Abstract：The traditional sparse aperture methods are not suitable for signal processing of Inverse Synthetic Aperture Imaging Ladar (ISAIL) for the following reasons. One is the lack of echoes caused by the noncooperation characteristic of the target, the other is the low Signal-to-Noise Ratio (SNR) caused by the influence of atmosphere attenuation and natural background light. For this reason, a novel sparse aperture imaging method is proposed in this paper which combines the Compressed Sensing (CS) with the weighted matrix. Through the preprocessing of CS based imaging, the supporting field of the target can be obtained, with which the weighted matrix can be constructed. Then the cost function is optimized using the weighted matrix. Finally, with this new cost function, the high resolution image can be achieved using the incomplete original echoes from the sparse aperture ISAIL. This new method is robust in front of strong noise. The feasibility and effectiveness of the method are validated by the measured data of the indoor ISAIL system.
2010, Vol. 32 
