{'fraction_non_alphanumeric': 0.031746031746031744, 'fraction_numerical': 0.0, 'mean_word_length': 6.130434782608695, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Achieving high-accuracy distributed localization in sensor networks

Accurate, distributed localization algorithms are needed for a wide variety of wireless sensor network applications. This paper introduces a scalable, distributed weighted-multidimensional scaling (dwMDS) algorithm that adaptively emphasizes the most accurate range measurements available and naturally accounts for communication constraints within the sensor network. For received signal-strength (RSS) based range measurements, we demonstrate via simulation that location estimates are nearly unbiased with variance close to the Cramer-Rao lower bound (CRB). Further, RSS and time-of-arrival (TOA) channel measurements are used to demonstrate performance as good as the centralized maximum-likelihood estimator (MLE) in a real-world sensor network.