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Compensation of time-varying clock-offset in a lbl navigation
Simamora Y.S.M.a,b, Tjokronegoro H.A.a, Leksono E.a, Brodjonegoro I.S.a
a Engineering Physics Research Group, Institut Teknologi Bandung, Indonesia
b Department of Mechanical Engineering, Politeknik Purbaya, Indonesia
[vc_row][vc_column][vc_row_inner][vc_column_inner][vc_separator css=”.vc_custom_1624529070653{padding-top: 30px !important;padding-bottom: 30px !important;}”][/vc_column_inner][/vc_row_inner][vc_row_inner layout=”boxed”][vc_column_inner width=”3/4″ css=”.vc_custom_1624695412187{border-right-width: 1px !important;border-right-color: #dddddd !important;border-right-style: solid !important;border-radius: 1px !important;}”][vc_empty_space][megatron_heading title=”Abstract” size=”size-sm” text_align=”text-left”][vc_column_text]© 2020, Institute of Advanced Engineering and Science. All rights reserved.This paper presents compensation of the clock-offset in a long baseline (LBL) navigation. It departs from the existing literature mainly in dealing with a time-varying clock-offset, i.e. the clock-rate drifts over the time. Specifically, the clock-offset dynamics are introduced to the ToFs as an autoregressive filter. Subsequently, interactions among the now biased ToFs and the kinematics of an autonomous underwater vehicle (AUV)–the navigation subject–are represented in a state-space form. Implementing the so-called graphic approach, minimum sensor requirement for this system’s observability is then explicated. Finally, a standard discrete Kalman filter is deployed as the state estimator. By simulation, it is demonstrated that the estimator manages to compensate the offset and to provide localization with less than 1 m accuracy.[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Author keywords” size=”size-sm” text_align=”text-left”][vc_column_text][/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Indexed keywords” size=”size-sm” text_align=”text-left”][vc_column_text]Clock-offset,Long baseline,Sonar,State estimation,Time-of-flight[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Funding details” size=”size-sm” text_align=”text-left”][vc_column_text][/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”DOI” size=”size-sm” text_align=”text-left”][vc_column_text]https://doi.org/10.11591/eei.v9i4.1996[/vc_column_text][/vc_column_inner][vc_column_inner width=”1/4″][vc_column_text]Widget Plumx[/vc_column_text][/vc_column_inner][/vc_row_inner][/vc_column][/vc_row][vc_row][vc_column][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][/vc_column][/vc_row]