{'fraction_non_alphanumeric': 0.017517136329017517, 'fraction_numerical': 0.0, 'mean_word_length': 5.19811320754717, '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}}
Tracking Position of Airborne Target on SPx-Radar-Simulator Using Probabilistic Data Association Filter

Radar has various functions, one of which is tracking the position of targets in the air. In tracking the target position, there are obstacles, namely the uncertainty of data associations. To overcome the uncertainty of data associations, the concept of data association can be used where one of the algorithms that use this concept is the Probabilistic Data Association Filter (PDAF). A single target position tracking system in the air will be tested on radar using the PDAF with our proposed maintenance track algorithm. The data used for testing comes from simulating two motions on the SPx-Radar-Simulator. False alarms originating from interference (clutter) will be generated in the environment around the simulated target. The test results of the target tracking system using the PDAF algorithm that has been designed can track targets well, maintain tracking conditions in an environment that has clutter, and maintain track on multitarget environments. The error between the original data and the prediction on the validated target has a relatively small value, although there is a relatively significant difference in the error of the altitude data when the motion has varying altitude conditions.