Interferometric Imaging Radar Altimeter Research Articles

Interferometric Calibration Based on a Constrained Evolutionary Algorithm without Ground Control Points for a Tiangong-2 Interferometric Imaging Radar Altimeter

The interferometric imaging radar altimeter (InIRA), mounted on the Tiangong-2 space laboratory, utilizes a small incidence and a short interferometric baseline to achieve altimetry for wide swathes of ocean surface topography and inland water surface elevation. To obtain a high-precision digital elevation model (DEM), calibration of the interferometric system parameters is necessary. Because InIRA utilizes the small-incidence interference system design, serious coupling occurs between the interferometric parameters. Commonly used interferometric calibration methods tend to fall into the local optimal solution for InIRA. Because evolutionary algorithms have a stronger robustness and global search ability, they are better suited to handling the solution space structure under the coupling of complex interferometric parameters. This article establishes an interferometric calibration optimization model for InIRA by utilizing the relative flatness of the lake surface as an inequality constraint. Furthermore, an adaptive penalty coefficient constraint evolutionary algorithm is designed to solve the model. The proposed method was tested on actual InIRA data, and the results indicate that it efficiently adjusts interferometric parameters, enhancing the precision of measurements for Qinghai Lake elevation.

Preliminary Results of Marine Gravity Recovery by Tiangong-2 Interferometric Imaging Radar Altimeter

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.

Assessing the performance of the Tiangong-2 wide-swath imaging altimeter observations for water level monitoring over complex and shallow lakes

• Performance of the new generation wide-swath imaging altimeter (TG-2 InIRA) for water level monitoring is evaluated for the first time. • TG-2 InIRA is capable of capturing water surface elevations over shallow and small water bodies with a mean absolute bias of 24 cm. • TG-2 InIRA can also efficiently measure river water level with absolute differences below 43 cm, and river gradient mapping is consistent with the practical situation. • The study contributes to bridge the gap between in-situ measurements and the products of forthcoming SWOT mission. As a significant hydrological parameter, the water level of complex and shallow river-lake wetland has important implications for a number of hydrological, biological, physical and chemical processes. Current in-situ and satellite-based methods both have disadvantages in capturing water levels over smaller surface water bodies with spatial heterogeneity or complexity. Interferometric imaging radar altimeter (InIRA) is a latest generation of Ku-band radar altimeter onboard Tiangong-2 (TG-2), the Chinese space laboratory, launched in 2016. Similar to the design idea of NASA’s SWOT, it is expected to improve this situation through wide-swath altimetry. However, the capacity of the TG-2 InIRA to measure water levels within small surface water bodies remains unexamined. To explore these performances, particularly their potential impact on hydrology research, an assessment and comparison between in-situ and TG-2 derived measurements was performed over the largest river-lake wetland in China. The results showed that the TG-2 InIRA, with a broad range of coverage, was able to effectively capture most of the surface water at its elevation. For the focused shallow depressions, a relatively good correlation was observed between the in-situ and InIRA-derived water surface elevations (WSEs), with an R 2 of 0.97, RMSE of 0.29 m, and absolute difference ranging from 3 to 55 cm. The accuracy of InIRA-derived WSEs was highly controlled by the depression sizes, and the absolute biases broadly increased in a power law fashion as the size of the depression decreased. In addition, surface water profiles along the Ganjiang and Xiushui River channels indicated that the TG-2 InIRA could also measure river WSEs, with absolute differences below 0.43 m. Although differences were observed, the results of the river gradient distribution were consistent with the practical situation and showed overall slopes of 18.72 cm/km and 12.43 cm/km for the Xiushui and Ganjiang Rivers, respectively. Such results demonstrated that TG-2 InIRA measurements can satisfactorily capture spatial patterns of the surface water gradient, which is useful for accurately estimating river discharge. This study will not only bridge the gap between in-situ measurements and forthcoming SWOT products but also contribute to water resource management and hydrologic service assessments over data-sparse regions of river-lake systems within the study area.

Ocean Wave Inversion Based on a Ku/Ka Dual-Band Airborne Interferometric Imaging Radar Altimeter

Ocean wave parameters (OWPs), including wave propagation direction (WPD), significant wave height (SWH), and main wave wavelength (MWW) can be typically retrieved using an interferometric imaging radar altimeter (InIRA). However, the inversion accuracy of ocean waves in Ku (15.8 GHz) and Ka (35.8 GHz) bands has not yet been evaluated due to the lack of field observation data. In this paper, to assess the inversion accuracy of OWPs in Ku and Ka bands, an airborne observation experiment using simultaneous Ku and Ka bands was carried out for the first time in Rizhao, Shandong Province, China. A dual-band InIRA (DInIRA) was configured with small incidence angles (4°–18°) and a Global Navigation Satellite System (GNSS) buoy; a mobile weather station was placed at the intersection of the plane routes for validation. Afterward, the WPD, SWH, and MWW were retrieved based on the imaging of sea surface height. As compared with the field in situ data, the WPD inversion results of main wind wave were found to be consistent with the measurement environmental wind direction. The SWH inversion biases, retrieved by the Ku and Ka bands, were 0.38 m and 0.27 m; the MWW inversion biases for the swells were equal to 16.75 m and 3.67 m; and the MWW inversion biases about the wind waves were 2.32 m and 0.57 m. Ultimately, it was established that the OWPs could be effectively retrieved by the DInIRA, and the inversion accuracy of the SWH and the MWW in the Ka band outperformed that in the Ku band.

Interference image registration combined by enhanced scale-invariant feature transform characteristics and correlation coefficient

To realize the digital elevation inversion of the interferometric imaging radar altimeter (InIRA), an interference complex images registration algorithm combining enhanced scale-invariant feature transform (SIFT) characteristics with correlation coefficient is proposed. First, the locally tuned nonlinear method is used to enhance the image features. Then, SIFT algorithm is used to extract the matched feature points that are used as control points after screening. Based on these control points, the affine transformation is applied to calculate the coarse matching relation. Second, multiple control points are chosen uniformly. The local accurate offsets are determined by interpolating and calculating the maximum of correlation coefficients. The least-squares method is used to fit the difference between the two images. Third, the two images are matched by interpolating and resampling the one to be registered. Finally, the simulated InIRA sea surface images and the Sentinel-1A images of the Mount Hua area are employed to experiment. The results show that the proposed algorithm combines the advantages of SIFT algorithm and correlation coefficient algorithm. It is robust and its registration accuracy is better than the particle swarm optimization sample consensus algorithm, unsupervised deep-learning algorithm, SIFT algorithm, and correlation coefficient algorithm.

Approaches for Joint Retrieval of Wind Speed and Significant Wave Height and Further Improvement for Tiangong-2 Interferometric Imaging Radar Altimeter

The interferometric imaging radar altimeter (InIRA) adopts a short baseline along with small incidence angles to acquire interferometric signals from the sea surface with high accuracy, thus the wide-swath sea surface height (SSH) and backscattering coefficient (σ0) can be obtained simultaneously. This work presents an approach to jointly retrieve the wind speed and significant wave height (SWH) for the Chinese Tiangong-2 interferometric imaging radar altimeter (TG2-InIRA). This approach utilizes a multilayer perceptron (MLP) joint retrieval model based on σ0 and SSH data. By comparing with the European Center for Medium-Range Weather Forecasts (ECMWF) reanalysis data, the root mean square errors (RMSEs) of the retrieved wind speed and the SWH are 1.27 m/s and 0.36 m, respectively. Based on the retrieved SWH, two enhanced wind speed retrieval models are developed for high sea states and low sea states, respectively. The results show that the RMSE of the retrieved wind speed is 1.12 m/s when the SWHs < 4 m; the RMSE is 0.73 m/s when the SWHs ≥ 4 m. Similarly, two enhanced SWH retrieval models for relatively larger and relatively smaller wind speed regions are developed based on the retrieved wind speed with corresponding RMSEs of 0.19 m and 0.16 m, respectively. The comparison between the retrieved results and the buoy data shows that they are highly consistent. The results show that the additional information of SWH can be used to improve the accuracy of wind speed retrieval at small incidence angles, and also the additional information of wind speed can be used to improve the SWH retrieval. The stronger the correlation between wind speed and SWH, the greater the improvement of the retrieved results. The proposed method can achieve joint retrieval of wind speed and SWH accurately, which complements the existing wind speed and SWH retrieval methods for InIRA.

An improved synthetic aperture radar‐scale invariant feature transform algorithm for interferometric imaging radar altimeter image registration

Interferometric imaging radar altimeter (InIRA) integrating synthetic aperture radar (SAR) and synthetic aperture radar interferometry (InSAR) is a new type of radar altimeter. InIRA will be widely adopted in marine scientific research and surface water topography measurements. Owing to the geometric distortion of InIRA images, there are difficulties in feature point extraction and matching, making InIRA registration challenging. Here, an improved SAR-scale invariant feature transform (SIFT, SAR-SIFT) algorithm is proposed to address these difficulties. First, a modified Harris non-linear scale space is constructed using the Harris function and non-linear scale space, and extracted the feature points according to the SAR-SIFT algorithm. Second, the orbital parameters of InIRA are used to calculate the geographic coordinates of each feature point by Hermit interpolation. Subsequently, a geographic-coordinate-based method is proposed to match the feature points. The results show that the proposed algorithm gained more correct matches and improved the registration accuracy by 13% and 16.7% compared with the SIFT and SAR-SIFT algorithms, respectively, and was 18% more time efficient than the SAR-SIFT algorithm. The experiments demonstrate that the proposed algorithm outperforms the SAR-SIFT algorithm for InIRA image registration in terms of accuracy and efficiency.

Cross-Track Error Correction and Evaluation of the Tiangong-2 Interferometric Imaging Radar Altimeter

The Interferometric Imaging Radar Altimeter (InIRA) carried on the Tiangong-2 Space Laboratory can observe three-dimensional sea surface topography over a swath tens of kilometers wide. The InIRA represents a test mission that will provide valuable experience for the design and data processing technology of future wide-swath altimeters. In addition to the tropospheric delay, ionospheric delay, and sea state bias that affect traditional altimeters, InIRA was also affected by the cross-track error derived from roll error, baseline length error, and interference phase error, which had to be properly corrected. In this paper, range error correction based on correction models and cross-track error correction based on the reference topography data method were applied to a 15-day InIRA dataset and evaluated using the Jason-2, Jason-3, Saral/AltiKa, and Sentinel-3A. The results showed that the standard deviation between corrected InIRA and the combined dataset was 7.96 cm after eliminating the influence of tides and dynamic atmospheric correction, which was comparable to nadir altimeter measurement accuracy.

New Ku-Band Geophysical Model Function and Wind Speed Retrieval Algorithm Developed for Tiangong-2 Interferometric Imaging Radar Altimeter

A Ku-band geophysical model function for wind speed retrieval named as KuLMOD-H is proposed based on the quasi-specular reflection model for the Chinese Tiangong-2 Interferometric Imaging Radar Altimeter (TG2-InIRA), which can be used to retrieve the wind speed with 2 km resolution. The model is derived by expanding the effective nadir reflection coefficient term and the mean square slope term in the quasi-specular reflection model using quadratic polynomials with wind speed as variable. The model coefficients are obtained by fitting the radar backscattering coefficient data from TG2-InIRA to the collocated sea surface wind speed data from European Center for Medium-Range Weather Forecasts (ECMWF). For solving the problem of potential ambiguous solutions when the incidence angles are relatively large, a regularization approach is further proposed. The retrieved wind speed results have a root-mean-square error (RMSE) of 1.42 m/s compared with the collocated ECMWF wind speed data and at the same time, they are highly consistent with the buoy data. Different from the previous works on TG2-InIRA wind speed retrieval, this article derives a semiphysical model suitable for incidence angles from 1 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$^\circ$</tex-math></inline-formula> to 8 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$^\circ$</tex-math></inline-formula> , by which better retrieval results are achieved. This work not only explores the wind speed retrieval capability of the instrument under low incidence-angle observation, but also provides high-resolution wind speed data for further correction of sea state bias for TG2-InIRA sea surface height measurements.

Research on Internal Solitary Wave Detection and Analysis Based on Interferometric Imaging Radar Altimeter Onboard the Tiangong-2 Space Laboratory

The Tiangong-2 space laboratory was launched by China on 15 September 2016, carrying the Interferometric Imaging Radar Altimeter (InIRA), the first of the latest generation of imaging altimeters that can perform imaging and acquire elevation information simultaneously. This paper analyzes the feasibility of using InIRA images to obtain two-dimensional characteristics of oceanic internal solitary waves (ISWs) and information about vertical sea surface fluctuations caused by the propagation of ISWs. The results show that InIRA demonstrates a relatively reliable ability to observe ISWs with high resolution and can identify the fine-scale features of ISWs of different forms. Furthermore, InIRA can observe centimeter-level changes in the Sea Surface Height Anomaly (SSHA) caused by ISWs. The geometric relationship between the sensor’s flight direction and the propagation direction of ISWs does not affect its detection effect. However, the swath width of InIRA is too narrow to fully capture ISW information, and the height accuracy of InIRA height product images is not insufficient to detect the height information of small-scale ISWs. These shortcomings need to be considered in the future development of imaging altimeters to increase their potential for detecting mesoscale phenomena in the ocean.

Research on an ionospheric delay correction method for the interferometric imaging radar altimeter based on improved GIM data

ABSTRACT The Interferometric Imaging Radar Altimeter (InIRA) is alow-orbit single-frequency altimeter whose signals are subject to an ionospheric delay, which introduces measurement errors. Additionally, some difficulties, such as selecting the interpolation algorithm and intercepting the height scale, arise when applying the ionospheric correction model. Based on Sentinel-3A dual-frequency measurements, this paper suggests that linear variogram-based kriging is suitable for spatial interpolation, and the total electron content height scale coefficient calculated by the hierarchical IRI forecast model can be applied to the interpolated GIM intercept. When the improved GIM value is applied to four scenes of InIRA data, the obtained Ku-band ionospheric correction varies from 1.49cm to 1.57cm.

Preliminary Significant Wave Height Retrieval from Interferometric Imaging Radar Altimeter Aboard the Chinese Tiangong-2 Space Laboratory

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.

A Novel Ship Wake Detection Algorithm Based on WTHT and Radon Transform

This paper proposes a novel ship wake detection algorithm based on the White Top-hat Transform (WTHT) and the Radon transform, which aims to improve the contrast between the ship wake and the background so as to improve the detection performance on Synthetic Aperture Radar (SAR) images. The proposed algorithm includes two major processes, and one is to improve the contrast and another one is to locate the ship wake. In high sea state conditions, the contrast of ship wake and background can be very low, which makes it difficult to detect. In the first step, the proposed contrast improvement algorithm is applied to improving the contrast which helps for improving the detection performance. An attribute filter based on edge detection result is adopted here. In the second step the contrast improved image is transformed into the Radon domain followed by peak extraction process to find the wake, the WTHT is used once more in this step. Finally, in the last step, the wake is overlapped on the original image. Experimental results on Tiangong-2 Interferometric Imaging Radar Altimeter (InIRA) images are presented and compared with that obtained by using the classical algorithm, and in this way, the better performance of our algorithm is demonstrated.

Sea Surface Imaging Simulation for 3D Interferometric Imaging Radar Altimeter

The interferometric imaging radar altimeter (InIRA) is a new generation radar altimeter, which can provide two-dimensional images of the sea surface topography at high resolution along a wide swath. This article proposes a method for the simulation of sea surface images measured by InIRA. First, the Pierson-Moskowitz wave spectrum and two-scale model are used to simulate the sea surface from which elevation data is to be acquired. This simulated sea surface is then divided into small triangular facets using Delaunay triangulation. Second, the backscattering cross sections of these small facets are calculated via application of quasi-mirror scattering theory, and the backscattering coefficient of the simulated region derived via coherent superposition. Third, system parameters are set, consistent with the basic principle of InIRA. Assuming that the signal transmitted is a linear frequency modulation pulse signal, the simulation images are then derived using the range Doppler and back projection algorithms. By inverting the interferometric phase diagram, elevation estimates can be derived, and compared with original simulated sea levels. This demonstrated accuracy within the centimeter range, verifying the correctness and feasibility of the proposed method.

Preliminary Evaluation and Correction of Sea Surface Height from Chinese Tiangong-2 Interferometric Imaging Radar Altimeter

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.

Correction of the tropospheric slant path delay of Tiangong-2 Interferometric Imaging Radar Altimeter

Correction of the tropospheric slant path delay of Tiangong-2 Interferometric Imaging Radar Altimeter

Non‐uniform phase filter for Tiangong‐2 Interferometric Imaging Radar Altimeter

The interferometric imaging radar altimeter (InIRA) on-board Chinese Tiangong-2 space laboratory is a Ku-band interferometric radar whose major aim is to measure the wide-swath ocean topography. Unlike traditional interferometric synthetic aperture radar (InSAR) aiming at measuring digital elevation model of land surface, Tiangong-2 InIRA adopts small incidence angles and short baseline to get strong and high coherency reflections from ocean surface. The interferometric phase noise is a notable source of errors which limits the accuracy of the ocean height measurements. Compared with traditional InSAR, the height error of Tiangong-2 InIRA shows different distribution pattern due to the absolutely small but relatively large variation incidence angles. This study gives a filtering method for interferometric phase generated with small incidence angles and short baseline. Non-uniform windows are selected according to the relation between the coherence, imaging geometry, and the height variation. Results on Tiangong-2 InIRA data are analysed by comparing the non-uniform filtering method with traditional multi-looking method.

Improved BAQ algorithm for Tiangong‐2 interferometric imaging radar data compression

Tiangong-2 interferometric imaging radar altimeter (InIRA), the first space-borne radar altimeter in the world, applying a new mechanism of interferometry with short baseline and small incident angle, can achieve wide swath and high accuracy sea surface height measuring. Comparing to traditional altimeter, InIRA can obtain SAR image of observation area, which means InIRA needs higher AD sampling rate. Due to the limitation of satellite on-board storage and downlink speed, in order to extend the working time of InIRA, data compression algorithm for InIRA must be studied. Block adaptive quantisation (BAQ) is an efficient and widely adopted approach for space-borne SAR raw data compression. Based on the characters of InIRA echo waveform, this study discusses compressing InIRA raw data by changing quantisation bits and size of blocks of BAQ algorithm to achieve higher compression ratio and less sea surface height error.

Sea Surface Wind Speed Retrieval and Validation of the Interferometric Imaging Radar Altimeter Aboard the Chinese Tiangong-2 Space Laboratory

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 σ 0 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.

AN ASSESSMENT OF SPACEBORNE NEAR-NADIR INTERFEROMETRIC SAR PERFORMANCE OVER INLAND WATERS WITH REAL

Abstract. Elevation measurements of the continental water surface have been poorly collected with in situ measurements or occasionally with conventional altimeters with low accuracy. Techniques using InSAR at near-nadir angles to measure the inland water elevation with large swath and with high accuracy have been proposed, for instance, the WSOA on Jason 2 and the KaRIn on SWOT. However, the WSOA was abandoned unfortunately and the SWOT is planned to be launched in 2021. In this paper, we show real acquisitions of the first spaceborne InSAR of such kind, the Interferometric Imaging Radar Altimeter (InIRA), which has been working on Tiangong II spacecraft since 2016. We used the 90-m SRTM DEM as a reference to estimate the phase offset, and then an empirical calibration model was used to correct the baseline errors.