The paper proposes a methodology to perform azimuth focusing of spaceborne transmitter-stationary receiver bistatic synthetic aperture radar (SAR) data across multiple along-track apertures to increase azimuth resolution. The procedure uses as input several azimuth apertures (continuous groups of range compressed pulses) from one or more satellite bursts and comprises the following stages: antenna pattern compensation, slow time resampling, reconstruction of missing azimuth samples between neighboring sets of pulses using an auto-regressive (AR) model and back-projection focusing of the resulting multi-aperture range image. A novel, highly efficient method is proposed to estimate the optimal order for the AR model. It differs from the traditional approach that uses the Akaike Information Criterion to directly estimate the order, because the proposed method estimates the order indirectly by detecting the number of targets using principle component analysis. Spatial Smoothing is used to obtain a full rank Covariance matrix, whose eigen values are then analyzed using Minimum Description Length. The optimal order is an integer multiple of the number of targets, which depends on SNR. The approach is evaluated with real bistatic data acquired over an area of Bucharest city, Romania.

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Bistatic radar receivers that use an opportunistic transmitter require a reference channel to capture the original transmitted signal, which is then used as a reference signal for constructing the matched-filter during the range compression step. Because the reference signal is received from line-of-sight, it is orders in magnitude larger than the reflections captured by the receive channel. It is generally difficult to construct the system such that the reference signal is not leaked into the received signal, either via coupling in the circuitry or via reflections off objects in the vicinity of the receiver. Due to its much larger amplitude, the reference signal can easily mask smaller targets with its side-lobes. In this paper we propose a novel deconvolution method for bistatic SAR images as a means of eliminating leakage of the reference signal.

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