Instantaneous UAV tracking using single-photon LiDAR via photon-event-driven suppression of temporal-averaging bias
通过光子事件驱动抑制时间平均偏差，利用单光子激光雷达实现无人机瞬时跟踪
光子イベント駆動による時間平均バイアスの抑制を用いた単一光子LiDARによる瞬間的なUAV追跡
단일 광자 LiDAR를 이용한 순간적인 UAV 추적: 시간 평균 편향의 광자 이벤트 기반 억제
Rastreo instantáneo de UAV mediante LiDAR de fotones únicos mediante supresión de sesgo de promediado temporal impulsado por eventos de fotones
Suivi instantané des UAV à l'aide de LiDAR à photons uniques via la suppression du biais de moyenne temporelle par événement de photon
Мгновенное отслеживание БПЛА с использованием однопорцельного лидара через подавление временного усреднения по событиям фотонов
Dongfang Guo ¹, Jianfeng Sun ¹ ², Xin Zhou ¹ ² ³, Chen Shen ⁴, Sheng Chen ¹ ², Sining Li ¹, Yanchen Qu ¹
¹ National Key Laboratory of Laser Spatial Information, Harbin Institute of Technology, Harbin, 150000, China
中国 哈尔滨 哈尔滨工业大学激光空间信息全国重点实验室
² Zhengzhou Research Institute, Harbin Institute of Technology, Zhengzhou, 450000, China
中国 哈尔滨 哈尔滨工业大学郑州高等研究院
³ Research Center for Space Optical Engineering, Harbin Institute of Technology, Harbin, 150000, China
中国 哈尔滨 哈尔滨工业大学空间光学工程研究中心
⁴ School of Electrical and Electronic Engineering, Nanyang Technological University, Jurong West, 639798, Singapore
Single-photon LiDAR offers photon-level sensitivity for long-range detection, yet its application to dynamic targets like low-altitude Unmanned Aerial Vehicle (UAV) is bottlenecked by motion-induced temporal-averaging bias. When target motion exceeds spatial resolution within a sampling interval, conventional multi-frame accumulation blurs the instantaneous spatial and temporal coordinates. Here, we introduce a photon-aware three-dimensional dynamic tracking framework (P3DTT) that suppresses this bias by transitioning to a multi-dimensional, photon-event-driven observation space.
By integrating spatio-temporal-frame photon-event statistical modeling with a Random Sample Consensus-based iterative fitting scheme, P3DTT extracts instantaneous, unbiased target positions under extreme photon starvation. Monte Carlo simulations demonstrate accurate 3D-position correction and tracking of target moving up to 188.8 m/s at 2 km under 0.2184 photons per pixel and a Signal-to-Noise Ratio (SNR) of −8.37 dB. The photon-arrival time fitting error is reduced from 4.71 ns to 0.33 ns (about 14-fold improvement), while the 3D tracking error reached 0.16 m. Field experiments conducted with the custom-developed Geiger-mode avalanche photodiode (Gm-APD) single-photon LiDAR demonstrate reliable UAV tracking at 2.5 km under only 0.2731 photons per pixel and an SNR of −7.68 dB. P3DTT consistently recovered unbiased instantaneous 3D-position, achieving tracking errors below 0.43 m.
This work establishes a new computational paradigm, pushing single-photon LiDAR beyond integral imaging towards instantaneous perception for low altitude monitoring.
