基于变角速度螺旋线扫描的雷达目标截获优化策略

Radar Target-Acquisition Optimization Strategy Based on Variable Angular Velocity Spiral Scanning

  • 摘要: 鸟类、无人机等低空目标探测是当前雷达探测领域的研究热点。为实现低空目标种类与行为识别,必须对个体实现精细跟踪与观测。由于精密跟踪雷达不具备自行捕获目标的能力,当前通常采用大空域搜索雷达引导、精密跟踪雷达截获跟踪的探测体制。因此,目标的高概率截获是实现低空目标精准观测的关键。现有的平行扫描方法、圆周扫描方法、螺旋线扫描方法等目标截获方法采用匀速扫描模式,缺乏基于低空目标空间位置信息的针对性优化。为了实现有限时间内截获低空目标,本文提出了一种基于变角速度螺旋线扫描的雷达目标截获优化策略,根据最优搜索理论优化不同空间位置的扫描驻留时间,并基于逆变换采样求解非均匀螺旋线驻留时间分配方法;在此基础上,进一步提出一种基于目标检测逻辑的二次扫描策略,有效提升了目标截获概率。最后,本文通过仿真和高分辨雷达系统目标捕获实验验证了方法的有效性。

     

    Abstract: ‍ ‍The detection of low-altitude targets, such as birds and drones, is a current popular research topic under radar detection. Precise individual tracking and observation are required to achieve the recognition of low-altitude target categories and behaviors. Because precise tracking radars lack independent target-acquisition capabilities, the current radar system often adopts a cooperative mechanism in which large-airspace search radars provide indication information, enabling precision tracking radars to capture and track a target. Therefore, high acquisition probability is the key to achieving the efficient observation of low-altitude targets. Existing target-acquisition methods such as parallel scanning, circular scanning, and spiral scanning use a fixed search pattern, which lacks specific optimization for target indication information. To capture low-altitude targets in a limited time, this paper proposes a radar target-acquisition optimization strategy based on variable angular velocity spiral scanning. A method for allocating non-uniform spiral dwell time based on inverse transform sampling is proposed, which optimizes the scanning dwell time at different locations according to the optimal search theory. Subsequently, a supplementary scanning method based on target detection logic is proposed, which effectively improves the target-acquisition probability. Finally, simulation experiments and high-resolution radar system target-acquisition experiments verified the effectiveness of the method.

     

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