# Multi-Radar Tracking Optimization for Collaborative Combat

arXiv: https://arxiv.org/abs/2010.11733 · HTML: https://mlsanity.com/paper/2010.11733/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 20 Oct 2020.

## Built on by (most cited first, 1 of 1)

- [Tracking mulitple targets with multiple radars using Distributed Auctions](https://mlsanity.com/paper/2307.16477/) (2023)

## Abstract (arXiv)

Smart Grids of collaborative netted radars accelerate kill chains through more efficient cross-cueing over centralized command and control. In this paper, we propose two novel reward-based learning approaches to decentralized netted radar coordination based on black-box optimization and Reinforcement Learning (RL). To make the RL approach tractable, we use a simplification of the problem that we proved to be equivalent to the initial formulation. We apply these techniques on a simulation where radars can follow multiple targets at the same time and show they can learn implicit cooperation by comparing them to a greedy baseline.