# Attack-Resilient H2, H-infinity, and L1 State Estimator

arXiv: https://arxiv.org/abs/1803.07053 · HTML: https://mlsanity.com/paper/1803.07053/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 19 Mar 2018.

## Built on by (most cited first, 1 of 1)

- [Attack Detection using Time Series Foundation Models](https://mlsanity.com/paper/2606.06347/) (2026)

## Abstract (arXiv)

This paper considers the secure state estimation problem for noisy systems in the presence of sparse sensor integrity attacks. We show a fundamental limitation: that is, 2r-detectability is necessary for achieving bounded estimation errors, where r is the number of attacks. This condition is weaker than the 2r-observability condition typically assumed in the literature. Conversely, we propose a real-time state estimator that achieves the fundamental limitation. The proposed state estimator is inspired by robust control and FDI: that is, it consists of local Luenberger estimators, local residual detectors, and a global fusion process. We show its performance guarantees for H2, H-infinity, and L1 systems. Finally, numerical examples show that it has relatively low estimation errors among existing algorithms and average computation time for systems with a sufficiently small number of compromised sensors.