稀疏子带的多频段雷达信号融合超分辨距离成像

The Super-Resolution Range Imaging Based on Sparse Band Multiple Frequency Bands Radars Signal Fusion

多频段雷达信号融合是提高目标距离分辨率的一种有效方法,在稀疏子带观测条件下,由于信号频带稀疏,传统的相位补偿和融合成像方法难以应用,为此本文在线性调频信号体制下,基于修正的多重信号选择(MU-SIC)算法提出了一种新的参数化融合成像方法.该方法首先对信号离散序列进行均匀采样处理,然后对多个频带的雷达信号统一建模,将相位补偿参数与目标散射中心参数一起估计,理论分析和仿真结果表明该方法能够有效融合多频段的雷达观测信号,改善目标一维距离像的分辨率.

The signal fusion of multiple frequency bands and multiple radars is an effective method to improve the resolution of target range profile. With the sparse band observation, the conventional phase compensation methods in signal fusion are invalid because the frequency bands are sparse. A new super-resolution range imaging method based on the modified MUSIC （ multiple signal classification） algorithm is presented with liner frequency modulated signal. Firstly, the uniform B-splines is applied to resample the signals for obtaining the uniform signal sequences. Secondly, the signal model of multiple radars with multiple frequency bands is established. Consequently, the phase compensation parameter and the scatter center parameters are estimated based on the uniform signal model. The theoretical analysis and simulations results show the presented signal fusion imaging method can effectually increase signal bandwidth and obtain super-resolution range image under sparse frequency band observations conditions.