Ocean waves can either be the target of interferometric radar altimeter (IRA) observations or may affect observations of mesoscale and submesoscale ocean dynamic phenomena. Due to the low incidence angle of the IRA, in addition to the azimuth shift caused by the motion of the ocean waves, the range shift caused by the height of the ocean wave is also significant. In this article, based on previous research, we propose a new nonlinear integral transform relating ocean wave spectra to phase image spectra of an IRA at a low incidence angle that includes the effect of range shift. This new nonlinear integral transformation can be replaced by a quasilinear transformation when the nonlinear variation is weak or the wavelength of the ocean wave is large. We analyze the effect of swell and wind waves on the phase spectra under different conditions based on the new nonlinear integral transform through simulation. The height of the ocean wave and the incidence angle of the radar affect the range shift, leading to a range nonlinear effect in the phase spectra. The orbital velocity of the ocean wave affects the azimuth shift, leading to an azimuth nonlinear effect in the phase spectra. The wavelength and propagation direction of the ocean wave also induces a distortion in the phase spectra. Overall, the nonlinear effect has a small effect on the swell and a large effect on the wind wave.

Systematic attitude errors (the roll, pitch, and yaw errors) are important sources of altimetric error in interferometric radar altimeters (IRA). So far, the effect of systematic attitude errors on the measurement of IRA has been investigated based on the interferometric geometry, in which the impact of the attitude errors on the IRA image quality and the coupling between each attitude error are not considered. In this work, the influence of attitude errors on the measurement accuracy of IRA is reanalyzed according to the IRA imaging principle and the interferometry theory. The theoretical formulas derived in this paper demonstrate that the roll is the most important factor affecting the measurement accuracy of IRA. Although the altimetric error directly introduced by yaw and pitch is smaller, the yaw and pitch would cause the altimetric error to be offset along the azimuth direction, and the offset grows approximately linearly across the range direction in the IRA images. Meanwhile, the attitude jitter would also introduce additional high-frequency altimetric errors, although these high-frequency altimetric errors can be removed through a Gaussian low-pass filter with the cut-off frequency determined by wavelet analysis. To verify the validity of the theoretical formulas and exhibit the impact of diverse attitude errors, a full-link simulation method is proposed, which encompasses the entire process from IRA observation to imaging and interference processing. Furthermore, the theoretical results are compared with the results of the full-link simulation and the experimental data acquired by an airborne IRA.

The azimuth cutoff of interferometric radar altimeter (IRA) image, which is acquired at small incidence angles, is mainly determined by the vertical component of the orbital velocity of ocean waves and is almost independent of the wave direction. Using this property, an inversion method for wind waves and wind speed has been proposed based on the azimuth cutoff of IRA image in combination with the Elfouhaily wind wave spectrum, which can effectively solve the problem of small-scale wind wave parameters loss caused by velocity bunching. In the present work, the wind speed and the significant height of wind waves (SH$_{\mathrm {ww}}$) have been retrieved from five pairs of airborne IRA images acquired in offshore areas. The results show that the differences between SHww retrieved from the five pairs of IRA images used in this article by the new method and the reference SHww are acceptable in ocean wave inversion. However, if the wind fetch is small and the wind direction is inconsistent with wave propagation direction, there is a significant difference between the retrieved wind speed and the reference wind speed when using the new method to retrieve wind speed. Moreover, the results also show that for the sea area with infinite wind fetch, the inversion accuracy of wind speed and SHww determined by the accuracy of the retrieved radar radial significant orbital velocity of wind waves (SV$_{\mathrm {ww}}$). However, for the sea area with finite wind fetch, the inversion accuracy would also be affected by wind fetch.

The swath of the conventional spaceborne synthetic aperture radar (SAR) is parallel-to-orbit, making it inefficient to observe long curved terrain, like coastlines, railways, etc.. Imaging long curved terrains with the terrain matching (TM) curved swath is a promising technique for efficient data acquisition. The key feature is the employment of a long curved swath matching with the orientations of the long curved terrains. This paper reports the first demonstration of the spaceborne SAR TM curved imaging with the LJ2-01 satellite. A TM curved swath of 161.7 km is imaged with an azimuth resolution of 0.6 m. The main technical contributions are: First, a new electrical-mechanical-combined beam control method is proposed to achieve uniform azimuth resolution; Second, a new non-uniform pulse repetition frequency sequence is used to mitigate the data loss caused by the violent spatial variation of the slant range; Third, a new swath-adaptive sub-aperture time-domain imaging algorithm is proposed for efficient TM curved swath imaging. These innovations contribute to successful data acquisition and imaging of the spaceborne SAR TM curved imaging with the LJ2-01 satellite.

Wide swath near-nadir interferometric altimetry is a newly developed technology for sea surface height (SSH) measurement. However, the absence of actual measurement data makes this novel SSH mapping technique difficult to verify and apply for wide swath interferometric altimeters. To verify the designed performance of the scheduled wide swath single-pass interferometric altimeter in the "Guanlan Mission", an airborne campaign was carried out off the coast of Rizhao, China on November 16, 2020. An airborne dual-frequency interferometric radar altimeter system (ADIRAS) with a single-pass mode was utilized for SSH measurement as the first flight. Two pioneering and fundamental works have been conducted: an intensive altimetry error analysis according to the ADIRAS parameter settings along the incident direction, an effective SSH reconstruction approach based on a multichannel likelihood (ML) function, and detailed validation procedures through airborne campaigns illustrated in this study. The results indicated that the difference between the wave-induced sea surface elevation (WSSE) variances derived by the ML approach and GNSS buoy was 2 cm2, which was smaller than the results of the single band on Ku (11 cm2) and Ka (6 cm2). Moreover, the estimated Significant Waves Height (SWH) bias of joint bands was 10 cm, which was also superior to that of Ku (39 cm) and Ka (24 cm). Both simulated data and real airborne dual-frequency InSAR data were employed in this study for cross-validation of the proposed method. This approach represents an effective technique for SSH reconstruction of future spaceborne/airborne interferometric altimeters.

This letter describes the new ability to measure wind-generated gravity waves using the airborne$Ka$-band interferometric altimeter (AirKaIA). Although the original definition of wave parameters is derived from wave-induced sea surface elevation (WSSE), it is difficult to directly measure the WSSE, so most remote sensing of waves use other types of signals to obtain wave parameters. Here, we present the measurement of 2-D WSSE from AirKaIA. A new wave retrieval method based on the 2-D WSSE has been developed, tested with simulation data, and applied to AirKaIA data. The results indicate that the retrieved dominant wave directions, dominant wavelengths, and significant wave heights from AirKaIA are in agreement within situmeasurements while highlighting the need for further method tests using more observations. The study of ocean signals from interferometric altimeter is an emerging research topic. AirKaIA’s measurements of wind-generated gravity waves with 2-D WSSE have implications for the assessment of future interferometric altimeter missions.

Interferometric radar altimeter (IRA) is a new ocean remote sensing sensor. It can be used to retrieve sea surface height (SSH) by means of cross-track interferometry. Compared with the traditional cross-track interferometric synthetic aperture radar (XT-InSAR), IRA works at very small incidence angles for higher altimetry sensitivity. In this case, multiple discontinuous surface scatterers at sea surface would be cut into a same range pixel which leads to severe layover. This layover induced by ocean waves will reduce the correlation between the master-slave images acquired by IRA and increase random interferometric phase noise. At present, how to quantitatively analyze the impact of the ocean wave layover on the decorrelation of IRA images is still a problem that needs in-depth discussion. In this letter, theoretical analysis of the effect of ocean waves on the decorrelation of IRA images has been carried out when the ocean waves layover is considered. And the theoretical results are also compared with the airborne IRA data. It is found that the layover of ocean waves has significant influence on the decorrelation between the master-slave IRA images, especially at very low incidence angles.

Deconvolution technique can be utilized in the forward-looking radar (FLR). However, the forward-looking imaging performance degenerates greatly due to the effect of high-speed movement of the platform. In this article, an efficient Bayesian forward-looking superresolution imaging algorithm based on Doppler deconvolution in expanded beam space is proposed. First, the Doppler phase information caused by the high-speed platform is fully exploited and the Doppler matrix is integrated with the antenna pattern. The Doppler convolution model of the echo signal for forward-looking is derived in this article. Then, the Doppler phase information is adopted to perform the Doppler deconvolution. Moreover, an expanded beam space is constructed to enhance the sparsity of the imaging scene. The complex Gaussian distribution and the Laplace distribution have been used to model the distribution characteristics of noise and targets in the imaging scene, respectively. Finally, based on the Bayesian framework, the forward-looking imaging problem is converted into the convex optimization problem. The performance assessment based on simulated and experimental data, also in comparison to the conventional real beam, truncated singular value decomposition (TSVD), iterative adaptive approach (IAA) methods, has demonstrated the effectiveness of our proposed algorithm under high-speed platform scenarios.

The interferometric radar altimeter (IRA) is one of the main payloads of the “Guanlan” ocean science satellite proposed by the National Laboratory for Marine Science and Technology of China. To evaluate the effectiveness and accuracy of the IRA in retrieving the ocean dynamic parameters, such as sea surface height (SSH), ocean wave spectrum, and wind speed, two airborne IRA experiments were carried out at Qingdao Xiaomaidao (XMD) sea area on March 31, 2019, and Rizhao sea area on November 16, 2020. In the present work, wave-induced sea surface elevation (SSE) and its spectrum have been retrieved based on the interferograms acquired by the airborne IRA. To suppress the random phase noise, a mean filtering algorithm has been used in the multilook process of calculating the complex IRA images. The results show that the size of the filter window has a significant effect on the retrieved SSE. If the size of the filter window along THE range direction is too large, the flat earth would cause the spectral density of the retrieved ocean wave to be higher. In addition, the comparisons of the retrieved spectra with the buoy measurements demonstrate that the swell can be well-retrieved by IRA images at low sea-state conditions with significant wave height (SWH) less than 0.7 m. However, for wind wave, because of the effect of the velocity bunching along the azimuth direction, the wind wave spectrum can be extracted only when it propagates approximately along the ground-range direction of the IRA images.

Synthetic aperture radar (SAR) simulation of 3-D forest canopies is a powerful tool for studying the interaction between radar and forest, for testing new applications, and for devising inversion algorithms of forest structures. SAR raw-signal generation is frequently used in point-target simulation but is rarely used in 3-D forest simulation. The existing simulators directly produce SAR images based on an impulse response function (IRF) without involving raw-signal generation and various nonideal factors. In this paper, a novel simulator to produce SAR images of 3-D forest canopies is proposed. It incorporates a SAR raw-signal generation process taking account of various nonideal factors such as trajectory deviation of radar platforms and complexity of natural environments, which is more faithful to realistic remote sensing systems. Furthermore, an approach to speed up the raw-signal generation is put forward based on the equivalent scattering model consisting of a few virtual scatterers with specially calculated positions and backscattering matrices. Thus, the raw signals received from the entire forest canopy can be equivalent to those from virtual scatterers in the case of tiny slant-range errors. The error sensitivity of equivalent conditions is analyzed, and the optimum selection of equivalent parameters is derived considering the compromise between precision and efficiency. The results of simulation and forest height inversion demonstrate the feasibility and potential utilities of the proposed simulator.

Synthetic Aperture Radar (SAR) has been proved as an effective instrument for detecting vertical structures of forest canopies. However, the quality of SAR images could decline because of phase errors caused by the residual motion deviations after motion compensation or autofocus process. Then, the accuracy of forest height inversion will be affected. In this paper, the relationship between residual phase errors and the accuracy of the retrieved height is established via three-dimensional forest canopies simulation of SAR. The residual motion deviations with different amplitudes and frequencies are considered in simulation experiments. Reasonable levels of estimated phase errors to reach high accuracy of retrieved height are achieved. It is demonstrated that higher accuracy of estimated phase errors is demanded for forest height inversion based on SAR data.

Interference fringes will be generated in SAR image when distributed targets' echo signal is simulated because of the uniform model of targets. The fringes can be suppressed by adding random height in space or random phase on backscatter coefficient of the distributed targets. However, the former method will introduce location error and the latter method will increase speckle noise twice in simulated image. In this paper, we develop a high accuracy method for fringes suppression based on targets' position randomizing and RCS re-sampling via bilinear interpolation. The validation of method is successfully proved by simulation results and the performance of the method is discussed on accuracy and computational complexity at the end of this paper.