Convex Reformulation of Information Constrained Linear State Estimation with Mixed-Binary Variables for Outlier Accommodation

Details

• Creators:
  Hu, Wang ; Jiang, Zeyi ; Mohsenian-Rad, Hamed ; Farrell, Jay A.
• Corporate Creators:
  University of California, Riverside. Dept. of Electrical and Computer Engineering
• Subject/TRT Terms:
  Control Estimation Theory Linear Systems Systems Tools
• Resource Type:
  Journal Article
• Right Statement:
  Open Access; arXiv- Non-exclusive license to distribute
• Geographical Coverage:
  United States
• Corporate Publisher:
  arXiv [Cornell University]
• Abstract:
  This article considers the challenge of accommodating outlier measurements in state estimation. The Risk-Averse Performance-Specified (RAPS) state estimation approach addresses outliers as a measurement selection Bayesian risk minimization problem subject to an information accuracy constraint, which is a non-convex optimization problem. Prior explorations into RAPS rely on exhaustive search, which becomes computationally infeasible as the number of measurements is increases. This paper derives a convex formulation for the RAPS optimization problems via transforming the mixed-binary variables into linear constraints. The convex reformulation herein can be solved by convex programming toolboxes, significantly enhancing computational efficiency. We explore two specifications: Full-RAPS, utilizing the full information matrix, and Diag-RAPS, focusing on diagonal elements only. The simulation comparison demonstrates that Diag-RAPS is faster and more efficient than Full-RAPS. In comparison with Kalman Filter (KF) and Threshold Decisions (TD), Diag-RAPS consistently achieves the lowest risk, while achieving the performance specification when it is feasible.
• Content Notes:
  This is an open access article under the terms of arXiv.org - Non-exclusive license to distribute.
• Format:
  PDF
• Collection(s):
  US Transportation Collection
• Main Document Checksum:
  urn:sha-512:284eecc59d42fe2454500b45a282cc3665b9739473bf2a9be466f725ca5489898a93e87cf33812a0adcb969d9f521e95a8ba34f79e964dd9709e335fd1e561a2
• Download URL:
  https://rosap.ntl.bts.gov/view/dot/80646/dot_80646_DS1.pdf
• File Type:
  [PDF - 285.41 KB ]