# Geolocation of Multiple Noncooperative Emitters Using Received Signal Strength: Sparsity, Resolution, and Detectability

## TL;DR

This paper explores the limits of locating multiple RF emitters using only RSS data, focusing on resolution, detectability, and the effectiveness of sparse recovery methods in uncharted environments.

## Contribution

It introduces a sparse approximation framework for RF emitter localization using RSS data without prior environment mapping, highlighting resolution and detection limits.

## Key findings

- Resolution depends on sensor geometry and noise levels.
- Sparse recovery algorithms can effectively identify multiple emitters.
- Detectability threshold varies with emitter power and environmental factors.

## Abstract

In this paper we investigate the problem of locating multiple non-cooperative radio frequency (RF) emitters using only received signal strength (RSS) data. We assume that the number of emitters is unknown and that individual emitters cannot be distinguished in the RSS data. Moreover, we assume that the environment in which the data has been collected has not been mapped or "fingerprinted" by the prior collection of RSS data. Our primary interest is the limiting resolution that can be obtained by this type of data, and the lowest power emitters that can be detected, as a function of noise level, sensor geometry, and other variables. We formulate the recovery problem as one of sparse approximation or compressed sensing, and investigate an appropriate recovery algorithm for this setting, and use it to illustrate our conclusions. We also include a reconstruction based on sampled data we collected, to illustrate the reasonableness of our parameter choices and conclusions.