Airborne Distributed Coherent Aperture Radar Synchronization Error Calibration Method Based on Prominent Points
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摘要:
机载分布式相参雷达(DCAR)相比较于地基DCAR具有探测距离远、机动性高和部署灵活等优势，然而，载机平台运动使得机载DCAR面临更加严格的时间、空间和相位同步要求。为此，该文建立了基于慢时间码分多址(ST-CDMA)波形的机载DCAR信号模型及其矩阵表示形式，分析了时间、空间和相位同步误差对目标相参合成的影响，并提出一种基于特显点的机载DCAR同步误差校正方法。该方法首先采用目标参数搜索的方式消除滤波器网格失配误差；接着，利用基于目标的估计方法或者基于中继的估计方法完成单元位置误差校正；最后，利用特征结构方法校正等效幅相误差。仿真实验验证了所提方法的有效性。
Abstract:Airborne Distributed Coherent Aperture Radar (DCAR) has the advantages of wide observation range, high maneuverability and flexible deployment. However, airborne DCAR is confronted with more stringent time, space and phase synchronization requirements. Therefore, an airborne DCAR signal model and its matrix representation based on Slow-Time Code Division Multiple Access (ST-CDMA) waveform are established successively. Moreover, the influence on target coherence synthesis resulted from time, space and phase synchronization errors is analyzed in detail, and a novel airborne DCAR synchronization error calibration method based on prominent points is proposed. This method utilizes the target parameter search strategy to eliminate the grid mismatch filtering firstly. Then, with the utilization of estimation approaches based on target model or repeater station model, the unit platform position error is calibrated. Finally, equivalent amplitude and phase errors are calibrated by Eigen structure methods. The validity of the proposed method to calibrate the airborne DCAR synchronization error is demonstrated by simulation experiments.
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表 1 算法时间复杂度比较
算法 时间复杂度 基于目标+特征结构 $O(MPW){\rm{ + }}O(2{M^6})$ 基于中继+特征结构 $O\left(\displaystyle\sum\nolimits_{\tilde m{\rm{ = } }1}^M { { {\tilde m}^2}PW} \right){\rm{ + } }O(2{M^6})$ 联合估计方法 $O(MPW) + O\left(\displaystyle\sum\nolimits_{\tilde m{\rm{ = } }1}^M { { {\tilde m}^2}PW} \right){\rm{ + } }O(4{M^6})$ 
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表 2 不同方法估计的时间同步误差比较 (μs)
单元雷达序号 2 3 4 实际时间同步误差 2.0368 2.2645 0.3175 基于目标的方法的估计误差 2.0350 2.2650 0.3175 联合方法的估计误差 2.0350 2.2650 0.3175
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