Cramer-Rao bound for source estimation using a network of binary sensors

TL;DR

This paper derives the Cramer-Rao lower bound for source parameter estimation using binary sensors in a network, providing theoretical limits and validating them with numerical experiments for atmospheric hazardous gas detection.

Contribution

It introduces a theoretical Cramer-Rao bound for binary sensor networks in source estimation, bridging the gap between theory and empirical results.

Findings

Theoretical bounds closely match empirical errors.

Numerical results validate the derived Cramer-Rao bound.

Applicable to atmospheric hazardous gas monitoring.

Abstract

The paper derives the theoretical Cramer-Rao lower bound for parameter estimation of a source (of emitting energy, gas, aerosol), monitored by a network of sensors providing binary measurements. The theoretical bound is studied in the context of a source of a continuous release in the atmosphere of hazardous gas or aerosol. Numerical results show a good agreement with the empirical errors, obtained using an MCMC parameter estimation technique.