Forward looking imaging has broad application prospects, array radar is widely applied to angular super-resolution in forward-looking imaging. Based on the derived array radar forward-looking echo model, forward-looking imaging algorithms based on MUSIC estimation and single snapshot data sparse decomposition are given. Also, an algorithm based on joint sparse decomposition of multi-pulse amplitude and phase data is proposed. The imaging performance of the above three algorithms are analyzed. Experimental results demonstrated that the multi-pulse amplitude and phase data joint sparse decomposition algorithm has the highest resolution and is suitable for complex scenes.
Azimuth super-resolution is generally realized by real beam scanning deconvolution and array antenna super-resolution algorithms, especially by using amplitude envelope or phase information. Aiming at the situation that echo information is not fully utilized, this paper proposes a forward looking imaging method of array radar scanning based on compressed sensing, combining the real beam scanning by transmitter and the echo receiving by array antenna. Under the condition of sparse scene, the range dimension super-resolution is achieved by pulse compression, and the azimuth direction complex observation matrix is constructed based on the array antenna echo model, and the super-resolution is achieved by improved L1 norm smoothing approximation algorithm. The 2d super-resolution imaging simulation results show that the proposed method can effectively improve the performance.
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