Online Moving Interference Target Perception and Suppression for Passive Radar Detection of UAVs

TY - JOUR

T1 - Online Moving Interference Target Perception and Suppression for Passive Radar Detection of UAVs

AU - Wang, Tianrun

AU - Liu, Shengheng

AU - Feng, Yuan

AU - Liu, Yingshi

AU - Wen, Chenyu

AU - Wang, Zhi

AU - Wang, Zhenghang

AU - Shan, Tao

N1 - Publisher Copyright: © 2026 The Author(s). IET Radar, Sonar & Navigation published by John Wiley & Sons Ltd on behalf of The Institution of Engineering and Technology.

PY - 2026/1/1

Y1 - 2026/1/1

N2 - This paper addresses moving interference targets (MITs) in passive radar detection of low-altitude unmanned aerial vehicles (UAVs) by introducing a strategy that reinterprets strong scattering interference as target-like responses. An online perception of MIT-dominated areas is achieved through spatiotemporal statistical analysis and iterative processing of detection results. Targets within these identified areas are subsequently removed, effectively suppressing low-altitude MITs and reducing the false-alarm rate. A method for estimating the occurrence frequency of low-altitude interference targets based on a first-order autoregressive model is developed. This paper provides a detailed theoretical analysis of the weight-update mechanism and includes a proof of the algorithm's convergence. Furthermore, a dynamic-coefficient method and an adaptive-coefficient method are introduced to enhance convergence performance and enable adaptive adjustments to changes in the target-occurrence frequency. Simulation results demonstrate that the proposed algorithm converges within 100 iterations and achieves a postconvergence standard deviation of 0.0078. Field experiments show removal rates of 87.5% and 72.9% for low-altitude interference targets, with corresponding UAV false-removal rates of 20.26% and 4.17%, respectively.

AB - This paper addresses moving interference targets (MITs) in passive radar detection of low-altitude unmanned aerial vehicles (UAVs) by introducing a strategy that reinterprets strong scattering interference as target-like responses. An online perception of MIT-dominated areas is achieved through spatiotemporal statistical analysis and iterative processing of detection results. Targets within these identified areas are subsequently removed, effectively suppressing low-altitude MITs and reducing the false-alarm rate. A method for estimating the occurrence frequency of low-altitude interference targets based on a first-order autoregressive model is developed. This paper provides a detailed theoretical analysis of the weight-update mechanism and includes a proof of the algorithm's convergence. Furthermore, a dynamic-coefficient method and an adaptive-coefficient method are introduced to enhance convergence performance and enable adaptive adjustments to changes in the target-occurrence frequency. Simulation results demonstrate that the proposed algorithm converges within 100 iterations and achieves a postconvergence standard deviation of 0.0078. Field experiments show removal rates of 87.5% and 72.9% for low-altitude interference targets, with corresponding UAV false-removal rates of 20.26% and 4.17%, respectively.

KW - interference suppression

KW - passive radar

KW - radar detection

UR - https://www.scopus.com/pages/publications/105033086139

U2 - 10.1049/rsn2.70120

DO - 10.1049/rsn2.70120

M3 - Article

AN - SCOPUS:105033086139

SN - 1751-8784

VL - 20

JO - IET Radar, Sonar and Navigation

JF - IET Radar, Sonar and Navigation

IS - 1

M1 - e70120

ER -