{'fraction_non_alphanumeric': 0.022131147540983605, 'fraction_numerical': 0.0, 'mean_word_length': 5.529411764705882, '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}}
Combining Measurements and Simulations for Evaluation of Tracking Algorithms

Wireless device position tracking has been already thoroughly studied in literature. Most of the studies rely on the presumption that location information is acquired based on range measurements that are performed in a very short period of time. However, in time-division-multiple-access (TDMA) two-way-ranging (TWR) ultra-wideband (UWB) wireless localization networks, those ranging measurements are always spread in time by significant time delays. Those delays have negative impact on the tracking performance and the effects of ranging in these systems should be evaluated accordingly. In this paper we propose a time-of-flight (ToF) simulation-based approach for indoor tracking algorithm evaluation with a measurement calibration which enables changing the size of TDMA slots and thus observing the tracking performance degradation. A constant velocity movement model with a random curvature of walking path is proposed to simulate the person's random walking pattern inside the room as naturally as possible. With a proposed simulation framework the impact of individual hyperparameter changes on tracking performance can be evaluated.