Multi-Sensor Network-Based Three-Dimensional Positioning Algorithm for Airborne Targets

PENG Rui-hui; GUO Wei; QIAN Hai-ning; TAN Shun-cheng; TAN Shuo

doi:10.12263/DZXB.20240300

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Multi-Sensor Network-Based Three-Dimensional Positioning Algorithm for Airborne Targets

PAPERS | 更新时间：2025-12-11

- Multi-Sensor Network-Based Three-Dimensional Positioning Algorithm for Airborne Targets
- ACTA ELECTRONICA SINICA Vol. 52, Issue 12, Pages: 4059-4073(2024)
- 作者机构：
  
  1.哈尔滨工程大学信息与通信工程学院，黑龙江哈尔滨 150001
  2.哈尔滨工程大学青岛创新发展中心，山东青岛 266000
  3.海军航空大学信息融合研究所，山东烟台 264001
  4.中国航天科技创新研究院，北京 100032
- 作者简介：
- 基金信息：
  
  National Defense Science and Technology Key Laboratory Fund(2023-JCJQ-LB-016);Stable Support Project of Aerospace Science and Technology Corporation(ZY0110020009)
- DOI：10.12263/DZXB.20240300
  CLC： TP212.9;
- Received：08 April 2024，
  
  Revised：2024-07-24，
  
  Published：25 December 2024
- 稿件说明：
移动端阅览
彭锐晖, 郭玮, 钱海宁, 等. 多传感器组网的航空目标三维定位算法[J]. 电子学报, 2024, 52(12): 4059-4073.

PENG Rui-hui, GUO Wei, QIAN Hai-ning, et al. Multi-Sensor Network-Based Three-Dimensional Positioning Algorithm for Airborne Targets[J]. Acta Electronica Sinica, 2024, 52(12): 4059-4073.
彭锐晖, 郭玮, 钱海宁, 等. 多传感器组网的航空目标三维定位算法[J]. 电子学报, 2024, 52(12): 4059-4073. DOI：10.12263/DZXB.20240300

PENG Rui-hui, GUO Wei, QIAN Hai-ning, et al. Multi-Sensor Network-Based Three-Dimensional Positioning Algorithm for Airborne Targets[J]. Acta Electronica Sinica, 2024, 52(12): 4059-4073. DOI：10.12263/DZXB.20240300

摘要

由于航空目标相对地面目标具有更快的运动速度、更广的运动范围，对航空目标的三维精确定位极具挑战性.本文提出了一种多传感器组网的航空目标三维定位算法，以两个高空无人飞艇各载一部光学传感器设备，无人机-艇载双基地两坐标雷达，多平台协同实现对航空目标的精确定位为研究背景，解决了由于各传感器量测维度欠完备、无法独立获得目标三维空间精确位置，导致传统点迹关联、目标定位方法失效等问题.首先，在空间对准的基础上提出了基于角度-距离两级点迹关联算法，实现多传感器缺维量测的有效关联；其次，通过目标引导点构建、椭球空间Nelder-Mead欧氏距离寻优、方位面空间投影，在各空间量测模型上确定目标初始定位点；最后，通过无迹变换和同源数据压缩得到目标精确定位点.仿真结果表明，该算法实现了缺维情况下雷达-双光学量测数据的稳定关联，且对航空目标的最优定位误差可达到115.7 m.

Abstract

Accurately locating aviation targets in three dimensions presents formidable challenges owing to their high-speed movements and expansive maneuverability compared to ground targets. This paper presents a three-dimensional positioning algorithm for aerial targets based on a multi-sensor network. Using two high-altitude unmanned airships

each equipped with an optical sensor device

and UAV-shipborne bistatic dual-coordinate radars

the study focuses on achieving precise positioning of aerial targets through multi-platform collaboration. This approach addresses the limitations of traditional methods

which often fail due to the incomplete measurement dimensions of individual sensors

preventing accurate independent determination of the target’s 3D spatial position. Our approach begins with the introduction of a two-level point-trace correlation algorithm grounded in spatial alignment

leveraging both angle and distance to effectively correlate non-dimensional measurements from multiple sensors. Subsequently

we establish the initial positioning points of the target on each spatial measurement model through the construction of target guidance points

employing techniques such as ellipsoidal space Nelder-Mead Euclidean distance optimization and azimuth space projection. Finally

precise positioning points of the target are obtained through the utilization of unscented transform and homologous data compression.Simulation results demonstrate the efficacy of our algorithm in achieving stable correlation of radar-dual optical measurement data

even in scenarios where dimensionality is lacking. Notably

our algorithm achieves an optimal positioning error for aviation targets as low as 115.7 meters.

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references

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