*Result*: Quantitative Assessment of the Computing Performance for the Parallel Implementation of a Time-Domain Airborne SAR Raw Data Focusing Procedure.

*Highlights: What are the main findings? Two implementation strategies for Time-Domain (TD) airborne Synthetic Aperture Radar (SAR) focusing are presented and quantitatively compared using real airborne SAR data. The pixel-wise strategy consistently outperforms the matrix-wise strategy by 19–36% in computing time, with the performance gap widening for larger output grids, while both methods produce identical focused images. For both proposed implementation strategies, TD focusing can be substantially accelerated through the proper application of parallel processing techniques. Depending on available hardware capabilities, significant speedup factors can be achieved. For instance, with the considered Information Technology (IT) platform, up to 177× have been achieved. Specifically, if we consider a SAR raw data size of 4000 × 200,000 samples, covering an area of approximately 3 km in slant range and 8 km in azimuth, and apply the pixel-wise approach to implement the TD focusing, by setting an azimuth resolution of 30 cm, over an output grid of 4000 × 32,000 pixels, with a single-job of the IT platform available at IREA-CNR we need 1560 min of computing time. Exploiting 256 jobs on the same platform, we reduce this computing time to just 8 min. What are the implications of the main findings? Time-Domain SAR focusing becomes operationally viable for near-real-time airborne monitoring and emergency response applications, with processing times reduced to minutes for large-scale datasets when appropriate parallelization strategies are applied. The identified scaling behavior and efficiency limits allow for predicting processing times and optimization of resource allocation in operational SAR scenarios. Since computing efficiency deteriorates beyond specific parallelization thresholds, the presented results allow establishing practical criteria for balancing performance improvements against costs/inefficiencies related to parallelization. In this work, different implementation strategies for a Time-Domain (TD) focusing procedure applied to airborne Synthetic Aperture Radar (SAR) raw data are presented, with the key objective of quantitatively assessing their computing time. In particular, two methodological approaches are proposed: a pixel-wise strategy, which processes each image pixel independently, and a matrix-wise strategy, which handles data blocks collectively. Both strategies are further extended to parallel execution frameworks to exploit multi-threading and multi-node capabilities. The presented analysis is conducted within the context of the airborne SAR infrastructure developed at the Institute for Electromagnetic Sensing of the Environment (IREA) of the National Research Council (CNR) in Naples, Italy. This infrastructure integrates an airborne SAR sensor and a high-performance Information Technology (IT) platform well-tailored to the parallel processing of huge amounts of data. Experimental results indicate an advantage of the pixel-wise strategy over the matrix-wise counterpart in terms of computing time. Furthermore, the adoption of parallel processing techniques yields substantial speedups, highlighting its relevance for time-critical SAR applications. These findings are particularly relevant in operational scenarios that demand a rapid data turnaround, such as near-real-time airborne monitoring in emergency response contexts. [ABSTRACT FROM AUTHOR]*