An enhanced group matching method with transformed fingerprints, similarity filtering, and adaptive selection for indoor localization

This paper proposes GMM-TSFA, an enhanced machine learning framework that combines fingerprint transformation, similarity-based filtering, and adaptive reference selection. It improves localization accuracy and robustness while maintaining an interpretable decision process.