An Efficient Polyphase Filter Based Resampling Method for Unifying the PRFs in SAR Data

TL;DR

The paper introduces POLYPHASE, a polyphase filter-based resampling method that unifies variable PRFs in SAR data, enabling real-time, on-board processing with computational efficiency while maintaining image quality.

Contribution

It presents a novel, efficient polyphase filter-based resampling scheme for SAR data that unifies variable PRFs and allows real-time onboard implementation.

Findings

POLYPHASE achieves comparable image quality to state-of-the-art methods.

The scheme offers significant computational savings for arbitrary PRF variations.

Experimental results validate the effectiveness of the proposed method.

Abstract

Variable and higher pulse repetition frequencies (PRFs) are increasingly being used to meet the stricter requirements and complexities of current airborne and spaceborne synthetic aperture radar (SAR) systems associated with higher resolution and wider area products. POLYPHASE, the proposed resampling scheme, downsamples and unifies variable PRFs within a single look complex (SLC) SAR acquisition and across a repeat pass sequence of acquisitions down to an effective lower PRF. A sparsity condition of the received SAR data ensures that the uniformly resampled data approximates the spectral properties of a decimated densely sampled version of the received SAR data. While experiments conducted with both synthetically generated and real airborne SAR data show that POLYPHASE retains comparable performance to the state-of-the-art BLUI scheme in image quality, a polyphase filter-based implementation of POLYPHASE offers significant computational savings for arbitrary (not necessarily periodic) input PRF variations, thus allowing fully on-board, in-place, and real-time implementation.