Improving the iGNSS-R Ocean Altimetric Precision Based on the Coherent Integration Time Optimization Model

Improving the altimetric precision under the requirement of ensuring the along-track resolution is of great significance to the application of iGNSS-R satellite ocean altimetry. The results obtained by using the empirical integration time need to be improved. Optimizing the integration time can suppress the noise interference from different sources to the greatest extent, thereby improving the altimetric precision. The inverse relationship between along-track resolution and signal integration time leads to the latter not being infinite. To obtain the optimal combination of integral parameters, this study first constructs an analytical model whose precision varies with coherent integration time. Second, the model is verified using airborne experimental data. The result shows that the average deviation between the model and the measured precision is about 0.16 m. The two are consistent. Third, we apply the model to obtain the optimal coherent integration time of the airborne experimental scenario. Compared with the empirical coherent integration parameters, the measured precision is improved by about 0.1 m. Fourth, the verified model is extrapolated to different spaceborne scenarios. Then, the optimal coherent integration time and the improvement of measured precision under various conditions are estimated. It was found that the optimal coherent integration time of the spaceborne scene is shorter than that of the airborne scene. Depending on the orbital altitude and the roughness of the sea surface, its value may also vary. Moreover, the model can significantly improve the precision for low signal-to-noise ratios. The coherent integration time optimization model proposed in this paper can enhance the altimetric precision. It would provide theoretical support for the signal optimization processing and sea surface height retrieval of iGNSS-R altimetry satellites with high precision and high along-track resolution in the future.

Evaluation and Correction of Elevation Angle Influence for Coastal GNSS-R Ocean Altimetry

The elevation angle influence on coastal GNSS-R ocean code-based altimetry for GPS signals (L1 C/A and L5) and BDS B1 signals is investigated, and the corresponding correction method is presented. The study first focuses on the coastal ocean altimetry method, including the general experiment geometry and the code delay estimation using the single-point tracking algorithm. The peak power and the maximum first derivative are used as the location of the specular point. Then, the sensitivity of the height retrieved using the above coastal ocean altimetry method to elevation angle is analyzed based on the Z-V model. It can be seen that the elevation angle has a significant influence on the height retrieval, which will affect the precision of the coastal GNSS-R ocean altimetry. Finally, two correction methods, the model-driven method and the data-driven method, are proposed. The coastal altimetry experiments demonstrate that the correction methods can correct the elevation angle influence, and the data-driven method is more effective. The experimental results show that, after correcting the elevation angle influence, the code-based altimetry precision of the GPS L1 C/A signal, L5 signal, and BDS B1 signal can be up to the meter level, decimeter level (less than 4 decimeters), and meter level with respect to a reference tide gauge (TG) data set, respectively, without smoothing over time. These results provide information to guide the sea surface height retrieval using coastal GNSS-R, especially multi-satellite observation and GNSS signal with a higher chipping rate.

Dynamic Mapping of Along-Track Ocean Altimetry: Performance from Real Observations

The dynamic optimal interpolation (DOI) method merges altimetric sea surface height (SSH) data into maps that are continuous in time and space. Unlike the traditional linear optimal interpolation (LOI) method, DOI has the advantage of considering a nonlinear temporal propagation of the SSH field. DOI has been successfully applied to along-track pseudo-observations in observing system simulation experiments (OSSEs), demonstrating a reduction in interpolation error in highly turbulent regions compared to LOI mapping. In the present study, we further extend the validation of the DOI method by an observing system experiment (OSE). We applied and validated the DOI approach with real nadir-altimetric observations in four regional configurations. Overall, the qualitative and quantitative assessments of these realistic SSH maps confirm the higher level of performance of the DOI approach in turbulent regions. It is more of a challenge to outperform the conventional LOI mapping in coastal and low-energy regions. Validations against LOI maps distributed by the Copernicus Marine Environment Monitoring Service indicate a 10%–15% increase in average performance and an improved resolution limit toward shorter wavelengths. The DOI method also shows improved mesoscale mapping of intense jets and fronts and reveals new eddies with smoother trajectories.

Improving the representation of ice-sheet mass changes in the global inversion for sea-level contributions

<p><span>G</span><span>lobal-mean sea level rises (GMSLR) by 3.1-3.5 mm a<sup>-1 </sup></span><span>(1993-2017)</span><span> and </span><span>of which</span><span> about 50 % can be attributed to changes in global-mean ocean mass due to hydrological variations, m</span><span>ass changes</span><span> of land glaciers, </span><span>and</span> <span>mass </span><span>c</span><span>hanges</span><span> of the major ice sheets in Greenland and Antarctica. The i</span><span>ce-sheet contributions</span><span> account for more than </span><span>the</span><span> half of the contemporary ocean mass change </span><span>and can be</span><span> observed w</span><span>ith</span><span> time-variable gravi</span><span>metry</span><span> by the Gravity Recovery and Climate Experiment (GRACE) and its follow-on mission (GRACE-FO). In addition, geometric surface changes due to </span><span>the volume change of</span><span> ice sheets is also observed b</span><span>y polar </span><span>altimetry </span><span>missions</span><span>. </span><span>Of particular importance here is the signal of glacial isostatic adjustment (GIA) which is superimposed with i</span><span>ce mass change</span><span>.</span></p><p><span>Conventionally, the g</span><span>ravimetry</span><span> and ice-altimetry observations are processed independently. For ocean applications, a global fingerprint inversion (Rietbroek et al., 2016) allows to estimate individual mass and steric contributors to the sea-level budget by combi</span><span>ni</span><span>ng GRACE and ocean-altimetry data in a joint approach. To improve the estimates of the ice-sheet contributions to GMSLR, we present first results from additionally incorporating independent ice-altimetry data over Greenland and Antarctica into the fingerprint inversion. We examine the sensitivity of the sea-level contributions to the additional ice-altimetry data </span><span>(from </span><span>ERS-2, Envisat, ICESat, CryoSat-2 </span><span>missions)</span><span> and provide validation against independent estimates. </span><span>I</span><span>n our standard runs</span><span>, </span><span>GIA is </span><span>accounted for </span><span>a</span><span>s an a-priori correction during the inversion.</span><span> H</span><span>owever,</span><span> we demonstrate the potential and limitations of a regional inverse approach i</span><span>n which</span><span> GIA is separated from ice mass change </span><span>over Antarctica</span><span> using GRACE and ice altimetry. In our future work, we a</span><span>im to </span><span>parametrise</span><span> and</span><span> co-</span><span>estimate GIA </span><span>with</span><span>in the global inversion framework.</span></p>

First Field-Test results of iGNSS-R instrument of the PRETTY payload

<p>The PRETTY mission is a 3U CubeSat mission, hosting two different payloads, a radiation dosimeter and an interferometric GNSS reflectometer. The intended launch is planned in 2022.</p><p>The reflectometer payload has been built, using flight representative hardware and mounted inside a portable setup. Two campaigns have been carried out, a first one to verify the setup in real world condition and the second one to record reflectometry data over the Danube river. The reflections over the river are analyzed and compared to a reference data set obtained from basemap.at (which is released under Open Government Data Österreich Lizenz CC-BY 4.0).</p><p>The hardware is capable of generating complex and power waveforms at the same time, and the reflection events are visible in both. Since PRETTY is aiming for phase altimetry, only coherent measurements are conducted with an integration time of 20ms .</p><p>The re-tracking algorithm for the specular point and height estimation are based on [1]. Due to the low elevation angle and receiver height, the effects from the ionosphere is not considered , however effects from the atmosphere have to be included in the data re-tracking process. The reflection peaks, and the signal to noise ratio of the peaks, are large enough detect the peak and to calculate the height of the reflection point. The height retrieval is shown in the paper.</p><p>The results are promising w.r.t. the performance of the overall structure of the PRETTY GNSS-R payload  in order to deliver altimetry results on a low-cost CubeSat platform.</p><p>[1] W. Li, E. Cardellach, F. Fabra, S. Ribó and A. Rius, "Assessment of Spaceborne GNSS-R Ocean Altimetry Performance Using CYGNSS Mission Raw Data," in IEEE Transactions on Geoscience and Remote Sensing, vol. 58, no. 1, pp. 238-250, Jan. 2020. doi: 10.1109/TGRS.2019.2936108</p>