Optimal Time-Reversed Wideband Signals for Distributed Sensing

TL;DR

This paper investigates the use of time-reversal waveforms in distributed sensing systems to optimize target detection by identifying resonant frequencies through eigenvalue analysis, considering frequency-dependent interference effects.

Contribution

It introduces a novel analysis of the frequency dependence of time-reversal eigenvalues for idealized scatterers, linking them to resonant frequencies and the poles of the Singularity Expansion Method.

Findings

Eigenvalues depend on constructive/destructive interference.

Time-reversal process finds resonant frequencies automatically.

Distinct frequency behavior from previous single-frequency TR work.

Abstract

This paper considers a distributed wave-based sensing system that probes a scene consisting of multiple interacting idealized targets. Each sensor is a collocated transmit-receive pair that is capable of transmitting arbitrary wideband waveforms. We address the problem of finding the space-time transmit waveform that provides the best target detection performance in the sense of maximizing the energy scattered back into the receivers. Our approach is based on earlier work that constructed the solution by an iterative time-reversal (TR) process. In particular, for the case of idealized point-like scatterers in free space, we examine the frequency dependence of the eigenvalues of the TR operator, and we show that their behavior depends on constructive and destructive interference of the waves traveling along different paths. In addition, we show how these eigenvalues are connected to the poles of the Singularity Expansion Method. Our study of the frequency behavior distinguishes this work from most previous TR work, which focused on single-frequency waveforms and noninteracting targets. The main result of the present paper is that the TR process provides an automated, guaranteed way to find the resonant frequencies of the scattering system.