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Coherent Detection Method for Moving Platform Based Distributed Aperture Radar and Experimental Verification
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摘要: 动平台分布孔径雷达不仅可以通过多部小孔径雷达相参合成等效获得大孔径雷达的探测性能，也可进一步通过机动性和灵活部署增强探测与抗毁伤能力，是未来雷达重要发展方向之一。但由于多雷达间存在内部钟差和外部传播路径差，各雷达发射信号无法直接相参合成，需进行必要的时间和相位相参参数校正，且分布孔径雷达间距通常远超半波长，合成方向图将存在栅瓣问题，影响目标角度估计。为获得相参参数，该文以闭环式框架为基础，给出动平台分布孔径雷达认知相参框架，并结合运动条件下相参参数的变化规律，提出多脉冲关联相参参数估计方法以提升参数估计精度。同时，针对栅瓣问题，结合平台运动特性提出一种基于阵列构型累积的无模糊角度估计方法。最后，在仿真验证基础上基于所提框架设计了3节点地面动平台分布孔径雷达原理样机并开展了试验验证，试验结果表明在运动场景下，相比单部孔径雷达可以实现最高14.2 dB的信噪比增益，从而提升了目标的测距精度，同时在一定条件下实现了目标角度的无模糊测量，证明了所提方法和框架的有效性。该文工作将对未来分布孔径雷达的工程化实现及发展起到一定的引导作用。Abstract: As one of the most promising next-generation radars, Moving platform based Distributed Aperture Radar (MDAR) cannot only coherently combining distributed apertures to obtain the same detection performance of a large aperture, but also enhance the detection and anti-damage capabilities through mobility and flexible deployment. However, time and phase synchronization among radars should be done before coherently combining due to internal clock differences and external propagation path differences. Moreover, grating lobes will generate as the distance between multiple radars usually exceeds half a wavelength, which affects the estimation accuracy of target angle. To obtain Coherent Parameters (CPs), this paper established a cognitive framework for MDAR based on closed-loop structure. And a multi-pulse correlation CPs estimation method considering motion conditions is proposed to improve estimation accuracy. In the meanwhile, an unambiguous angle estimation method based on array configuration accumulation is proposed considering platform motion characteristics. Finally, based on the simulation verification and the proposed framework, a prototype of a 3-node ground Moving platform based Distributed Coherent Aperture Radar (MDCAR) system is designed and experiments are conducted. Compared to a single radar, a maximum value of 14.2 dB signal-to-noise ratio improvement can be achieved, which can further enhance range detection accuracy. Besides, unambiguous angle estimation is also realized under certain conditions. This work is expected to provide support for the research and development of MDCAR.
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图 5 方向图与阵列构型关系示意
Figure 5. Illustration of the relationship between array geometry and beam pattern
图 8 平台运动控制精度与相参合成效率的关系
Figure 8. Impact of platform control errors on coherent efficiency
图 13 原子钟频率随时间变化情况
Figure 13. Relationship between the frequency of the atomic clock and the time
表 1 相参参数估计仿真参数
Table 1. Simulation parameters of CPs estimation
参数 数值 节点数目 2 信号波形 正负线性调频信号 节点初始位置 [0, 0; 0, 50] m 发射中心频率 300 MHz 发射带宽 10 MHz 脉冲重复频率 2000 Hz 仿真持续时间 1 s 节点运动速度 [0, 10] m/s 目标初始位置 [ 10000 ,8000 ] m目标运动速度 [–200, 0] m/s 初始内部相位误差 0° 
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表 2 角度估计主要仿真参数
Table 2. Simulation parameters of angle estimation
参数 数值 节点数目 3 节点初始位置 [0, 0; 0, 1.5; 0, 3.0] m 发射中心频率 300 MHz 节点运动速度(相参情形) [0, 10; 0, 10; 0, 10] m/s 节点运动速度(非相参情形) [0, 10; 0, 20; 0, 30] m/s 脉冲重复间隔 25 ms 目标角度 10° 所用脉冲个数 3
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表 3 雷达参数
Table 3. Radar parameters
参数 数值 节点数目 3 发射中心频率 230 MHz 信号带宽 1 MHz 脉冲宽度 30 μs 脉冲重复频率 2000 Hz 认知-校正时延 0.5 s
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