Domain-Knowledge-Aided Airborne Ground Moving Targets Tracking

TL;DR

This paper presents a novel UAV-based ground moving targets tracking algorithm that integrates domain knowledge like road maps and traffic rules into the JPDA filter to improve tracking accuracy and robustness.

Contribution

It introduces a domain-knowledge-aided tracking algorithm that incorporates map and traffic regulation constraints into the JPDA filter, enhancing multi-target tracking performance.

Findings

Improved tracking accuracy demonstrated through simulations.

Enhanced recognition of temporary track loss.

Effective integration of domain knowledge into tracking algorithms.

Abstract

This paper investigates the problem of traffic surveillance using an unmanned aerial vehicle (UAV) and proposes a domain-knowledge-aided airborne ground moving targets tracking algorithm. To improve the accuracy of multiple targets tracking, the proposed algorithm incorporates domain knowledge into the joint probabilistic data association (JPDA) filter as state constraints. The domain knowledge considered in this paper includes both road information extracted from a given map and local traffic regulations. Conventional track update method is modified to enhance the capability of recognition of temporarily track loss. A variable structure multiple model (VS-MM) method is developed to assign the road segment to a given target. The effectiveness of proposed algorithm is demonstrated through extensive numerical simulations.