Rajarshi Biswas, Akash S. Doshi, Akankshya Bhatta, S. R. Pillai
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引用次数: 0
Abstract
Employing multiple wide aperture radars with partially overlapping coverage to accurately track moving objects is becoming increasingly popular. However, identifying a common track across the radars can be challenging when each radar sensor obtains multiple measurements from different targets in its field of view. The presence of clutter and spurious measurements further complicates this problem. Data association and target tracking in this context can benefit from the combined processing of the sensor measurements. We adapt the well known single sensor Viterbi Data Association (VDA) algorithm to exchange information between multiple sensors, thereby reinforcing the target tracking performance. The proposed multi-sensor data fusion algorithm is demonstrated to have vastly improved performance over conventional single sensor techniques.
采用多部部分重叠覆盖的大孔径雷达来精确跟踪运动目标已成为一种越来越流行的方法。然而,当每个雷达传感器从其视场中的不同目标获得多个测量值时,识别雷达上的共同轨迹可能具有挑战性。杂波和虚假测量的存在使这个问题进一步复杂化。在这种情况下,数据关联和目标跟踪可以受益于传感器测量的组合处理。我们采用了著名的单传感器VDA (Viterbi Data Association)算法在多个传感器之间交换信息,从而增强了目标跟踪性能。所提出的多传感器数据融合算法被证明比传统的单传感器技术有很大的改进。