为了获取无源雷达中微弱目标回波的角度信息, 现有研究主要采用基于时延-Doppler域二维相关处理的估计算法, 其基本思想是通过参考信号和监视信号的互模糊函数来获得积累增益, 提升回波信号信噪比, 而后进行角度估计。该文针对高速多目标场景, 提出了一种更加高效稳健的时延-Doppler域角度估计算法。根据目标运动和外辐射源信号参数, 对参考信号和监视信号进行分段处理, 段内为快时间, 段间为慢时间; 考虑到目标高速运动可能引发距离徙动问题, 利用Keystone变换对各频率的时间轴进行尺度变换, 校正高速目标的距离徙动, 继而将目标回波信号能量积累至同一时延-Doppler域; 检测并提取目标回波所在时延单元的阵元慢时间采样信号, 并转化为慢时间维度的多快拍信号测角问题; 针对多目标场景下可能存在的相干信号, 利用均匀圆阵轴向虚拟平移解相干和多信号分类(MUSIC)算法对信号处理得到目标方位角和俯仰角估计。仿真实验结果表明： 所提出的算法可以以较低的计算复杂度实现无源雷达微弱目标回波信号的角度估计, 特别是在高速多目标场景下, 具有明显的性能优势。
Abstract
[Objective] The passive radar systems for urban aerial target surveillance highlight the importance of accurately determining the angle of arrival (AOA) of weak target echoes. The AOA information is crucial for locating targets using passive radars, considerably impacting the detection capabilities of the system. Traditionally, research on AOA estimation has focused on algorithms utilizing two-dimensional correlation processing in the delay-Doppler domain. These methods enhance the signal-to-noise ratio of the echo signal, leveraging the accumulated gain from the mutual ambiguity function between the reference signal and monitoring signals and subsequently facilitating angle estimation. However, existing algorithms face notable challenges. For instance, they are particularly prone to the distance migration effect when tracking weak targets moving at high speeds, adversely affecting the accumulation gain and the accuracy of parameter estimations. In addition, the computational requiremens of the mutual ambiguity function are high, complicating real-time implementation. Although certain rapid implementation methods for the mutual ambiguity function can reduce the computational requiremens, they are unsuitable for platforms with limited processing power. Additionally, current algorithms struggle to differentiate between multiple targets within the same range-Doppler unit owing to their inability to refine target distinction along the angle dimension. Considerably, this paper proposes a more efficient algorithm for delay-Doppler angle estimation tailored to high-speed, multitarget scenarios. [Methods] The proposed algorithm is divided into three steps. (1) The reference and monitoring signals undergo segmented processing; this division is based on the target movement and the signal parameters of the external radiation source, distinguishing between the fast time within each segment and the slow time across segments. (2) The second step addresses distance migration, which can occur owing to the high-speed movement of the target. Thus, the Keystone transform is used to adjust the time axis of each frequency, effectively correcting the distance migration for high-speed targets. Next, the energy of the target echo signal is aggregated into a singular delay-Doppler unit. The process continues with the detection and extraction of the slow time-sampling signal from the delay unit containing the target echo. This extracted signal forms the basis for converting the problem into one of the angle measurements, focusing on the multifast beat signal within the slow time dimension. (3) The target azimuth and pitch angles are estimated by employing axial virtual shift coherence within a uniform circular array. The multiple signal classification (MUSIC) algorithm is applied to these coherent signals for efficient processing in scenarios involving multiple targets. [Results] The algorithm can distinguish multiple targets in the same delay-Doppler cell. This differentiation is facilitated by the array axial virtual translation method, which improves the capability of the algorithm to process multiple-target signals. [Conclusions] Simulation results have demonstrated the effectiveness of the proposed method for the delay-Doppler processing, particularly its segmented processing combined with the Keystone transform, which corrects the distance migration of the target and greatly reduces the computational complexity. Consequently, the stability and the real-time performance of the algorithm are markedly improved. The algorithm exhibits obvious performance advantages, especially in scenarios characterized by high-speed movements and the presence of multiple targets.
关键词
无源雷达 /
均匀圆阵 /
高速目标 /
相干信号 /
角度估计 /
Keystone变换
Key words
passive radar /
uniform circular array /
high-speed target /
coherent signals /
angle estimation /
Keystone transform
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