Optimal asynchronous multi-sensor registration in 3 dimensions

Shunan Jiang, Wenqiang Pu, Zhi Quan Luo

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The success of multi-sensor data fusion requires an important step called sensor registration, which involves estimating sensor biases from sensors' asynchronous measurements. There are two difficulties in the bias estimation problem: one is the unknown target states which serve as the nuisance variables in the estimation problem, the other is the highly nonlinear coordinate transformation between sensors' local and common coordinate frames. In this work, we focus on the 3-dimensional scenario and propose a new nonlinear least squares (LS) formulation which avoids estimating target states. The proposed LS formulation eliminates the target states by exploiting the nearly-constant velocity property of the target motion. To address the intrinsic nonlinearity, we propose a block coordinate descent (BCD) scheme for solving the formulation which alternately updates various bias estimates. Specifically, semidefinite relaxation technique is introduced to handle the nonlinearity brought by angle biases. Furthermore, two BCD algorithms with different block picking rules are proposed. Finally, the effectiveness and the efficiency of the proposed BCD algorithms are demonstrated in the numerical simulation section.

Original languageEnglish (US)
Title of host publication2018 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2018 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages81-85
Number of pages5
ISBN (Electronic)9781728112954
DOIs
StatePublished - Feb 20 2019
Event2018 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2018 - Anaheim, United States
Duration: Nov 26 2018Nov 29 2018

Publication series

Name2018 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2018 - Proceedings

Conference

Conference2018 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2018
CountryUnited States
CityAnaheim
Period11/26/1811/29/18

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Keywords

  • Block coordinate descent algorithm
  • Nonlinear least squares
  • Semidefinite relaxation
  • Sensor registration problem

Cite this

Jiang, S., Pu, W., & Luo, Z. Q. (2019). Optimal asynchronous multi-sensor registration in 3 dimensions. In 2018 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2018 - Proceedings (pp. 81-85). [8646342] (2018 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2018 - Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/GlobalSIP.2018.8646342