## 5 Discussion  
In addition to the wide-swath SSH measurement, the InIRA has the potential for wave measurement because it can provide NRCSs with high spatial resolutions similar to the conventional SAR. The measured waves are useful in correcting the sea state bias of InIRA-derived SSHs and supplementing wave products from other spaceborne sensors. Currently, only a few studies involved the wave or SWH retrieval from InIRA data; thus, this study focuses on this aspect. From previous studies on SARs [8; 9; 10; 11; 12; 13; 14; 15], there are generally two SWH retrieval approaches, namely the theoretical transfer relation and empirical model. In terms of SWH retrieval accuracy, the latter is better than the former, possibly because the latter handles the nonlinear and cutoff effects more effectively. Therefore, this paper proposed an empirical model to retrieve SWH data. Using the model, SWHs were retrieved from InIRA data and validated using both WW3 and traditional altimeter data. Through the validation, the InIRA SWH retrievals were found to have agreement with the collocated data, suggesting the potential of InIRA data for SWH retrieval. In the comparisons between the InIRA SWH retrievals with traditional altimeter data, the average RMSEs of the InIRA SWH retrievals are within 0.5 m, which are comparable to SAR values using the empirical model approach. For instance, using the ERS2 SAR data, [PERSON] et al. [12] proposed an empirical model (CWAVE2.0) to estimate the SWH, which results in an RMSE of approximately 0.5 m compared to WAM model data. Following this approach, [PERSON] et al. [13] use the CWAVE_ENV model to obtain an RMSE of approximately 0.5 m for ENVISAT SAR data compared to traditional altimeter data. [PERSON] and [PERSON] [14] used the CWAVE_SIA model and obtain RMSEs within 0.5 m for Sentinel-1A SAR data compared to traditional altimeter and buoy data. These comparisons suggest that both the InIRA and SAR can provide acceptable SWH retrieval accuracies using the empirical model, although they follow different backscattering mechanisms (quasi-specular and Bragg). This study found the dependences between the SWH and two factors, range and azimuth integration, which were further confirmed from the InIRA data. On this basis, an orthogonal empirical model using the two integration factors as inputs was proposed. This model adopted a concept of orthogonal decomposition, which has not been widely applied in empirical models [12; 13; 14; 15]. In our attempt, the model obtained an acceptable  
Figure 8: Comparisons of SWH between InIRA retrievals and collocated (**a**) JASON2; (**b**) JASON3; (**c**) SARAL; and (**d**) HY2A data. retrieval accuracy, which indicates that SWH can be modeled by combining the two orthogonal integration factors calculated from image spectra. This concept concerning the orthogonal integration factors may be used for supplementing existing SAR and OWS SWH retrieval methods. The InIRA NRCS image in this study exhibits clear wave-like stripes and complete image spectra, which indicates that the cutoff effect on the InIRA is significantly weaker than that on the conventional SAR. This is because the InIRA has a lower satellite altitude, which can be well explained by the known SAR ocean wave imaging theory. The small cutoff of the InIRA data confirmed this theory again. Nevertheless, owing to the limited coverage, the low-altitude SAR has not been widely used for ocean remote sensing observations. Currently, with the improvement in satellite technology and reduction in launch cost, a low-altitude satellite constellation that can effectively extend the data coverage through a combination of multiple satellites has become possible. In this case, the low-altitude constellation can simultaneously satisfy the requirements of weak cutoff effects and wide coverage, which may provide a new manner for measuring ocean wave fields. Despite the above findings, this study has three limitations. First, the hydrodynamic modulation was not considered owing to its complexity and weakness.