In sea clutter background, spaceborne or airborne surveillance radar with a high-speed moving platform is confronted with the problem of clutter spreading. This poses a considerable challenge for maritime radar systems when detecting slowly moving targets of low signal-to-noise ratio. However, the space-time decorrelation characteristics caused by the internal motions of sea clutter under different sea conditions are mostly neglected in the current detecting techniques, which go against the reliable parameter selection in the clutter suppression process. An innovative multi-channel space-time decorrelation analysis method based on sea clutter is proposed. First, the channel decorrelation factors caused by the channel amplitude-phase errors and the noise are calculated by fusing the calibration signal with echo data. Then, the temporal decorrelation curve caused by the internal motions of sea clutter is obtained by fitting the peak points of multi-channel correlation coefficient curve based on the multi-channel phase center. Finally, the independent spatial decorrelation curve is derived through calculating the multi-channel correlation coefficients of different range bins. Due to the utilization of space-time characteristics decomposition method for sea clutter, the space-time coupling problem can be solved effectively. The experimental results based on the measured data prove the effectiveness of the proposed method.
In high-resolution bistatic synthetic aperture radar (SAR) systems, parameter estimation is essential to moving target imaging quality. However, precise parameters are difficult to obtain without priori information due to the relative along-track and across-track velocities between the moving target and platforms that change with time. A parameter estimation and imaging approach for moving targets is proposed. First, slant range and relative velocities expression are deduced based on the geometry of bistatic SAR model with one stationary configuration. Then, range curvature term are compensated skillfully by fitting the range-compressed curve in two-dimensional time domain, meanwhile, the initial estimated range walk slope can be achieved. Finally, precise Doppler centroid is estimated through searching for the maximum contrast with folding search algorithm, which is giving consideration to both searching precision and computational complexity. Thus, the proposed algorithm provides an effective way for parameter estimation and imaging of moving target without prior information and interpolation operation. Experimental results show the effectiveness of the proposed method.
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