External Information Aided Urban Target Tracking with UAVs

Jianduo Chai, Yue Hou, Shaoming He*

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

This paper addresses the challenging problem of airborne target tracking in complex urban contexts by incorporating external information. Both extrinsic and intrinsic elements are mathematically formulated to constrain the motion of the target. A Bayesian method, aided by a data-driven pattern matching mechanism, is proposed for recognizing the target's behavior and allocating appropriate constraints to the ground target. A quadratic programming problem is formulated to integrate the constraint relations into the target tracking process. The target's distribution is obtained using Generalized Covariance Intersection (GCI) to fuse the state distribution calculated from each local tracker. The proposed method's advantages are analyzed and validated through numerical simulations.

Original languageEnglish
Title of host publication2023 Asia-Pacific International Symposium on Aerospace Technology, APISAT 2023, Proceedings - Volume II
EditorsSong Fu
PublisherSpringer Science and Business Media Deutschland GmbH
Pages48-64
Number of pages17
ISBN (Print)9789819740093
DOIs
Publication statusPublished - 2024
EventAsia-Pacific International Symposium on Aerospace Technology, APISAT 2023 - Lingshui, China
Duration: 16 Oct 202318 Oct 2023

Publication series

NameLecture Notes in Electrical Engineering
Volume1051 LNEE
ISSN (Print)1876-1100
ISSN (Electronic)1876-1119

Conference

ConferenceAsia-Pacific International Symposium on Aerospace Technology, APISAT 2023
Country/TerritoryChina
CityLingshui
Period16/10/2318/10/23

Keywords

  • constrained filter
  • data fusion
  • pattern matching
  • Target tracking

Cite this