# Track selection in Multifunction Radars: Nash and correlated equilibria

## TL;DR

This paper models multi-target track selection in multifunction radars as a game, deriving distributed algorithms for Nash and correlated equilibria to improve coordination and tracking accuracy.

## Contribution

It introduces a game-theoretic framework for radar track selection, including distributed algorithms for Nash and correlated equilibria under various observability and connectivity conditions.

## Key findings

- Distributed algorithms outperform centralized approaches in efficiency
- Nash equilibria are characterized for coordinated tracking
- Correlated equilibria improve performance with partial observability

## Abstract

We consider a track selection problem for multi-target tracking in a multifunction radar network from a game-theoretic perspective. The problem is formulated as a non-cooperative game. The radars are considered to be players in this game with utilities modeled using a proper tracking accuracy criterion and their strategies are the observed targets whose number is known. Initially, for the problem of coordination, the Nash equilibria are characterized and, in order to find equilibria points, a distributed algorithm based on the best-response dynamics is proposed. Afterwards, the analysis is extended to the case of partial target observability and radar connectivity and heterogeneous interests among radars. The solution concept of correlated equilibria is employed and a distributed algorithm based on the regret-matching is proposed. The proposed algorithms are shown to perform well compared to the centralized approach of significantly higher complexity.