一种利用车载雷达确定相关目标车辆的鲁棒方法

L. Zhifeng, Wang Jianqiang, L. Keqiang
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引用次数: 1

摘要

为了解决车载雷达测量环境的复杂性导致相关目标选择不稳定的问题,提出了一种利用车载雷达确定相关目标的鲁棒方法。该方法在分析测量环境的基础上,利用同一车道内最近目标的原理进行目标预选。采用卡尔曼滤波对目标信息进行预测,并通过一致性检查对预选目标进行相关性验证。目标决策是通过“相关目标生命周期”方法做出的。验证试验表明,该方法有效地消除了鬼影物体、其他干扰和车辆的颠簸摆动的影响,可以在不同条件下完成相关目标的确定。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A robust method to determine relevant target vehicle using vehicular radar
In order to solve the problem of the instability in the selection of relevant target, caused by the complexity of the measurement environment of vehicular radar, a robust method to determine the relevant target using vehicular radar is proposed. Based on analyzing the measurement environment, the method uses the principle of the nearest object in the same lane for target pre-selection. The Kalman filter is applied to predict the target information and the relevance verification of the pre-selected target is done by the consistence checking. The target decisions are made through a "relevant target life cycle" method. The verification tests show that by efficiently eliminating the effects of ghost objects, other disturbances and the bumping and swinging of vehicle, the proposed method can accomplish the determination of relevant target under different conditions.
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