Tian Jihua

Motion compensation for Compressive Sensing SAR imaging with autofocus

The high resolution required by various modes of Synthetic Aperture Radar (SAR) results in a huge amount of sampling data, which brings a demand for bigger storage. Recently, a novel SAR concept based on Compressive Sensing (CS) theory asserts that an unknown sparse signal can be recovered exactly with an overwhelming probability even from what appear to be highly sub-Nyquist-rate samples. In this paper, the phase errors caused by radar platform motion are discussed for CS based SAR imaging, and autofocus processing is employed to implement motion compensation. The experiment results show that unfocused SAR images through CS recovery are different from conventional unfocused SAR images for the same motion caused phase error, and usually used Phase Gradient Autofocus (PGA) algorithm is still effective to CS based SAR motion compensation.

The effects of input signal-to-noise ratio on compressive sensing SAR imaging

Synthetic Aperture Radar (SAR) is an active and coherent microwave high resolution imaging system, which has the capability to image in all weather and day-or-night conditions. The high resolution required by various modes of SAR results in a huge amount of sampling data, which brings a demand for bigger storage. Recently, a novel concept based on Compressive Sensing (CS) theory asserts that an unknown sparse signal can be recovered exactly with an overwhelming probability even with highly sub-Nyquist-rate samples. In this paper, a new scheme for the test bed of CS based SAR imaging is proposed. Experimental results on some real raw SAR data reveal that there are some practical limitations on the use of CS based SAR imaging, especially for complex imaging scenes and systems with low Signal-to-Noise Ratio (SNR).

Space-time adaptive processing for sea clutter and jamming suppression in radar seekers

When radar seeker searches and tracks moving target on sea surface, sea clutter spectra severely spread out due to the strong effect of sea conditions. Conventional methods for suppressing sea clutter have achieved poor performance. This paper mainly analyzes the sea clutter characteristics in azimuth-Doppler domain and clutter spectra with different scanning angles. Then space-time adaptive processing (STAP) technique is applied to suppress sea clutter. Research results indicate that sea clutter spectra have some special characteristics in space-time distribution, and the proposed STAP algorithm can detect slow moving targets effectively as it can suppress sea clutter and strong jamming.