Improved Azimuth Multichannel SAR Imaging for Configurations With Redundant Measurements

Abstract

The traditional spectrum reconstruction algorithm for nonuniform sampling of a displaced phase center antenna (DPCA) synthetic aperture radar (SAR) system can provide an unambiguous recovery of an original signal through the inverse computation of a joint filter matrix. However, when the sampling positions of different receivers coincide spatially, the joint filter matrix will be non-invertible, thus causing the ineffectiveness of the algorithm. This letter proposes a regularized spectrum reconstruction scheme when the pulse repetition frequency of a multichannel system operates on these critical frequencies, as well as in their neighborhoods. First, a low-order regularization of the joint filter matrix is suggested so that the original spectrum of the multichannel system can be recovered more accurately with a decreased number of nonredundant channels' measurements. Furthermore, in order to improve the output signal-to-noise ratio (SNR) of the reconstruction network, a combinational low-order spectrum recovery scheme is additionally presented, which takes all redundant channels' samples into account. The optimizations bring significant benefits to both the suppression of aliased ambiguities and the advance of the output SNR of the reconstruction network.Index Terms-Ambiguity suppression, displaced phase center antenna (DPCA), redundant samples, signal-to-noise ratio (SNR), spectrum reconstruction.

Modified reconstruction algorithm based on space-time adaptive processing for multichannel synthetic aperture radar systems in azimuth

“…The PRF of transmitted pulses is low to avoid range ambiguities, and all the received pulses from each receiver will be reconstructed with a high PRF to suppress azimuth ambiguities. In recent years, various Doppler spectrum reconstruction methods 11 – 17 have been proposed to reconstruct the signals from these multiple channels in azimuth, which could effectively suppress azimuth ambiguities and achieve HRWS imaging. Among the numerous processing methods, the space–time adaptive processing (STAP)–based approach is one of the most effective algorithms 11 .…”