented, executable code that demonstrates core algorithmic components such as similarity measurement, neighbor selection criteria, and weight assignment strategies. Through in-depth examination of these algorithms and their implementation approaches, readers can better understand the applications and limitations of fingerprint localization technology in indoor environments, along with methodologies for developing more accurate and reliable indoor positioning systems. Key code segments illustrate parameter optimization techniques and performance evaluation metrics. Let's explore this fascinating and challenging field together!