An effective operation mode and a space-time synchronization technique for the spaceborne/airborne hybrid bistatic synthetic aperture radar (SA-BSAR) using sources of opportunity are presented. Our motivation lies in the fact that the existing approaches in the literature, where the transmitter antenna must be steered, can only be used in the hybrid bistatic SAR systems with cooperative transmitter. The presented mode is to widen the receiving beam for the purpose to increase the scene extension in azimuth. The inspiration comes from the much shorter receiving distance as compared to the one in mono-static spaceborne SAR. This means that the receiving gain can be significantly reduced to provide the same signal-to-noise ratio (SNR) with respect to the mono-static case. The feasibility of the wide-beam mode is first preliminarily verified by a quantitative analysis of SNR and a demonstration that the pulse repetition frequency (PRF) used in the spaceborne illuminator can easily satisfy the PRF constraints of the SA-BSAR. The influence on the azimuth ambiguity to signal ratio (AASR) is also discussed and the corresponding broadening factor of the maximum allowable for receiver beamwidth is subsequently derived. Afterwards, the formulae for calculating the overlap time, the scene extension and the azimuth resolution are deduced. As there are no grating lobes in satellite antenna pattern since the non-cooperative illuminator normally operates in the side-looking mode, an existing technique for the space-time synchronization in cooperative hybrid systems can not be directly applied. The modification performed and its underlying principle are presented in detail. The simulation results demonstrate the effectiveness of the wide-beam mode, and show that in most cases a useful scene extension (on the order of at least 1 km) can be achieved with a roughly equivalent azimuth resolution as compared to the one in mono-static spaceborne SAR. In some cases, explicit measures to suppress the azimuth ambiguity must be taken to achieve the expected scene extension.

Tomo-SAR imaging with sparse baselines can be formulated as a sparse signal recovery problem, which suggests the use of the Compressive Sensing (CS) method. In this paper, a novel Tomo-SAR imaging approach based on Sparse Bayesian Learning (SBL) is presented to obtain super-resolution in elevation direction and is validated by simulation results.

A new constant false alarm rate (CFAR) detection scheme based on the goodness-of-fit (GoF) test is proposed to deal with the problem of extended object detection in high resolution synthetic aperture radar (SAR) images. The performance of this detector is compared with that of the traditional detectors using the MSTAR database. Results show that the proposed detector is superior to the traditional detectors in controlling false alarms in nonhomogeneous environment where boundaries widely exist.

This paper develops a complete architecture for constant false alarm rate (CFAR) detection based on a goodness-of-fit (GOF) test. This architecture begins with a logarithmic amplifier, which transforms the background distribution, whether Weibull or lognormal into a location-scale (LS) one, some relevant properties of which are exploited to ensure CFAR. A GOF test is adopted at last to decide whether the samples under test belong to the background or are abnormal given the background and so should be declared to be a target of interest. The performance of this new CFAR scheme is investigated both in homogeneous and multiple interfering targets environment.