Abstract: Discriminative methods for multipath fingerprinting, enabling single-site localization in rich multipath environments, are provided herein. In contrast to the existing descriptive method that uses only the data of each location for its fingerprint extraction, these methods use also the data of the other locations in the database, and leverage it to make the fingerprint as different as possible from the other fingerprints in the database. The performance of these methods, validated with both simulated and real data, is superior to the existing method, demonstrating localization accuracy of about 1 m in typical indoor environments.

Abstract: Discriminative methods for multipath fingerprinting, enabling single-site localization in rich multipath environments, are provided herein. In contrast to the existing descriptive method that uses only the data of each location for its fingerprint extraction, these methods use also the data of the other locations in the database, and leverage it to make the fingerprint as different as possible from the other fingerprints in the database. The performance of these methods, validated with both simulated and real data, is superior to the existing method, demonstrating localization accuracy of about 1 m in typical indoor environments.