A method for synthetic aperture radar (SAR) imaging using maximum a posteriori (MAP) estimation based on multiplicative speckle model is presented. The new method uses the total variation (TV) minimization to regularize the solution. The reconstruction of SAR image is formulated as a biconvex optimization problem, which is solved by the alternate convex search (ACS) method. Experiments on Radarsat-1 raw data show that the proposed method can recover most of the structural and texture details of the imaged scene using only a half of raw data. Compared with regular regularization methods for SAR imaging with incomplete data, the proposed method performs much better on less sparse scenes.

This study focuses on the retrieval and validation of sea-surface wind speeds using data from the interferometric imaging radar altimeter (InIRA) aboard the Chinese Tiangong-2 space laboratory. First, an empirical model, KuLMOD2, is proposed, which is a revised version of the former Ku-band low incidence model (KuLMOD) that directly relates the normalized radar cross section σ0 to both the wind speed and incidence angle. The revised model extends the ranges of the incidence angle and wind speed and is thus applicable to the new InIRA data. The model coefficients are estimated by fitting precipitation radar data from the Tropical Rainfall Measuring Mission and collocated wind data from the European Centre for Medium-Range Weather Forecasts. The wind speeds are then retrieved from the InIRA data using KuLMOD2. For more efficient retrieval, a lookup table method is used to find the wind speed solution. Finally, the InIRA wind speeds are validated using collocated Advanced Scatterometer (ASCAT) wind speeds. The validation of the InIRA wind speed data shows that InIRA can capture regional changes and that the data have a bias of 0.02 m/s and a root-mean-square error of 1.58 m/s. This suggests that the InIRA data alone can provide valid wind speeds for future sea state bias correction of InIRA-derived sea-surface heights and that the InIRA data can act as a complement to data from other spaceborne wind sensors.

In this study, we performed preliminary comparative evaluation and correction of two-dimensional sea surface height (SSH) data from the Chinese Tiangong-2 Interferometric Imaging Radar Altimeter (InIRA) with the goal of advancing its retrieval. Data from the InIRA were compared with one-dimensional SSH data from the traditional altimeters Jason-2, Saral/AltiKa, and Jason-3. Because the sea state bias (SSB) of distributed InIRA data has not yet been considered, consistency was maintained by neglecting the SSB for the traditional altimeters. The results of the comparisons show that the InIRA captures the same SSH trends as those obtained by traditional altimeters. However, there is a significant deviation between InIRA and traditional altimeter SSHs; consequently, systematic and parametric biases were analyzed. The parametric bias was found to be related to the incidence angles and a significant wave height. Upon correcting the two biases, the standard deviation significantly reduced to 8.1 cm. This value is slightly higher than those of traditional altimeters, which typically have a bias of ~7.0 cm. The results indicate that the InIRA is promising in providing a wide swath of SSH measurements. Moreover, we recommend that the InIRA retrieval algorithm should consider the two biases to improve SSH accuracy.

The interferometric imaging radar altimeter (InIRA) aboard the Chinese Tiangong-2 space laboratory is the first spaceborne imaging radar working at low incidence angles. This study focuses on the retrieval of significant wave heights (SWHs) from InIRA data. The retrieved SWHs can be used for correcting the sea state bias of InIRA-derived sea surface heights and can supplement SWH products from other spaceborne sensors. First, we analyzed tilt, range bunching and velocity bunching wave modulations at low incidence angles, and we found clear dependencies between the SWH and two defined factors, range and azimuth integration, for ocean waves in the range and azimuth directions, respectively. These dependencies were further confirmed using InIRA measurements and collocated WaveWatch III (WW3) data. Then, an empirical orthogonal SWH model using the range and azimuth integration factors as model inputs was proposed. The model was segmented by the incidence angle, and the model coefficients were estimated by fitting the collocation at each incidence angle bin. Finally, the SWHs were retrieved from InIRA data using the proposed model. The retrievals were validated using both WW3 and altimeter (JASON2, JASON3, SARAL, and HY2A) SWHs. The validation with WW3 data shows a root mean square error (RMSE) of 0.43 m, while the average RMSE with all traditional altimeter data is 0.48 m. This indicates that the InIRA can be used to measure SWHs.

This letter proposes a novel dechirp processing method for wideband nonlinear frequency modulation (NLFM) waveform which enables low sampling rate of data. As we know, NLFM waveform can easily realize optimal shape of power spectral density which helps to achieve better pulse compression result with low range sidelobes without signal-to-noise ratio degradation caused by weighting as we usually do for LFM waveforms. In the approach, hamming window is adopted in the generation of the NLFM waveform for better balance on the low range sidelobes and a relative small bandwidth. In dechirp operation, the NLFM radar echoes are mixed with a local reference LFM signal, and thus narrowband signals are resulted and only low sampling rate is needed. The dechirped NLFM signals are then up-sampled and inverse dechirped by software and finally matched filtering is conducted to complete pulse compression. Both numerically simulated data and real radar data are processed to verify the effectiveness of the proposed method.

This paper presents for the first time the results of marine gravity recovery using the ocean observation data acquired by Tiangong-2 interferometric imaging radar altimeter (TG2 InIRA) which demonstrate not only the balanced accuracies of the north and east components of deflection of the vertical (DOV) as envisaged, but also the improved spatial resolutions of DOV compared with that by conventional altimeters (CAs). Moreover, much higher measurement efficiency owing to the wide-swath capability and the great potential in accuracy improvement of marine gravity field are also demonstrated. TG2 InIRA adopts the interferometry with short baseline and takes small incidence angles, by which wide-swath sea surface height (SSH) can be measured with high accuracy. Gravity recovery experiments in the Western Pacific area are conducted to demonstrate the performance, advantages and capability of TG2 InIRA. SSH data processing algorithms and DOV calculation have been designed by taking the wide-swath feature into account, based on which, the gravity anomalies are then calculated using the inverse Vening Meinesz formula. The derived gravity anomalies are compared with both the published gravity models and the shipborne gravity measurements. The results show that the accuracy of TG2 InIRA is equivalent to, or even a little better than, that of CAs. The fused gravity result using equal TG2 InIRA data and CAs data performs better than those using TG2 InIRA data alone or CAs data alone. Due to the signal bandwidth of TG2 InIRA is only 40 MHz which is much smaller than that of CAs, much higher accuracy can be hopefully achieved for future missions if larger signal bandwidth is used.