Airborne Target Tracking Algorithm Using Multi-Platform Heterogeneous Information Fusion

PENG Ruihui; GUO Wei; SUN Dianxing; TAN Shuo; DOU Yuecong

doi:10.11999/JEIT240130

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PENG Ruihui, GUO Wei, SUN Dianxing, TAN Shuo, DOU Yuecong. Airborne Target Tracking Algorithm Using Multi-Platform Heterogeneous Information Fusion[J]. Journal of Electronics & Information Technology. doi: 10.11999/JEIT240130

Citation:

PENG Ruihui, GUO Wei, SUN Dianxing, TAN Shuo, DOU Yuecong. Airborne Target Tracking Algorithm Using Multi-Platform Heterogeneous Information Fusion[J]. Journal of Electronics & Information Technology. doi: 10.11999/JEIT240130

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Airborne Target Tracking Algorithm Using Multi-Platform Heterogeneous Information Fusion

doi: 10.11999/JEIT240130

PENG Ruihui¹,
GUO Wei^{1
,
,},
SUN Dianxing^{1, 2},
TAN Shuo³,
DOU Yuecong¹

1.
Qingdao Innovation and Development Base, Harbin Engineering University, Qingdao 266000, China
2.
Insitute of Information Fusion, Naval Aeronautical University, Yantai 264001, China
3.
China Academy of Aerospace Science and Technology Innovation, Beijing 100032, China

Received Date: 2024-03-04
Rev Recd Date: 2024-06-24

Available Online: 2024-06-03

Abstract

Abstract

An innovative aviation target tracking algorithm is presented in this paper, utilizing high-altitude unmanned airship dual photoelectric sensors in conjunction with (Unmanned Aerial Vehicle, UAV)-borne two-coordinate radar. The algorithm addresses the challenge of integrating sensor data to accurately track targets when individual sensors lack complete target position information, thus overcoming limitations of traditional point-trace association methods. Initially, a two-level point-trace correlation algorithm based on angle and distance is introduced for multi-sensor measurement association following coordinate system transformation. Subsequently, a line-plane intersection fusion localization algorithm is proposed to determine the initial target track position through techniques such as least squares method, intersection projection, distance nearest point solution, and homologous data compression. Leveraging heterogeneous information from space-based multi-platform reconnaissance, an extended Unscented Kalman Filter (UKF) is designed to track aviation targets by enhancing the traditional UKF. Simulation results demonstrate that this algorithm achieves superior precision in tracking high-speed aerial targets.
- Information fusion,
- Target tracking,
- Measurement association,
- Extended Unscented Kalman Filter (UKF),
- Space-based multi-platform

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References(16)

References

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