利用机会发射器进行被动多目标跟踪

R. Tharmarasa, T. Kirubarajan, M. McDonald
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引用次数: 13

摘要

无源相干定位(PCL),利用商业信号(例如,调频广播,数字电视)作为照明机会,是防空系统中的一项新兴技术。PCL的优点是成本低,对电子对抗的脆弱性低,对隐身目标的早期发现和低空探测。然而,PCL的局限性包括缺乏对光源的控制,有限的可观测性以及由于低信噪比(SNR)而导致的较差的检测。这导致高杂波和低概率检测目标感兴趣。本文分析了PCL系统的多目标跟踪算法,以解决低检测概率和测量模型因测量误差大而产生的高非线性问题。在PCL雷达系统中实现了转换测量卡尔曼滤波器、无气味卡尔曼滤波器和基于粒子滤波的PHD滤波器,并进行了比较。仿真数据和实际数据表明了利用机会变送器跟踪机载目标的可行性。
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Passive multitarget tracking using transmitters of opportunity
Passive Coherent Location (PCL), which uses commercial signals (e.g., FM broadcast, digital TV) as illuminators of opportunity, is an emerging technology in air defense systems. The advantages of PCL are low cost, low vulnerability to electronic counter measures, early detection of stealthy targets and low-altitude detection. However, limitations of PCL include lack of control over illuminators, limited observability and poor detection due to low Signal-to-Noise Ratio (SNR). This leads to high clutter with low probability of detection of target of interest. In this paper, multiple target tracking algorithms for PCL systems are analyzed to handle low probability of detection and high nonlinearity in the measurement model due to high measurement error. The converted measurement Kalman filter, unscented Kalman filter and particle filter based PHD filter are implemented and compared for PCL radar systems. The feasibility of using transmitters of opportunity for tracking airborne targets is shown on simulated and real data sets.
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