# Localizing an Unknown Number of mmW Transmitters Under Path Loss Model Uncertainties

## TL;DR

This paper presents a novel method for localizing an unknown number of mmW transmitters under path loss uncertainties, using convex optimization and l1-regularization to accurately estimate positions and powers even with model uncertainties.

## Contribution

It introduces an unbiased estimator that converts a complex combinatorial problem into a convex form, enabling off-grid target localization under uncertain conditions.

## Key findings

- High accuracy in noise-free simulations
- Effective localization despite model uncertainties
- Handles unknown number of transmitters

## Abstract

This work estimates the position and the transmit power of multiple co-channel wireless transmitters under model uncertainties. The model uncertainties include the number of the targets and the parameters of the path-loss model which enable the system to cope with changes in the weather conditions and in mmW ranges. The problem is solved by an unbiased estimator. The underlying complicated optimization problem has a combinatorial nature that selects the best grid points as the location of the targets. The combinatorial problem is converted to a convex form by means of l1-regularization, which enables locating off-grid targets. Simulations show that the proposed algorithm solves the problem with very high accuracy in the absence of noise and shadowing.