A Channel-Adaptive Range-Doppler Domain Filtering Serial BAQ Algorithm and Comparative Analysis

With the growing demand for large-scale urban observation, multi-channel technology has become a cornerstone of high-resolution wide-swath SAR systems. The challenge of storing and transmitting the large data volumes generated by multi-channel systems has driven the development of advanced data compression techniques. However, in onboard implementations with non-power-of-two channel numbers and serial data formats, the existing multi-channel compression algorithms reveal significant conflicts involving channel counts, FFT cores, and the Krieger method. To address these issues, this paper introduces the Channel-Adaptive Range-Doppler domain filtering Serial Block Adaptive Quantization algorithm (CARDS-BAQ). By incorporating a point-frequency RD domain filtering approach and leveraging serial data matrix splicing and rollback combined with point-frequency ABAQ, CARDS-BAQ enables efficient data compression for arbitrary channel counts. The performance of CARDS-BAQ is validated using GF-3 measured data through comparative analysis with BAQ, ABAQ, MCBAQ, and 3MBAQ algorithms under power-of-two channel conditions. Additionally, its applicability and reliability for non-power-of-two channel numbers are demonstrated through payload flight experiments conducted in 2024 in Yingkou, Liaoning Province, China. CARDS-BAQ effectively supports data storage and transmission for large-scale urban observation, marking a significant advancement in remote sensing technology.