# An Information-Theoretic Framework for Uncertainty Quantification and Sensitivity Analysis in UWB Fuze Transmitters

## TL;DR

This paper introduces a new framework to analyze how component variations in UWB transmitters affect system performance using information theory.

## Contribution

A novel information-theoretic framework is introduced to quantify uncertainty and sensitivity in UWB fuze transmitters.

## Key findings

- Inductance tolerances strongly amplify joint uncertainty in pulse amplitude and width.
- Load resistance mainly influences amplitude uncertainty in a linear, independent manner.

## Abstract

Component tolerances in Ultra-Wideband (UWB) fuze transmitters inevitably induce waveform distortions, which propagate through the signal chain to degrade system-level tactical performance, specifically detection range and ranging resolution. Addressing the lack of quantitative mechanisms linking component variations to operational effectiveness, this study proposes an information-theoretic sensitivity analysis framework. First, we establish a physics-based mathematical model of the transmitter and rigorously validate it against circuit-level simulations to characterize the step recovery diode’s transient response under tolerance disturbances. Second, we employ the Latin Hypercube Sampling-Information Entropy (LHS-IE) method to quantify the uncertainty propagation from parameters to pulse features. Crucially, we introduce Feature Interaction Information (FII) to decode the nonlinear coupling between components. Our results reveal a strong Amplifying effect driven by inductance tolerances, where the interaction between parameters amplifies the joint uncertainty of amplitude and width beyond their individual impacts. Conversely, load resistance primarily dictates amplitude uncertainty as an independent linear factor. The proposed framework provides a theoretical basis for converting traditional tolerance design into an entropy-driven precision allocation strategy, ensuring system robustness under manufacturing constraints.