Higher order nonlinear chirp scaling algorithm for medium Earth orbit synthetic aperture radar

Abstract

Abstract. Due to the larger orbital arc and longer synthetic aperture time in medium Earth orbit (MEO) synthetic aperture radar (SAR), it is difficult for conventional SAR imaging algorithms to achieve a good imaging result. An improved higher order nonlinear chirp scaling (NLCS) algorithm is presented for MEO SAR imaging. First, the point target spectrum of the modified equivalent squint range model-based signal is derived, where a concise expression is obtained by the method of series reversion. Second, the well-known NLCS algorithm is modified according to the new spectrum and an improved algorithm is developed. The range dependence of the twodimensional point target reference spectrum is removed by improved CS processing, and accurate focusing is realized through range-matched filter and range-dependent azimuth-matched filter. Simulations are performed to validate the presented algorithm. © The Authors. Published by SPIE under a Creative Commons Attribution 3.0 Unported License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.

A Novel Imaging Algorithm for High-Resolution Wide-Swath Space-Borne SAR Based on a Spatial-Variant Equivalent Squint Range Model

“…In order to correct the range-variant RCM of the target echoes across different range cells, typically, a Chirp Scaling (CS) method [23][24][25] is performed which can eliminate the linear differential RCM through complex multiplications. When the resolution increases, the non-linear differential RCM becomes significant, and the Nonlinear Chirp Scaling (NCS) algorithm [30][31][32] is correspondingly proposed. However, when the resolution further increases, the precision of the NCS similarly cannot meet the requirement, and meanwhile, the NCS will introduce high-order modulations to the range phase, which could cause the degradation of the range profile for the imaging result.…”

Accelerating Spaceborne SAR Imaging Using Multiple CPU/GPU Deep Collaborative Computing

“…One of the important contributions is that the range cell migration correction (RCMC) [ 12 , 13 ] interpolation operation is avoided compared to Range-Doppler (RD) algorithm, thus the amount of computation is reduced about times [ 14 ]. Besides, CS algorithm can significantly improve the performance of the SAR imaging because of the accurate processing in the squint mode [ 2 , 15 , 16 ]. On the other hand, Back-Projection (BP) algorithm is theoretically capable of precise imaging processing for various mode, but is seldom employed in practical applications due to low imaging efficiency.…”