MEO-SAR in-orbit Elevation Antenna Pattern Determination Using Nano Calibration Satellite

Low-earth-orbit (LEO) synthetic aperture radar (SAR) can achieve advanced remote sensing applications benefiting from the large beam coverage and long duration time of interested area provided by a geosynchronous (GEO) SAR illuminator. In addition, the receiving LEO SAR system is also cost-effective because the transmitting module can be omitted. In this article, an imaging method for GEO-LEO bistatic SAR (BiSAR) is proposed. First, the propagation delay characteristics of GEO-LEO BiSAR are studied. It is found that the traditional "stop-and-go" propagation delay assumption is not appropriate due to the long transmitting path and high speed of the LEO SAR receiver. Then, an improved propagation delay model and the corresponding range model for GEO-LEO BiSAR are established to lay the foundation of accurate imaging. After analyzing the sampling characteristics of GEO-LEO BiSAR, it is found that only 12.5% sampling data can be acquired in the azimuth direction. To handle the serious sub-Nyquist sampling problem and achieve good focusing results, an imaging method combined with multireceiving technique and compressed sensing is proposed. The multireceiving observation model is first obtained based on the inverse process of a nonlinear chirp-scaling imaging method, which can handle 2-D space-variant echo. Following that, the imaging problem of GEO-LEO BiSAR is converted to an L <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sub> regularization problem. Finally, an effective recovery method named complex approximate message passing (CAMP) is applied to obtain the final nonambiguous image. Simulation results show that the proposed method can suppress eight times Doppler ambiguity and obtain the well-focused image with three receiving channels. With the proposed method, the number of required receiving channels can be greatly reduced.

A novel synthetic aperture radar (SAR) constellation called Constellation of Geostationary and Low Earth Orbit SAR (ConGaLSAR), including one geostationary illuminator and several low Earth orbit CubeSat transponders, was previously proposed with outstanding revisiting. The MirrorSAR technology used in transponder significantly simplifies the satellite; however, it brings complexity to the imaging geometry, resulting in failures of the traditional bistatic imaging method. The introduction of probe signals achieves accurate measurement of the additional transponding distance. In this article, a three-step imaging method is proposed to realize accurate imaging processing aiming at the transponding mechanism and wide swath observation: 1) linear time variation for range cell migration grid correction; 2) second range compression for the additional squint angle introduced in the previous step; and 3) range cell migration correction in the range-Doppler domain for nonuniform cell grid caused by bistatic SAR (BiSAR). Digital simulations and real BiSAR data experiments are conducted to verify the effectiveness and accuracy of the algorithm. Moreover, the influence of the elevation is analyzed, confirming its excellent tolerance of elevation errors under the condition of a 3-m resolution and a 40-km swath width, which conforms to the system design of ConGaLSAR.

The 3-D deformation retrieval is significant for the accurate evaluation of geologic disasters (e.g., earthquakes and landslides). Multiple-aperture interferometry (MAI) is an effective method to obtain 3-D deformation, combined with the cross-heading tracks synthetic aperture radar (SAR) data. However, because of the limitations of the low earth orbit SAR, a long satellite revisit time, small common areas of the cross-heading tracks data, and the unsatisfied along-track deformation measurement accuracy usually exist in the traditional MAI 3-D deformation retrieval. Geosynchronous SAR (GEO SAR) runs in the geosynchronous orbit, which has the advantages of a large observation area and a short revisit time. This paper focuses on 3-D deformation retrieval by GEO SAR MAI processing. Aiming at the high orbit and the squint looking of GEO SAR, the accurate expressions of the along-track deformation, 3-D deformation, and the errors in GEO SAR MAI processing are given. The distortions and their correction in the MAI interferogram brought by the geometrical difference between the forward- and backward-looking interferograms and the multicycles flat-earth and topographic phases are given. Moreover, an optimal subaperture selection method based on minimum position dilution of precision is proposed. Finally, the effectiveness of the proposed method is validated by simulations and the experiment of BeiDou-2 inclined geosynchronous orbit navigation satellite. The theoretical analysis and the experimental results suggest centimeter-level and even millimeter-level deformation measurement accuracy could be obtained in 3-D by GEO SAR MAI processing.

Geosynchronous synthetic aperture radar (GEO SAR) data focusing is a more challenging and difficult task than the low earth orbit (LEO) SAR due to the strong 2-D coupling of echo signal induced by the orbital trajectory curvature. The range cell migration (RCM) in the GEO SAR configuration is space variant in both range and azimuth directions, hence standard RCM correction (RCMC) functions developed for LEO SAR are inadequate for GEO. In this letter, a curved trajectory model is proposed, taking into consideration the impacts of "stop-and-go" assumption. Based on the range model, a new data transform is derived to deal with the complicated coupling in GEO SAR. From the derivation, we find that the original Stolt mapping is a special case of the proposed "generalized Omega-k" algorithm. In comparison with the original Omega-k algorithm, this new algorithm can correct more complicated RCM effectively. Finally, simulation results show that the proposed imaging algorithm performs well for large scene focusing in an L-Band GEO SAR system.

Circular synthetic aperture radar (SAR) imaging on the geosynchronous orbit has many potential advantages, such as high-resolution three-dimensional (3D) imaging and continuous surveillance of broad area. The mission considered is an L-band geosynchronous circular SAR (GEOCSAR) with full aperture measurement. Since the integration time of GEOCSAR can be as long as 24 h, the orbit altitude is about 36 000 km and the coverage may reach 1/3 of the Earth's surface. The spatial and temporal variation of the ionosphere may impose significant effects on 3D imaging performance of GEOCSAR. The effects of ionospheric spatial variation including vertical and horizontal structure, the ionospheric turbulence and the ionospheric temporal variation are discussed. The analysis shows that the temporal variation of the ionospheric electron content during the synthetic aperture and the ionospheric turbulence may severely affect the GEOCSAR focusing performance on the XY plane. The vertical and horizontal structure of the ionosphere will cause image shift, and the dispersion effect is negligible.

Tropical natural forests play a crucial role in regulating the climate and maintaining global ecosystem functions. However, they face significant challenges due to human activities and climate change. Accurate classification of these forests can help reveal their spatial distribution patterns and support conservation efforts. This study employed four machine learning algorithms—random forest (RF), support vector machine (SVM), Logistic Regression (LR), and Extreme Gradient Boosting (XGBoost)—to classify tropical rainforests, tropical monsoon rainforests, tropical coniferous forests, broadleaf evergreen forests, and mangrove forests on Hainan Island using optical and synthetic aperture radar (SAR) multi-source remote sensing data. Among these, the XGBoost model achieved the best performance, with an overall accuracy of 0.89 and a Kappa coefficient of 0.82. Elevation and red-edge spectral bands were identified as the most important features for classification. Spatial distribution analysis revealed distinct patterns, such as mangrove forests occurring at the lowest elevations and tropical rainforests occupying middle and low elevations. The integration of optical and SAR data significantly enhanced classification accuracy and boundary recognition compared to using optical data alone. These findings underscore the effectiveness of machine learning and multi-source data for tropical forest classification, providing a valuable reference for ecological monitoring and sustainable management.

Computerized Ionospheric Tomography (CIT) is a power tool for investigating the ionospheric electron density in three-dimensional space, and has important implications for weather forecast and scientific research. The existing researches on CIT are mostly based on the GPS data, which have disadvantages of complex operation, bad environment adaptability, small covering area and so on. The researches on CIT based on space-borne SAR are still at primarily stage and the relevant research methods are based on the low earth orbit SAR (LEO SAR) data, which have disadvantages of real-time performance and small covering area. This paper proposes a CIT technique based on geosynchronous SAR (GEO SAR), which may well solve the problems in the existing CIT techniques. In this paper, firstly, the advantages of CIT based on GEO SAR are analyzed. Then, the geometry and implementation process of CIT technique based on GEO SAR are given. Moreover, a GEO SAR satellite formation design is proposed in order to achieve better CIT performance. Finally, the simulation results of CIT based on GEO SAR using the International Reference Ionosphere (IRI) data are shown, verifying the theoretical analysis.

The ability of differential interferometric synthetic aperture radar (DInSAR) technology used for centimeter level deformation detection has been well-proved. Nevertheless, the applications of DInSAR under the low Earth orbit (LEO) are limited to the line-of-sight (LOS) measurements, the limited observation area and the long revisited time. Geosynchronous SAR (GEO SAR), which runs in the height of 36000 km with the advantage of a short revisit time and a large observation area, is a potential approach to overcome the series problems in LEO SAR. This paper focuses on estimating three-dimensional (3D) displacements by using GEO SAR DInSAR measurements acquired from multiple imaging geometries. Aiming to provide a normal solution for geologic hazard monitoring and relative geophysical application in the future, the errors induced by decorrelation noise, orbital ramp and ionospheric distortion are analyzed for the GEO SAR DInSAR measurements. A series of experiments have been conducted to find the relationship between the 3D displacements and the DInSAR observations which are provided with different noises and combinations of imaging geometries. The results reveal that 3D displacements can be expected from the combination of left- and right-looking GEO SAR DInSAR measurements. In particular, the north-south solution can achieve centimeter and even millimeter level.

Due to the effects of the earth’s rotation and the satellite’s elliptical orbit, the Doppler centroid varies along the orbit in geosynchronous earth orbit synthetic aperture radar (GEO SAR). With an ultrahigh orbit height, the beam may illuminate outside the earth surface with a rotation angle large than 9 degrees. Therefore, the usual attitude steering methods to minimize the Doppler centroid in low earth orbit SAR (LEO SAR) may not be suitable for GEO SAR. In this paper, a novel steering strategy to maximize Nesigma0 for GEO SAR is proposed when the beam illuminates outside the earth surface. The new geometry and the gradient method are applied to demonstrate the method. The ability to stare imaging in geosynchronous orbit SAR is analyzed and verified by using the back projection (BP) algorithm to simulate the imaging principle. Nesigma0 under the new method improved 1dB comparing with the original image.

Hunters and gatherers living in tropical forests represent an important part of the total range of variation among contemporary hunting and gathering societies. Studies of tropical forest hunting and gathering peoples have contributed to our perceptions of the foraging way of life. Yet no peoples have ever been directly observed living independently of agriculture in tropical rain forest. This article tests the hypothesis that humans do not exist nor have ever existed independently of agriculture in tropical rain forest. We find no convincing ethnographic evidence and, with the possible exception of Malaysia, no archeological evidence for pure foragers in undisturbed tropical rain forests. Negative evidence cannot be conclusive, but it suggests that we need to carefully reexamine common assumptions concerning the recent history of tropical forest dwellers, the adaptability of preagricultural humans, the geographic and environmental range of hominids, and the form and consequences of selection pressures acting on humans in warm, humid environments. The overriding purpose of this article is to stimulate further ecological and archeological research in the neglected tropical forest areas of the world.

Minimum carbon uptake controls the interannual variability of ecosystem productivity in tropical evergreen forests

Circular synthetic aperture radar (SAR) imaging on the geosynchronous orbit has significant potential advantages, such as high resolution three-dimensional imaging, large coverage, but it also has challenges to overcome. One major problem limiting the high-resolution geosynchronous circular SAR (GEOCSAR) performances is the atmospheric effects including the tropospheric and ionospheric effects. In this study, the authors mainly consider the tropospheric effects on L-band GEOCSAR imaging. Since the integration time of GEOCSAR may be as long as 24 h, and the coverage can reach 1/3 of the Earth's surface, the effects of the spatial and temporal variation of the tropospheric refractive index cannot be ignored if well focused images are to be obtained. The analysis shows that the temporal variation of the tropospheric refractive index may cause severe degradation of the SAR images; the spatial variation of the refractive index and the tropospheric turbulence are not the important factor limiting the GEOCSAR imaging performance.

In this dissertation, several advancements in the field of synthetic aperture radar (SAR) polarimetry are described. First, a calibration technique for a dual-polarized antenna is developed, allowing polarimetric calibration to be performed through the measurement of specific square- or circular-waveguide loads, resulting in improvement in measurement accuracy when performing polarimetric SAR measurements. Imaging experiments are performed using a fabricated dual-polarized antenna and calibration loads, validating the efficacy of this calibration procedure. Second, a technique is developed enabling SAR polarimetric measurements to be made using a single polarization configuration, making use of the unique polarization pattern of a radially-polarized antenna. This technique possesses the full capabilities of previously used polarimetric SAR techniques, while at the same time vastly simplifies the necessary hardware and the calibration procedure. To this end, a specialized SAR imaging algorithm is developed, and imaging experiments are performed that demonstrate the effectiveness and accuracy of this technique compared to traditional SAR polarimetry methods. Third, a SAR 3D polarimetry technique is developed, by which targets can be characterized by their 3D features such as relative orientation about all three axes of rotation. A SAR imaging algorithm is developed for this purpose, and imaging experiments are performed to demonstrate the efficacy of the method. The advancements made in this work open the door for SAR polarimetry to be used in a much more diverse set of applications. Fourth, SAR polarimetry was applied to the specific nondestructive evaluation (NDE) application of detection and characterization of fiber misalignment in carbon and glass fiber polymer (CFRP and GFRP) composites. CFRP and GFRP samples are manufactured with fiber misalignment, and two different polarimetric SAR techniques, one of which is SAR 3D polarimetry, are used to detect the misalignment and determine the specific misalignment angles in each sample.

Tropical rain forests of the Far East forest structure animals in the forest the forest environment - climate seasonal cycles in plants and animals seed dispersal to seedling establishment growth of seedlings into trees the ecological basis of rain-forest silviculture growth rates, forest yields and biomass inorganic nutrients and their cycling the forest environment - soils forest formations 1 - the dry-land rain forests forest formations 2 - the wet-land rain forests monsoon forest formations animal life and forest formations conifers in the forest variation within the tropical lowland evergreen rain forests and its causes mountain rain forests man and the tropical rain forest secondary forest and shifting cultivation looking ahead. Appendix: select list of publications containing descriptions of tropical rain forest in the countries of the Far East. Bibliography, index of plant names, general index.

Multi-channel synthetic aperture radar (SAR) systems enable high-resolution wide-swath imagery thus overcoming the inherent limitation of conventional SAR. A possible realization based on the combination of multi-aperture SAR signal reconstruction in azimuth with digital beamforming on receive in elevation is given in [1]. The present paper turns focus to advanced concepts for the imaging of even wider swaths while still providing high azimuth resolution [2]. In this regard, the operation of multi-channel SAR systems in burst modes like ScanSAR or TOPS is introduced and aspects of applying the multi-aperture reconstruction algorithm to burst mode data are analyzed. The influence of the digital processing network on performance parameters as signal-to-noise-ratio and azimuth ambiguity-to-signal-ratio in multi-channel burst mode systems is considered and embedded in the design example of a ScanSAR system that allows for the imaging of a 400 km wide swath with a geometric resolution of 5 m. Finally, first results for a multi-channel TOPS system are presented and an optimized TOPS processing approach is introduced.