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The automatic detection of UAVs and drones presents a significant challenge due to their low flight altitude and operation in complex environments with diverse clutter characteristics. Radar sensors, especially passive radar systems, are considered a viable solution for tracking UAVs with a small radar cross section (RCS). This paper investigates a passive radar system that uses the P1 symbol in DVB-T2 signals for general target detection. In particular, the article provides a detailed assessment of the impact of clutters, modeled using Weibull, Lognormal, Rayleigh, and Gaussian distributions, on target detection performance. The analysis is carried out through Monte Carlo simulations with the Swerling 5 target model. The results demonstrate that clutter significantly affects system performance, with different types of clutter exhibiting different statistical characteristics that influence detection differently. These findings underscore the importance of selecting an appropriate clutter model when designing and evaluating passive radar performance.

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Effect of Clutter Models on Radar Sensor Detection of Aerial Targets Using DVB-T2 P1 Symbol

  • 会议论文

  • 发表日期：

    2026年

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  • Quang-Huy Duong,
  • Van-Phuc Hoang,
  • Tien-Hai Nguyen,
  • Thi-Thuy-Linh Le

摘要

The automatic detection of UAVs and drones presents a significant challenge due to their low flight altitude and operation in complex environments with diverse clutter characteristics. Radar sensors, especially passive radar systems, are considered a viable solution for tracking UAVs with a small radar cross section (RCS). This paper investigates a passive radar system that uses the P1 symbol in DVB-T2 signals for general target detection. In particular, the article provides a detailed assessment of the impact of clutters, modeled using Weibull, Lognormal, Rayleigh, and Gaussian distributions, on target detection performance. The analysis is carried out through Monte Carlo simulations with the Swerling 5 target model. The results demonstrate that clutter significantly affects system performance, with different types of clutter exhibiting different statistical characteristics that influence detection differently. These findings underscore the importance of selecting an appropriate clutter model when designing and evaluating passive radar performance.