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Copyright of Telecommunication Engineering is the property of Telecommunication Engineering and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Systems Engineering & Electronics is the property of Journal of Systems Engineering & Electronics Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Appropriate and effective resource scheduling is the key to achieving the best performance for a space-based radar. Considering the resource scheduling problem of multi-target tracking in a space-based radar system, we establish a cost function that considers target threat, tracking accuracy, and Low Probability of Interception (LPI). Considering target uncertainty and constraints of the space-based platform and long-term expected cost, we establish a resource scheduling model based on the Partially Observable Markov Decision Process (POMDP) with multiple constraints. To transform and decompose the resource scheduling problem of multi-target tracking with multiple constraints into multiple unconstrained sub-problems, we use the Lagrangian relaxation method. To deal with the curse of dimensionality caused by the continuous state space, continuous action space and continuous observation space, we use the online POMDP algorithm based on the Monte Carlo Tree Search (MCTS) and partially observable Monte Carlo planning with observation widening algorithm. Finally, a non-myopic and fast resource scheduling algorithm with comprehensive performance indices for multi-target tracking in a space-based radar system is proposed. Simulation results show that the proposed algorithm, when compared with the existing scheduling algorithms, allocates resources more appropriately and shows better performance.

When single space-based radar tracks and detects air targets, problems such as missing pitch angle information and nonlinear measurement lead to large target height estimation errors. Multi-space-based radar networking can solve this problem. Moreover, considering the system’s requirements for low computational complexity, low communication overhead, high accuracy, and high reliability, a consistency-based method for height estimation and location of air targets in a distributed space-based radar network is proposed. First, an air target motion model and a space-based radar measurement model are presented. Second, based on probabilistic graphical model theory, a factor graph for multi-frame measurement of target tracking and positioning in a space-based radar network is established. The coupling relationship between several local target motion states is established based on consistency fusion. Third, combining particle filtering and belief propagation establishes the message representation and iterative calculation rules of nonparametric belief propagation on the fusion tracking for factor graph of space-based radar networking. Finally, the performance of the algorithm is tested through simulation. The simulation results show that compared with the distributed consensus extended Kalman filter, the proposed algorithm improves the target height estimation accuracy by 35.3%, effectively improving the target localization performance of the space-based radar.

Copyright of Systems Engineering & Electronics is the property of Journal of Systems Engineering & Electronics Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Systems Engineering & Electronics is the property of Journal of Systems Engineering & Electronics Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Nowadays, the target detection technology for synthetic aperture radar( SAR) images has been widely researched and applied, and the deep learning method can be effectively applied to ship detection under complex background features, and the detection accuracy and speed are also has certain improvement. In order to further improve the detection speed and accuracy in the SAR ship target scene, a fast detection method for a single type of target in SAR ship images is proposed. The YOLOv4-Tiny network is modified by applying depthwise separable convolution, and on top of this, improved channel and spatial attention mechanisms are added to improve accuracy. Taking the input image size of 608 x 608 as the benchmark, compared with the YOLOv4-Tiny model, the experimental results show that the detection accuracy of the method in this paper can reach 93.91%, the detection speed can reach 42.8 frame/s, and the model is improved by 11.7 frame/s. The weight is only 2.17 MB in size, which is about 1/10 of that of YOLOv4-Tiny. The model is conducive to the deployment of hardware on the board, and meets the needs of fast detection scenarios for ship targets in SAR images. [ABSTRACT FROM AUTHOR]

To enhanced the information security protection capability of communication satellites and solved the information security monitoring problem of the system under the condition of limited on-board resources, based on the comparison of some typical information security protection designs, this paper summarized the characteristics and security threats of the communication satellites, analyzed the constraints on improved security protection capabilities, then proposed a sort of collecting satellite security data by using space based probe technology, built data analysis platform and integrated monitoring system based on the ground system, which could realized the system security status monitoring and security alarm on the premise of ensuring the normal operation of the satellite business and low resource occupancy. At last the actual operation of the system was analyzed and verified. [ABSTRACT FROM AUTHOR]

Copyright of World Nuclear Geoscience is the property of World Nuclear Geoscience Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Ordnance Industry Automation is the property of Editorial Board for Ordnance Industry Automation and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Objectives: Interferogram filtering is the key to the subsequent processing steps of interferometric synthetic aperture radar, such as phase unwrapping and geocoding. However, the existing filtering methods can't retain features in dense fringes and accurately estimate phase in low-coherence regions. The convolutional neural networks (CNN) is introduced to learn noise features and solve this problem. Methods: First, we selected a certain number of interferograms as samples, and divided them into training set, test set, and validation set. Second,we preprocessed the training set samples, and cut the preprocessed training set interferograms into small fixed-size block and randomly extract it as a model training sample, used the above steps to train the autoencoder filter model, after a certain number of iterations, the model was fitted. Results: Experiments were carried out on spaceborne imaging radar-C-band synthetic aperture radar data and Sentinel-1A data. Our proposed method was compared with Goldstein filter, mean filter, Lee filter, Frost filter, and improved denoising convolutional neural network (DnCNN). Goldstein filter can remove most of the noise while maintaining fringes edge, has good denoising ability. Mean filter performs well in high-coherence areas, but performs poorly in low-coherence areas, and can't filter noise well. Lee filter maintains it well image resolution, but the denoising effect is weak, and it can be seen from the filtering results that there is still a lot of noise. Frost filtering is weak in low-coherence areas and there is a lot of noise, but the fringe edges are well maintained in high-coherence areas. The improved DnCNN filter can significantly eliminate the noise, but it can't distinguish the fringe edge and the noise well. Our proposed method can suppress the noise very well, and it can maintain the fringe edge well in the low-coherence area and the high-coherence area. Conclusions: This proposed method can greatly improve the phase quality of the interferogram, suppress the noise to a greater extent, and restore more image details and maintain the edge continuity of the interference fringe. [ABSTRACT FROM AUTHOR]

Copyright of Systems Engineering & Electronics is the property of Journal of Systems Engineering & Electronics Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Industrial Minerals & Processing / Huagong Kuangwu yu Jiagong is the property of Industrial Minerals & Processing Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Remote Sensing is the property of Editorial Office of Journal of Remote Sensing & Science Publishing Co. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Objectives: Differential interferometric synthetic aperture radar(DInSAR) has been widely used in large-scale surface deformation monitoring. However, the surface deformation obtained from spaceborne synthetic aperture radar(SAR) data is easily affected by atmospheric noise, and the long revisit period leads to the incoherence. In order to effectively reduce these effects, we propose a method to monitor the deformation of highway slope by vehicle-borne InSAR system. Methods: Due to the orbit control of the vehicleborne dual-antenna InSAR system, the spatial baseline of the interferometric pairs is close to zero. Therefore, when the DInSAR data with this system is used to extract the deformation information, it can avoid the flat phase, which greatly simplifies the differential interference processing process. Results:A certain area of Wuhan, Hubei Province is chosen as the experimental area. Seven corner reflectors are deployed in the test area to evaluate the accuracy of deformation information extracted using the vehicle-borne dual-antenna InSAR system. The deformation of seven reflectors is calculated by using the proposed method. The root mean square error of deformation between the real value and the calculated value is 2.206 mm. Conclusions: A deformation monitoring method of zero space baseline using the vehicle-borne dual-antenna InSAR system is proposed and verified in Wuhan city. The DInSAR method based on zero space baseline can avoid the process of the flat phase. At the same time, our system is small in size, and the design of the trajectory according to the actual needs is flexibly, which is very practical for small-scale highway slope deformation monitoring. Because of the small revisit period, the vehicle-borne InSAR Data will not produce phase error due to atmospheric delay, and the deformation measurement accuracy is high. [ABSTRACT FROM AUTHOR]

Copyright of Control Theory & Applications / Kongzhi Lilun Yu Yinyong is the property of Editorial Department of Control Theory & Applications and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Experimental Technology & Management is the property of Experimental Technology & Management Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Telecommunication Engineering is the property of Telecommunication Engineering and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

By using the self-developed unmanned aerial vehicle (UAV) borne mini synthetic aperture radar (MiniSAR) system, all-directional echoes for multiple types of representative ground targets are collected and used for image processing by the Radar Detection and Imaging Techniques Research Group of Nanjing University of Aeronautics & Astronantics (NUAA). A proprietary SAR database for complex targets is constructed, based on which artificial-intelligence-inspired target recognition approaches are studied. To solve the challenging issue of SAR image defocus caused by unstable movement of the UAV platform and the limited accuracy provided by the accessory sensors, novel movement compensation and auto-focus processing methods are proposed. The impact of the image defocus on the classification accuracies provided by the neural networks is revealed, and the limited generalizability of the existing neural networks is demonstrated. Simulation results show that although the classic neural networks, such as AlexNet, ResNet-18, AConvNet, and VGG offer a near-100% accuracy for the MSTAR 10-target classification problem, the 9-class target classification accuracies provided by these networks for the MiniSAR dataset are all much lower than 90%. Since the experiment method employed in this paper closely resembles the practical application scenario, the proposed database will be of great reference value to the development of SAR target recognition algorithms for engineering applications. [ABSTRACT FROM AUTHOR]

Copyright of Systems Engineering & Electronics is the property of Journal of Systems Engineering & Electronics Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Geography & Geographic Information Science is the property of Geography & Geo-Information Science Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of East China University of Science & Technology is the property of Journal of East China University of Science & Technology Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Space-Integrated-Ground Information Networks is the property of Beijing Xintong Media Co., Ltd. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

According to the matching difficulties of mules-sensor remote sensing images, a new synthetic aperture radar (SAR) and optical image registration approach based on image style transfer invariable features is proposed. First, the style transfer neural network for SAR image conversion to optical image is trained. Then, the artificial optical image and the difference map between the artificial optical image and the original SAR image are generated based on the style transfer neural network, and the edge regions of the artificial optical image and the difference image are enhanced by using the multi-scale characteristics of wavelet. Alter binary segmentation, the stable edge features of the artificial optical image. And the edge features of the optical reference image are also extracted. Finally, the edge features are matched by the cross-correlation criterion to achieve the accurate registration between the original SAR image and the optical reference image. The experiments demonstrate that the artificial optical image can be accurately registered with the optical reference image even under the condition of insufficient training samples. This enhances the adaptability of the algorithm. [ABSTRACT FROM AUTHOR]

Copyright of Systems Engineering & Electronics is the property of Journal of Systems Engineering & Electronics Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Hydrographic Surveying & Charting / Haiyang Cehui is the property of Hydrographic Surveying & Charting Editorial Board and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Systems Engineering & Electronics is the property of Journal of Systems Engineering & Electronics Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Telecommunication Engineering is the property of Telecommunication Engineering and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Remote Sensing is the property of Editorial Office of Journal of Remote Sensing & Science Publishing Co. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Remote Sensing is the property of Editorial Office of Journal of Remote Sensing & Science Publishing Co. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Telecommunication Engineering is the property of Telecommunication Engineering and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The subband spectral cancellation (SSC) is an effective method to suppress radio frequency interference (RFI) of synthetic aperture radar (SAR). But it is easy to lose the image detail information while eliminating the interference, which affects the subsequent image interpretation. Therefore, based on the SSC method, combined with change detection technology, an improved SAR image interference suppression method is proposed. According to the improved log ratio change detection operator, the proposed method realizes the secondary detection of interference, eliminates the false alarm information in the interference image, and avoids the loss of useful signals in the image. Based on the wide-band mode interference SAR image of the European Space Agency Sentinel-1 A satellite, the interference suppression and effect evaluation are carried out. The experimental results show that the proposed method can effectively suppress the interference and retain the SAR image details as much as possible, which proves the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

In this paper, the domestic research results of heavy rain in China by using instruments of spectral remote sensing, passive microwave remote sensing and active microwave radar on-board satellite are reviewed. In the study of heavy rain by satellite spectral remote sensing, the brightness temperature at infrared channels is applied to monitor the development of heavy rain cloud clusters, and conducted a lot of research with application value in combination with reanalysis data, rain gauge observation results and weather models. In the aspect of passive microwave research on heavy rain, studies on improving weather model prediction ability is mainly carried out by combining passive microwave brightness temperature with variational assimilation system, but rarely using passive microwave multi-channel brightness temperature to retrieve cloud parameters of heavy rain. Meanwhile, in the area of heavy rain structure measured by satellite precipitation radars, many heavy rain cases are analyzed, and the spatial and temporal distribution of heavy rain intensity and frequency in China are investigated. It is also pointed out that the combination of the satellite multi-instrument remote sensing signals with the radiation transfer model and the high resolution cloud model is expected to obtain the atmospheric dynamic parameters, atmospheric thermodynamic parameters and cloud parameters of the storm clouds in the future.

The water level of coastal wetlands is essential to the growth of mangroves in the development of the local economy. The current monitoring system still relies on hydrological stations to obtain the regular water level at fixed positions. However, the high costs of the conventional method cannot meet the harsh requirements in time. Satellite altimetry technology can be widely expected to serve as an effective supplement to ground monitoring. Taking the coastal wetland of Beibu Gulf in Guangxi as the research object, this study aims to propose a feasible monitoring technology for the water level using the daily Jason-3 and Sentinel-3A altimetry data from 2016 to 2020. The initial value of water level was calculated in coastal wetland through the radar altimetry toolbox, where the triple middle error was used to remove the outliers. The obtained initial points of the water level in the coastal wetland were first imported into the Omap, thereby removing the redundancy data of water level falling on the land and vegetation coverage. As such, high accuracy was achieved to prevent the waveforms near shore from the land. Four re-tracking were then used to correct the water level in the height measurement, including the shift of gravity center, threshold value, the improved shift of gravity center, and the improved threshold value. The determination coefficient, the Root Mean Square Error (RMSE), and the Mean Absolute Error (MAE) were selected to quantitatively evaluate the accuracy of two altimetry satellites. High-precision altimetry satellites were selected to explore the intra-year and inter-annual dynamic changes of water level in the coastal wetland at the intra-year, monthly, seasonal, and annual average water level. The results showed that the best re-setting effect was achieved in the improved threshold for the water level of coastal wetlands. By Jason-3A, the maximum determination coefficient was 0.78, the minimum RMSE was 0.35 m, and the minimum MAE was 0.28. By Sentinel-3A, the maximum determination coefficient was 0.87, the minimum RMSE was 0.24 m, and the minimum MAE was 0.18 m. It inferred that the high monitoring accuracy was obtained by Sentinel-3A. There was also obvious seasonality for the water level change of the coastal wetland in Beibu Gulf from 2016 to 2020. The average change of the water level was 3.37 m during the year. There was a drastic downward trend in the water level changes as a whole, with an average annual change rate of 0.005 m/a. The spaceborne radar altimeter provides a powerful method for monitoring the water level of coastal wetlands on a large scale, which is of great significance to the study of coastal wetland changes and ecological environment protection. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Remote Sensing is the property of Editorial Office of Journal of Remote Sensing & Science Publishing Co. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Systems Engineering & Electronics is the property of Journal of Systems Engineering & Electronics Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Remote Sensing is the property of Editorial Office of Journal of Remote Sensing & Science Publishing Co. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Glacier motion represents a significant reference for the hazard assessment of glacier and glacial lakes.GF-3,as the first civil spaceborne synthetic aperture radar satellite in China,has important advantages in monitoring glacier motion due to its characteristics of all-weather, all-time capabilities and high spatial resolution. Based on five GF-3 images with FS Ⅱ imaging modes, the surface velocities of the Yiga Glacier, located in Nyenchen Tonglha Mountains, are estimated over five time periods using offset tracking technique during November 2017 to March 2018. The results were compared with the offset tracking results of Sentinel-1 images which have a similar time with GF-3 image and based on the assumption that the velocity of the bedrock in the study area should be 0, the velocity residuals of the bedrock in each period are calculated, then the applicability of GF-3 image in monitoring glacier surface motion was evaluated. The results of GF-3 data show that the distribution of the Yiga Glacier motion is similar in four periods, and the maximum surface velocities are all distributed in the central part of the glacier where the elevation changes dramatically. Meanwhile, the results are consistent with the results of Sentinel-1 based on two images. The RMSEs of velocity residuals in the bedrock area in four periods are 1.4 cm/d, 2.0 cm/d, 1.7 cm/d and 2.3 cm/d, respectively, which validate the reliability of the deformation estimated used GF-3 images in this paper. Based on the above analysis, GF-3 SAR data can be used as one of the conventional data sources for monitoring glacier surface movement. Because of its high spatial resolution and high cost performance, GF-3 can play a unique role in monitoring the motions of glaciers in China. [ABSTRACT FROM AUTHOR]

To solve the problem of high precision calibration of three‐dimensional baseline of space‐borne distributed interferometric synthetic aperture radar （InSAR） , a new method of baseline calibration is proposed. Firstly, this method combines the slave radar Doppler equation and the slave radar distance modification equation to form the baseline calibration model. Based on the ground control points, the least square iteration is used to solve the baseline three axial errors. Compared with the baseline calibration model based on the slave radar distance modification equation, the baseline calibration model optimizes the coefficient matrix condition number of the normal equation, reduces the morbidity of the matrix, and improves the calibration precision. Then, according to the baseline calibration, the baseline vector is actually used to intersect by the ground control points, and the intersection angle can be increased to improve the accuracy of the intersection. The control point layout strategy is given, that is, the control points are laid separately at the near and far ends of the radar footprint at ground. Compared with the way of laying control point uniformly, we can significantly improve the calibration precision and robustness. Finally, the spaceborne distributed InSAR simulation data was used to carry out the baseline calibration experiments based on different control points number, different control points precision, and different control points layout. The experiments show that the new method can achieve high ‐ precision result of three ‐ dimensional baseline calibration, namely, millimeter‐scale in cross‐track, along‐track and radial baseline direction respectively, which can provide a new way for the baseline calibration of spaceborne distributed InSAR . [ABSTRACT FROM AUTHOR]

In spaceborne SAR (Synthetic Aperture Radar) , the pulse compression of LFM (Linear Frequency Modulated) signal would be affected by the system phase error which changes in the space environment. Therefore a method of in-orbit phase pre-distortion for LFM signal based on polynomial fitting is put forward, in which the system phase error is obtained by in-orbit calibration, the phase compensation parameters are obtained by polynomial fitting on ground, and by uploading phase compensation parameters, LFM signal with compensation phase is generated by in-orbit calculation. The basis of the theory is described, as well as the realizing flow of the method is presented. Also, hardware requirements and advantages of the method are analyzed. The method is compared with other methods, and is verified to be efficient by the simulation and experiments in real system. [ABSTRACT FROM AUTHOR]

With a view to the requirement of geostationary orbital objects surveillance, the RCS characteristic of geostationary orbital targets is analyzed. Based on the work, the orbital altitude and revisiting period of space-based radar are designed in detail, so are the antenna's form and size. The relationship between imaging resolutions of spaceborne ISAR and system parameters is discussed. Furthermore, the integration time according to appointed cross range resolution is proposed on the direct orbit or retrograde orbit conditions. The research work indicates that it is feasible to surveil geostationary orbital objects nearby relatively using spaceborne wideband radar. [ABSTRACT FROM AUTHOR]