This paper proposes a generalized compact polarimetric (GCP) mode along with two optimal polarization mode selection parameters to address the challenges of polarization mode selection in classification tasks across diverse scenarios. Theoretically, we conduct an in-depth analysis of the differences between circular and linear transmit polarizations, demonstrating their fundamental equivalence in terms of information content. For the first time, we propose that different classification tasks require different optimal polarization modes, and the optimal transmit polarization mode may lie in the elliptic polarization domain of SAR systems rather than traditional circular compact polarimetric (CP) or linear dual-polarimetric (DP) modes. The proposed approach is validated using full-polarimetric SAR data from San Francisco and Hainan, showing that the optimal elliptical polarization mode achieves classification accuracies that are 2% to 42% higher than those of traditional CP or DP modes for certain categories, and performs comparably to full polarization. This improvement in accuracy stems from the interaction between the transmit polarization and the target scene, rather than advancements in classification algorithms. Using the two proposed parameters, the overall and category-specific classification performance of GCP modes can be effectively evaluated, enabling the identification of the optimal polarization mode for a given task. These findings provide significant insights for the design of future polarimetric SAR systems and offer new perspectives and directions for mission planning and mode selection for on-orbit satellites.

The debate surrounding the optimal polarimetric modes—compact polarimetry (CP) versus dual polarization (DP)—for PolSAR ship detection persists. This study pioneers a systematic investigation into Generalized Compact Polarimetry (GCP) for this application. By synthesizing and evaluating 143 distinct GCP configurations from fully polarimetric data, this study presents the first comprehensive comparison of their ship detection performance against conventional modes using Target-to-Clutter Ratio (TCR) and deep learning-based accuracy (AP50). Experiments on the FPSD dataset reveal that an optimized GCP mode (e.g., ellipse/orientation: [−10, −5]) consistently outperforms traditional CP and DP modes, yielding TCR gains of 0.2–2.7 dB. This translates to AP50 improvements of 0.5–4.7% (Faster R-CNN) and 0.1–5.5% (RetinaNet) over five common baseline modes. Crucially, this enhancement arises from optimizing the interaction between the polarization mode and target/clutter scattering characteristics rather than algorithmic improvements, supporting the proposed “optimization from the information source” strategy. These findings offer significant implications for future PolSAR system design and operational mode selection.

Calibration by distributed targets is an important part of polarimetric calibration (PolCAL) without corner reflectors (CRs). Currently, both the correlation of HH and VV ( $R_{\rm{hhvv}}$ ) and the equivalent number of looks (ENL) constitute the common method for the extraction of Bragg-like points (BLPs) in order to calibrate the co-polarization channel imbalance $k$ . However, strict assumptions about distributed targets and complex mathematical expressions regarding ENL limit the impact analysis of $k$ on $R_{\rm{hhvv}}$ and ENL; thus, the fixed thresholds for $R_{\mathrm{hhvv}}$ and ENL can be obtained only by comparing the calibration errors with the CRs or simulated values in order to calibrate $k$ accurately. In some Earth observation and lunar exploration without CRs, the above conditions are not satisfied. In this article, a BLP extraction method is proposed for calibrating co-polarization channel imbalance $k$ in PolCAL. ${H}/{\bar{\alpha }}$ decomposition is utilised to deduce the specific scattering impacts of BLPs by different $k$ values first. Then, a dynamic selection method is proposed to reduce the influence of fixed thresholds and improve the extraction accuracy. Multi-scene polarimetric synthetic aperture radar (PolSAR) images from AIRSAR, ALOS, and GF-3 are utilised to verify the effectiveness of the proposed algorithm in the extraction of BLPs and the calibration results of $k$ obtained by applying the extracted BLPs (ext. BLPs).