Investigations into optimum non-periodic bursts scheme in radar pulse train designed for fixed-wing drone detections by multi-function radar

IF 1.4 4区 管理学 Q3 ENGINEERING, ELECTRICAL & ELECTRONIC
Stanislaw Gmyrek, Dawid Sysak, Pawel Biernacki, Grzegorz Jaromi
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引用次数: 0

Abstract

Drone surveillance with multi-function radar (MFR) can benefit a lot from the careful radar pulse train organisation into dedicated sub-RPTs serving particular needs of tasks. In contemporary scenarios of MFR applications, where navigation, search and rescue, and natural environment safeguarding are to be shared, of particular importance is a case where airborne small drone detection radar performs other tasks concurrently. Resource sharing within the radar unit is based on variables and unpredictable circumstances, leading to strains in resources in MFR. Consequently, such constraints limit MFR functioning with optimal drone sensitivity for its own sake. To ensure a high quality of radar services performed quickly, with a low DC power consumption, the task sharing approach by the common MFR platform, non-periodic bursts emission of radar pulse energy has gained our major attention. At the same time, it was assumed that bursts feature periodic time intervals between radar pulses, which is a favourable circumstance in the control and implementation of signal processing. Each sub-RPTs is designed to cope with particular detection tasks. One to four linear polarisations (VV, VH, HV, HH) are activated. The focus of the investigation was on the radar emitting a few thousand pulses per second, but only a few 10 pulses per second were expected to be required to detect small airborne drones. The core of the research study was the optimisation process of the scheme operating with 4 to 16 pulse bursts optimised for drone detection with a modest use of resources at MFR. While performing several activities, the X-band MFR platform called ENAVI was developed in-house. The proposed non-periodic burst scheme optimisation approach was validated with in-field tests with the ENAVI radar model. The in-air target was a 3-metre fixed-wing drone having low RCS and flying at different altitudes with a speed close to 200 km/h. The radar antenna was a 26 dBi low-profile dual-polarisation array making it feasible to detect drones remaining a few degrees off the antenna breadboard direction. A very high likelihood of detection of drones from a few kilometres distance was demonstrated within one second. The authors present the effectiveness of the cell-averaging technique which proved to correctly detect drones within a 7-km range, and how MFR radar echoes can be used for basic weather surveillance. One vertical VV polarisation was used for drone detection and two VV and VH polarisations for weather observation. Weather radar capabilities were examined against heavy rain clouds imposing a hazard to the safety of drone flights.

Abstract Image

对多功能雷达探测固定翼无人机所设计的雷达脉冲序列中的最佳非周期性突发方案的研究
使用多功能雷达(MFR)进行无人机监视时,可通过将雷达脉冲序列精心组织成专用子 RPT 来满足任务的特定需求,从而获益匪浅。在多功能雷达的当代应用场景中,导航、搜救和自然环境保护等任务需要共享,其中尤为重要的是机载小型无人机探测雷达同时执行其他任务。雷达单元内的资源共享基于变量和不可预测的情况,导致 MFR 资源紧张。因此,这些制约因素限制了 MFR 以最佳无人机灵敏度运行。为了确保以较低的直流功耗快速提供高质量的雷达服务,由通用 MFR 平台进行任务分担的方法、非周期性的雷达脉冲能量突发发射受到了我们的高度关注。同时,我们假定突发的特点是雷达脉冲之间有周期性的时间间隔,这对信号处理的控制和实施是有利的。每个子 RPT 的设计都是为了应对特定的探测任务。可激活一至四个线性极化(VV、VH、HV、HH)。调查的重点是每秒发射几千个脉冲的雷达,但预计只需要每秒 10 个脉冲就能探测到小型机载无人机。研究的核心内容是优化方案的运行过程,优化后的方案具有 4 至 16 个脉冲串,可在适度使用 MFR 资源的情况下探测无人机。在开展多项活动的同时,还在内部开发了名为ENAVI的X波段MFR平台。利用ENAVI雷达模型进行的现场测试验证了所提出的非周期性脉冲串方案优化方法。空中目标是一架 3 米长的固定翼无人机,具有低 RCS,在不同高度飞行,速度接近 200 公里/小时。雷达天线是一个 26 dBi 的低剖面双极化阵列,可以探测到偏离天线面包板方向几度的无人机。结果表明,在一秒钟内就能探测到几公里外的无人机。作者介绍了单元平均技术的有效性,该技术被证明能正确探测到 7 千米范围内的无人机,并介绍了 MFR 雷达回波如何用于基本气象监测。一个垂直 VV 极化用于无人机探测,两个 VV 和 VH 极化用于气象观测。针对对无人机飞行安全造成危害的大雨云层,对气象雷达的能力进行了检验。
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来源期刊
Iet Radar Sonar and Navigation
Iet Radar Sonar and Navigation 工程技术-电信学
CiteScore
4.10
自引率
11.80%
发文量
137
审稿时长
3.4 months
期刊介绍: IET Radar, Sonar & Navigation covers the theory and practice of systems and signals for radar, sonar, radiolocation, navigation, and surveillance purposes, in aerospace and terrestrial applications. Examples include advances in waveform design, clutter and detection, electronic warfare, adaptive array and superresolution methods, tracking algorithms, synthetic aperture, and target recognition techniques.
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