It is a feasible and promising way to utilize deep neural networks to learn and extract valuable features from synthetic aperture radar (SAR) images for SAR automatic target recognition (ATR). However, it is too difficult to effectively train the deep neural networks with limited raw SAR images. In this paper, we propose a new approach to do SAR ATR, in which a multiview deep learning framework was employed. Based on the multiview SAR ATR pattern, we first present a flexible mean to generate adequate multiview SAR data, which can guarantee a large amount of inputs for network training without needing many raw SAR images. Then, a unique deep convolutional neural network containing a parallel network topology with multiple inputs is adopted. The features of input SAR images from different views will be learned by the proposed network layer by layer; meanwhile, the learned features from the distinct views are fused in different layers progressively. Therefore, the proposed framework is able to achieve a superior recognition performance, and requires only a small number of raw SAR images for network training samples generation. Experimental results have shown the superiority of the proposed framework based on the Moving and Stationary Target Acquisition and Recognition data set.

A new method of phase error estimation that utilizes the weighted least-squares (WLS) algorithm is presented for synthetic aperture radar (SAR)/inverse SAR (ISAR) autofocus applications. The method does not require that the signal in each range bin be of a certain distribution model, and thus it is robust for many kinds of scene content. The most attractive attribute of the new method is that it can be used to estimate all kinds of phase errors, no matter whether they are of low order, high order, or random. Compared with other methods, the WLS estimation is optimal in the sense that it has the minimum variance of the estimation error. Excellent results have been obtained in autofocusing and imaging experiments on real SAR and ISAR data

The rotation of structures in a target introduces additional frequency modulations on the returned signals and also generates sidebands about the center Doppler frequency of the target. In other words, the body image will be contaminated due to the interference from the rotating parts. In this paper, an imaging method for moving targets with rotating parts is presented. The method is simple to implement and is based on the Hough transform (HT), which is widely used in image processing. Using the standard HT and an extended HT, we put forward a separation method by detecting the straight lines and the sinusoids on the spectrogram, respectively. A computer simulation is given to illustrate the effectiveness of the proposed method.

New applications of nonlinear chirp scaling (NLCS) have been found in processing monostatic and bistatic SAR data acquired in the strip-map mode. When the effects in impulse response broadenings due to quadratic range migration are negligible for short radar wavelengths, a time domain range cell migration correction (RCMC) can be applied. After the correction, the FM rates of targets confined in a range gate will differ from each other. A nonlinear chirp perturbation function can be applied to each range gate to equalize the targets' FM rates before azimuth compression. This algorithm is analyzed in the paper and is supported by point target simulation experiments.

A broad bandwidth and high gain rectangular patch antenna was specifically designed in this paper using planar-patterned metamaterial concepts. Based on an ordinary patch antenna, the antenna has isolated triangle gaps and crossed strip-line gaps etched on the metal patch and ground plane, respectively. Demonstrated to have left-handed characteristics, the patterned metal patch and finite ground plane form a coupled capacitive-inductive circuit of negative index metamaterial. It is shown to have great impact on the antenna performance enhancement in terms of the bandwidth significantly broadened from a few hundred megahertz to a few gigahertz, and also in terms of high efficiency, low loss, and low voltage standing wave ratio. Experimental data show a reasonably good agreement between the simulation and measured results. This antenna has strong radiation in the horizontal direction for some specific applications within the entire band.