斜视模型下的被动合成孔径定位算法

    Passive Synthetic Aperture Localization Algorithm in Squint Model

    • 摘要: 在合成孔径定位中,斜视模式相比正侧视模式更具灵活性,能够更有效地适应复杂环境下的目标定位。但是,斜视模式下多普勒中心频率不再为零,方位定位结果会出现偏差。针对这一问题,文中提出了一种基于斜视合成孔径的无源定位算法。首先,该算法构建了全孔径模式下的斜视定位模型,通过线性相位调制补偿了多普勒中心,有效校正了多普勒中心频率的偏移,从而消除了定位偏差;然后,通过匹配滤波的方式实现方位聚焦,获得了目标的聚焦图像;最后,通过几何校正的方法,消除了方位偏差的空变特性,得到了精确的定位结果。仿真分析和蒙特卡洛实验结果表明,该算法能够在低信噪比下有效提升定位精度。实测数据也验证了该算法的有效性和正确性。

       

      Abstract: In synthetic aperture localization, the squint mode is more flexible compared to the broadside mode, and can better adapt to target localization in complex environments. However, the Doppler center frequency is no longer zero in squint mode, resulting in azimuth localization errors for the target. To address this issue, a passive localization algorithm based on squint synthetic aperture is proposed in this paper. First, the algorithm constructs a squint positioning model in full aperture mode, which compensates for the Doppler center through linear phase modulation and effectively corrects the frequency offset of the Doppler center, thereby eliminating positioning deviations. Then, azimuth-focusing is achieved through matched filtering to obtain focused image of the target. Finally, geometric correction is employed to eliminate the spatial variability of azimuth bias, thereby achieving accurate localization results. Simulation analysis and Monte Carlo experiment results demonstrate that the proposed algorithm can effectively enhance localization accuracy under low signal-to-noise ratio. Experimental data further validate the effectiveness and correctness of the proposed algorithm.

       

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