Search Results (83)

The Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2), equipped with the Advanced Topographic Laser Altimeter System (ATLAS), is capable of acquiring large-scale terrain and forest structural information through photon-counting LiDAR. However, photon point clouds exhibit significant noise variability due to diurnal changes and variations in beam intensity, which undermines the accuracy and stability of terrain and canopy height retrievals in forested regions. To address the limited adaptability of existing methods under daytime/nighttime and strong/weak beam conditions, this study proposes a multi-stage processing framework integrating photon denoising, classification, and quasi-full-waveform reconstruction. First, local statistical features combined with adaptive parameter optimization were employed, applying Gaussian and exponential fitting to denoise daytime strong and weak beams and enhance the signal-to-noise ratio (SNR). Subsequently, an improved random sample consensus (RANSAC) algorithm was introduced to remove residual noise and classify photons under both diurnal and beam-intensity variations. Finally, a radial basis function (RBF) interpolation was used to reconstruct quasi-full-waveform curves for terrain and canopy heights. Compared with the ATL08 product (terrain root mean square error (RMSE): 2.65 m for daytime strong beams and 5.77 m for daytime weak beams), the proposed method reduced RMSE by 0.53 m and 1.30 m, respectively, demonstrating enhanced stability and robustness under low-SNR conditions. For canopy height estimation, all beam types showed high consistency with airborne LiDAR measurements, with the highest correlation achieved for nighttime strong beams (R = 0.90), accompanied by the lowest RMSE (4.82 m) and mean absolute error (MAE = 2.97 m). In comparison, ATL08 canopy height errors for nighttime strong beams were higher (RMSE = 5.67 m; MAE = 4.16 m). Notably, significant improvements were observed for weak beams relative to ATL08. These results indicate that the proposed framework effectively denoises and classifies photon point clouds under diverse daytime/nighttime and strong/weak beam conditions, providing a robust methodological reference for high-precision terrain and forest canopy height estimation in forested regions. Full article

Radar altimeters receive radio-wave reflections from nadir and determine surface parameters from the strength and shape of the return signal. Over the oceans, the strength of the return, termed sigma0 (${\sigma }^0$), is strongly related to the small-scale roughness of the ocean surface and is used to estimate near-surface wind speed. However, a number of other factors affect ${\sigma }^0$, and these need to be estimated and compensated for when developing long-term consistent ${\sigma }^0$ records spanning multiple missions. Aside from unresolved issues of absolute calibration, there are various geophysical factors (sea surface temperature, wave height and rain) that have an effect. The choice of the waveform retracking algorithm also affects the ${\sigma }^0$ values, with the four-parameter Maximum Likelihood Estimator introducing a strong dependence on waveform-derived mispointing and the use of delay-Doppler processing leading to apparent variation with spacecraft radial velocity. As all of these terms have strong geographical correlations, care is required to disentangle these various effects in order to establish a long-term consistent record. This goal will enable a better investigation of the long-term changes in wind speed at sea. Full article

Mountain glaciers are the most direct and sensitive indicators of climate change. In the context of global warming, monitoring changes in glacier elevation has become a crucial issue in modern cryosphere research. The Global Ecosystem Dynamics Investigation (GEDI) is a full-waveform laser altimeter with a multi-beam that provides unprecedented measurements of the Earth’s surface. Many studies have investigated its applications in assessing the vertical structure of various forests. However, few studies have assessed GEDI’s performance in detecting variations in glacier elevation in land ice in high-mountain Asia. To address this limitation, we selected the Southeastern Tibetan Plateau (SETP), one of the most sensitive areas to climate change, as a test area to assess the feasibility of using GEDI to monitor glacier elevation changes by comparing it with ICESat-2 ATL06 and the reference TanDEM-X DEM products. Moreover, this study further analyzes the influence of environmental factors (e.g., terrain slope and aspect, and altitude distribution) and glacier attributes (e.g., glacier area and debris cover) on changes in glacier elevation. The results show the following: (1) Compared to ICESat-2, in most cases, GEDI overestimated glacier thinning (i.e., elevation reduction) to some extent from 2019 to 2021, with an average overestimation value of about −0.29 m, while the annual average rate of elevation change was relatively close, at −0.70 ± 0.12 m/yr versus −0.62 ± 0.08 m/yr, respectively. (2) In terms of time, GEDI reflected glacier elevation changes at interannual and seasonal scales, and the trend of change was consistent with that found with ICESat-2. The results indicate that glacier accumulation mainly occurred in spring and winter, while the melting rate accelerated in summer and autumn. (3) GEDI effectively monitored and revealed the characteristics and patterns of glacier elevation changes with different terrain features, glacier area grades, etc.; however, as the slope increased, the accuracy of the reported changes in glacier elevation gradually decreased. Nonetheless, GEDI still provided reasonable estimates for changes in mountain glacier elevation. (4) The spatial distribution of GEDI footprints was uneven, directly affecting the accuracy of the monitoring results. Thus, to improve analyses of changes in glacier elevation, terrain factors should be comprehensively considered in further research. Overall, these promising results have the potential to be used as a basic dataset for further investigations of glacier mass and global climate change research. Full article

We present the validation of the latest version F Geophysical Data Records (GDR-F) for the TOPEX/POSEIDON (T/P) altimetry satellite mission. The GDR-F products represent a major evolution with respect to the preceding version B Merged Geophysical Data Records (MGDR-B) that were released more than two decades ago. Specifically, the numerical retracking of the altimeter waveforms significantly mitigates long-standing issues in the TOPEX altimeter measurements, such as drifts and hemispherical biases in the altimeter range and significant wave height. Additionally, GDR-F incorporates updated geophysical model standards consistent with current altimeter missions, improved sea state bias corrections, end-of-mission calibration for the microwave radiometer, and refined orbit ephemeris solutions. These enhancements notably decrease the variance of the Sea Surface Height Anomaly (SSHA) measurements, with along-track SSHA variance reduced by 26 cm² compared to MGDR-B and crossover SSHA variance lowered by 1 cm². GDR-F products also demonstrate improved consistency with Jason-1 measurements during their tandem mission phase, reducing the standard deviation of differences from 6 cm to 4 cm when compared to Jason-1 GDR-E data. These results confirm that GDR-F products offer a more accurate and consistent T/P data record, enhancing the quality of long-term sea level studies and supporting inter-mission altimetry continuity. Full article

The full-waveform spaceborne laser altimeter improves footprint geolocation accuracy through waveform matching, providing critical data for on-orbit calibration. However, in areas with significant topographic variations or complex surface characteristics, traditional waveform matching methods based on the Pearson correlation coefficient (PCC-Match) are susceptible to errors from laser ranging inaccuracies and discrepancies in surface structures, resulting in reduced footprint geolocation stability. This study proposes a terrain-constrained cross-correlation matching (TC-Match) method. By integrating the terrain characteristics of the laser footprint area with spaceborne altimetry data, a sliding “time-shift” constraint range is constructed. Within this constraint range, an optimal matching search based on waveform structural characteristics is conducted to enhance the robustness and accuracy of footprint geolocation. Using GaoFen-7 (GF-7) satellite laser footprint data, experiments were conducted in regions of Utah and Arizona, USA, for validation. The results show that TC-Match outperforms PCC-Match regarding footprint geolocation accuracy, stability, elevation correction, and systematic bias correction. This study demonstrates that TC-Match significantly improves the geolocation quality of spaceborne laser altimeters under complex terrain conditions, offering good practical engineering adaptability. It provides an effective technical pathway for subsequent on-orbit calibration and precision model optimization of spaceborne laser data. Full article

Sea surface height (SSH) serves as a fundamental geophysical parameter in oceanographic research. In 2023, China successfully launched the world’s first spaceborne interferometric GNSS-R (iGNSS-R) altimeter, which features dual-frequency multi-beam scanning, interferometric processing, and compatibility with three major satellite navigation systems: the BeiDou Navigation Satellite System (BDS), the Global Positioning System (GPS), and the Galileo Satellite Navigation System (GAL). This launch marked the first in-orbit validation of the iGNSS-R altimetry technology. This study provides a detailed overview of the iGNSS-R payload design and analyzes its dual-frequency delay mapping (DM) measurements. We developed a refined DM waveform-matching algorithm that precisely extracts the propagation delays between reflected and direct GNSS signals, enabling the retrieval of global sea surface height (SSH) through the interferometric altimetry model. For validation, we employed an inter-satellite crossover approach using Jason-3 and Sentinel-6 radar altimetry as references, achieving an unprecedented SSH accuracy of 17.2 cm at a 40 km resolution. This represents a breakthrough improvement over previous GNSS-R altimetry efforts. The successful demonstration of iGNSS-R technology opens up new possibilities for cost-effective, wide-swath sea level monitoring. It showcases the potential of GNSS-R technology to complement existing ocean observation systems and enhance our understanding of global sea surface dynamics. Full article

The observation of small to medium inland water targets with nadir radar altimeters is currently limited by the along-track resolution of UnFocused SAR (UFSAR) altimetry, which is approximately 300 $\mathrm{m}$ for Delay-Doppler processors. In this study, we analyze the benefits of the sub-meter along-track resolution provided by Fully Focused SAR (FFSAR) altimetry applied to Sentinel-6 Michael Freilich data over a collection of small to medium targets in the Ebre Basin, Spain. The obtained water level estimations over a 2-year period are compared to in situ data to evaluate the long-term accuracy of the algorithm. The proposed FFSAR altimetry methodology achieves an average MAD precision of roughly 4 $\mathrm{c}$$\mathrm{m}$, and allows for a full operational implementation as it can be processed in a totally unsupervised manner. The precision improvement with respect to Delay-Doppler products over the same targets is essentially attributed to the FFSAR capabilities to better filter out waveforms contaminated by off-nadir scatterers. Moreover, we evaluate the application of extended water masks, which exploit nadir–altimeter measurements where water is at nadir or up to 250 $\mathrm{m}$ across-track from nadir to increase the number of acquisitions while maintaining the same level of accuracy, increasing by an average of 48% the number of valid measurements per pass, while maintaining the same level of accuracy as nadir measurements over water. We thus demonstrate the potential of FFSAR altimetry to monitor the water level of small to medium inland water targets. Full article

The 5G frequency band is extremely close to the operating frequency band of radio altimeters (RAs), so an in-depth study of the possible interference of 5G’s key parameters on RAs is especially necessary to ensure aviation safety. In this paper, the interference magnitude of 5G waveforms on an altimeter was measured by simulating the Adjacent Channel Leakage Power Ratio (ACLR) values for different sub-carrier spacing (SCS) and channel bandwidth configurations. Furthermore, interference injection experiments on simulated 5G signals and the interference thresholds of a frequency-modulated continuous wave (FMCW) altimeter were compared to experiments on the effects of the different configurations of 5G SCSs, channel bandwidths, and center frequency points. The interference thresholds of this FMCW altimeter were found to be in the range of 1 dBm to 6 dBm and −4 dBm to 0 dBm under the interference of 5G signals at the center frequency points of 3.7 GHz and 3.9 GHz. These results provided a certain reference for the engineering judgement margin of the interference thresholds. Full article

Accurate estimates of forest aboveground biomass (AGB) are necessary for the accurate tracking of forest carbon stock. Gaofen-7 (GF-7) is the first civilian sub-meter three-dimensional (3D) mapping satellite from China. It is equipped with a laser altimeter system and a dual-line array stereoscopic mapping camera, which enables it to synchronously generate full-waveform LiDAR data and stereoscopic images. The bulk of existing research has examined how accurate GF-7 is for topographic measurements of bare land or canopy height. The measurement of forest aboveground biomass has not received as much attention as it deserves. This study aimed to assess the GF-7 stereo imaging capability, displayed as topographic features for aboveground biomass estimation in forests. The aboveground biomass model was constructed using the random forest machine learning technique, which was accomplished by combining the use of in situ field measurements, pairs of GF-7 stereo images, and the corresponding generated canopy height model (CHM). Findings showed that the biomass estimation model had an accuracy of R² = 0.76, RMSE = 7.94 t/ha, which was better than the inclusion of forest canopy height (R² = 0.30, RMSE = 21.02 t/ha). These results show that GF-7 has considerable application potential in gathering large-scale high-precision forest aboveground biomass using a restricted amount of field data. Full article

Anomalies displaying significant deviations between terrain elevation products acquired from spaceborne full-waveform LiDAR and reference elevations are frequently observed in assessment studies. While the predominant focus is on “normal” data, recognizing anomalies within datasets obtained from the Geoscience Laser Altimeter System (GLAS) and the Global Ecosystem Dynamics Investigation (GEDI) is essential for a comprehensive understanding of widely used spaceborne full-waveform data, which not only facilitates optimal data utilization but also enhances the exploration of potential applications. Nevertheless, our comprehension of anomalies remains limited as they have received scant specific attention. Diverging from prevalent practices of directly eliminating outliers, we conducted a targeted exploration of anomalies in forested areas using both transmitted and return waveforms from the GLAS and the GEDI in conjunction with airborne LiDAR point cloud data. We unveiled that elevation anomalies stem not from the transmitted pulses or product algorithms, but rather from scattering sources. We further observed similarities between the GLAS and the GEDI despite their considerable disparities in sensor parameters, with the waveforms characterized by a low signal-to-noise ratio and a near exponential decay in return energy; specifically, return signals of anomalies originated from clouds rather than the land surface. This discovery underscores the potential of deriving cloud-top height from spaceborne full-waveform LiDAR missions, particularly the GEDI, suggesting promising prospects for applying GEDI data in atmospheric science—an area that has received scant attention thus far. To mitigate the impact of abnormal return waveforms on diverse land surface studies, we strongly recommend incorporating spaceborne LiDAR-offered terrain elevation in data filtering by establishing an elevation-difference threshold against a reference elevation. This is especially vital for studies concerning forest parameters due to potential cloud interference, yet a consensus has not been reached within the community. Full article

Reformation of the 3.7–4.0 GHz band to expand 5G communication deployment poses a risk of 5G signals disrupting radar altimeter operation, leading to data loss or inaccuracies. Thus, this paper proposes a guard band protection method to facilitate the coexistence of 5G base stations and radar altimeters operating in the 4.2–4.4 GHz band. To enhance the adjacent channel leakage ratio (ACLR), we implemented spectral regrowth on an oversampled waveform using a high-power amplifier model, filtering out-of-band spectral emissions. The results demonstrated that a 150 MHz guard band enables coexistence, except in the case of the 16-by-16 antenna array in rural environments. Notably, for the 4-by-4 antenna array in urban environments, coexistence can be achieved using a 50 MHz guard band. The proposed mitigation techniques may also be extended to promote coexistence between non-terrestrial networks and 5G communication systems, including satellites, unmanned aerial vehicles, and hot air balloons. Full article

This research advances millimeter-wave (mmWave) altimetry for unmanned aerial systems (UASs) by optimizing performance metrics within the constraints of inexpensive automotive radars. Leveraging the software-defined architecture, this study encompasses the intricacies of frequency modulated continuous waveform (FMCW) design for three distinct stages of UAS flight: cruise, landing approach, and touchdown within a signal processing framework. Angle of arrival (AoA) estimation, traditionally employed in terrain mapping applications, is largely unexplored for UAS radar altimeters (RAs). Time-division multiplexing multiple input–multiple output (TDM-MIMO) is an efficient method for enhancing angular resolution without compromising the size, weight, and power (SWaP) characteristics. Accordingly, this work argues the potential of AoA estimation using TDM-MIMO to augment situational awareness in challenging landing scenarios. To this end, two corner cases comprising landing a small-sized drone on a platform in the middle of a water body are included. Likewise, for the touchdown stage, an improvised rendition of zoom fast Fourier transform (ZFFT) is investigated to achieve millimeter (mm)-level range accuracy. Aptly, it is proposed that a mm-level accurate RA may be exploited as a software redundancy for the critical weight-on-wheels (WoW) system in fixed-wing commercial UASs. Each stage is simulated as a radar scenario using the specifications of automotive radar operating in the 77–81 GHz band to optimize waveform design, setting the stage for field verification. This article addresses challenges arising from radial velocity due to UAS descent rates and terrain variation through theoretical and mathematical approaches for characterization and mandatory compensation. While constant false alarm rate (CFAR) algorithms have been reported for ground detection, a comparison of their variants within the scope UAS altimetry is limited. This study appraises popular CFAR variants to achieve optimized ground detection performance. The authors advocate for dedicated minimum operational performance standards (MOPS) for UAS RAs. Lastly, this body of work identifies potential challenges, proposes solutions, and outlines future research directions. Full article

Sentinel-6 Michael Freilich (S6-MF) is the first altimeter operating in a continuous high-rate pulse mode, i.e., interleaved mode. This ensures the generation of low-resolution (LR) mode measurements with a pulse repetition frequency (PRF) of ∼9 kHz (variable along the orbit) for the Ku-band as well as the processing of high-resolution (HR) echoes on ground. This operating mode provides an elevated number of highly correlated single looks with respect to the fewer number, weakly correlated echoes of Jason-3 altimeter. A theoretical model is exploited to envisage the correlation properties of S6-MF pulse limited waveform echoes for different sea-state conditions; after that, the model is validated by comparison with the equivalent number of looks (ENL) empirically estimated from real data. The existence of a significant dependence of the statistical properties on the range is verified, and its impact on the precision and on the accuracy in the estimation of the geophysical parameters is assessed in case of the 9 kHz PRF of S6-MF. By applying pulse decimation before the multilook processing, an investigation on new processing techniques is performed, aimed at exploiting the higher ENL in S6-MF low-resolution mode waveforms. It is shown that a bias of less than 0.4 cm is found for SSH and about 1.5 cm for SWH at SWH = 2 m when the decimated waveforms processing is compared with full high-PRF processing. Full article

This study presents the first azimuth cutoff analysis in Synthetic Aperture Radar (SAR) altimetry, aiming to assess its applicability in characterizing sea-state dynamics. In SAR imaging, the azimuth cutoff serves as a proxy for the shortest waves, in terms of wavelength, that can be detected by the satellite under certain wind and wave conditions. The magnitude of this parameter is closely related to the wave orbital velocity variance, a key parameter for characterizing wind-wave systems. We exploit wave modulations exhibited in the tail of fully-focused SAR waveforms and extract the azimuth cutoff from the radar signal through the analysis of its along-track autocorrelation function. We showcase the capability of Sentinel-6A in deriving these two parameters based on analyses in the spatial and wavenumber domains, accompanied by a discussion of the limitations. We use Level-1A high-resolution Sentinel-6A data from one repeat cycle (10 days) globally to verify our findings against wave modeled data. In the spatial domain analysis, the estimation of azimuth cutoff involves fitting a Gaussian function to the along-track autocorrelation function. Results reveal pronounced dependencies on wind speed and significant wave height, factors primarily determining the magnitude of the velocity variance. In extreme sea states, the parameters are underestimated by the altimeter, while in relatively calm sea states and in the presence of swells, a substantial overestimation trend is observed. We introduce an alternative approach to extract the azimuth cutoff by identifying the fall-off wavenumber in the wavenumber domain. Results indicate effective mitigation of swell-induced errors, with some additional sensitivity to extreme sea states compared to the spatial domain approach. Full article

Precise altitude data are indispensable for flight navigation, particularly during the autonomous landing of unmanned aerial systems (UASs). Conventional light and barometric sensors employed for altitude estimation are limited by poor visibility and temperature conditions, respectively, whilst global positioning system (GPS) receivers provide the altitude from the mean sea level (MSL) marred with a slow update rate. To cater to the landing safety requirements, UASs necessitate precise altitude information above ground level (AGL) impervious to environmental conditions. Radar altimeters, a mainstay in commercial aviation for at least half a century, realize these requirements through minimum operational performance standards (MOPSs). More recently, the proliferation of 5G technology and interference with the universally allocated band for radar altimeters from 4.2 to 4.4 GHz underscores the necessity to explore novel avenues. Notably, there is no dedicated MOPS tailored for radar altimeters of UASs. To gauge the performance of a radar altimeter offering for UASs, existing MOPSs are the de facto choice. Historically, frequency-modulated continuous wave (FMCW) radars have been extensively used in a broad spectrum of ranging applications including radar altimeters. Modern monolithic millimeter wave (mmWave) automotive radars, albeit designed for automotive applications, also employ FMCW for precise ranging with a cost-effective and compact footprint. Given the technology maturation with excellent size, weight, and power (SWaP) metrics, there is a growing trend in industry and academia to explore their efficacy beyond the realm of the automotive industry. To this end, their feasibility for UAS altimetry remains largely untapped. While the literature on theoretical discourse is prevalent, a specific focus on mmWave radar altimetry is lacking. Moreover, clutter estimation with hardware specifications of a pure look-down mmWave radar is unreported. This article argues the applicability of MOPSs for commercial aviation for adaptation to a UAS use case. The theme of the work is a tutorial based on a simplified mathematical and theoretical discussion on the understanding of performance metrics and inherent intricacies. A systems engineering approach for deriving waveform specifications from operational requirements of a UAS is offered. Lastly, proposed future research directions and insights are included. Full article