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2019 IEEE International Conference on Signal, information and Data Processing, ICSIDP 2019

作者： Tan, Aijun Tan, Zefu Tian, Weiming Yan, Manjun Long, Ying Key Laboratory of Information and Signal Processing Chongqing Three Gorges University Chongqing China Key Laboratory of Electronic and Information Technology in Satellite Navigation Ministry of Education Beijing China

ISBN: (纸本)9781728123455

Ground-based differential interferometric radar is widely used in deformation monitoring research, but the one-dimensional deformation information dynamically acquired along the radar line of sight is often affected by random noise error and measurement error. In order to solve this problem, this paper proposes a deformation data processing method of ground-based differential interferometric radar based on Kalman filter. Firstly, the principle of ground-based differential interference technology is deeply studied. Then, based on the characteristics of deformation data monitored by ground-based radar, the Kalman filter data processing model is used to filter and predict the data. Finally, the measured data of slope monitoring in Malanzhuang open-pit mining is used. The effectiveness of the algorithm is verified by simulation and the accuracy of deformation data processing is greatly improved. © 2019 IEEE.

关键词： Kalman filters

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A Remote Sensing Image Matching Algorithm Based on Anisotropic Scale Space

A Remote Sensing Image Matching Algorithm Based on Anisotrop...

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2019 IEEE International Conference on Signal, information and Data Processing, ICSIDP 2019

作者： Yan, Manjun Tan, Zefu Tian, Weiming Tan, Aijun Zhang, Yi Key Laboratory of Information and Signal Processing Chongqing Three Gorges University Chongqing China Key Laboratory of Electronic and Information Technology in Satellite Navigation Ministry of Education Beijing China

ISBN: (纸本)9781728123455

Aiming at the influence of nonlinear brightness difference and noise on remote sensing image matching algorithm, a remote sensing image matching algorithm based on anisotropic scale space is proposed. Firstly, we use the additiveoperator splitting (AOS) algorithm to build the anisotropics cale space;Then, we extract feature points in the nonlinear scale space by Harris algorithm, and use the improved SIFT descriptor to describe the features;Finally, the nearest neighbor distance ratio is used to filter the matching point pairs, and the fast sample consensus (FSC) algorithm is used to delete the mismatch to improve the matching accuracy. This method can maintain the matching accuracy while increase the number of points. Extensive experiments results on different sensors that our method can improve the matching accuracy. © 2019 IEEE.

关键词： Remote sensing

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Analysis of Influencing Factors and Research on Strategy Optimization of BDS satellite Clock Bias Prediction

Analysis of Influencing Factors and Research on Strategy Opt...

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2024 International Seminar on Artificial Intelligence, Computer technology and Control Engineering, ACTCE 2024

作者： Ma, Ming Xu, Jie Guo, Yu College of Electronic Science and Technology Changsha China Key Laboratory of Satellite Navigation Technology Changsha China

ISBN: (纸本)9798331521714

The current research work on GNSS satellite clock bias prediction models and methods is very rich, but the research on the optimal accuracy of GNSS satellite clock bias prediction is not deep enough. In view of this problem, this paper constructs a satellite clock bias prediction model and analyzes the comprehensive influence of fitting time, prediction time, orbital height and satellite clock characteristics on the prediction accuracy. In this paper, the BDS satellite clock bias product provided by IGS are used to analyze and predict the optimal strategy. The results show that the better the performance of the satellite clock, the higher the prediction accuracy. The optimal fitting time of the clock bias prediction is related to the satellite's orbit. The BDS satellite clock bias has low prediction accuracy when the fitting time is 12h~24h, and stable prediction accuracy when it is 36h~108h, both of which are better than 0.5ns. The fitting time is 4 times and 7 times the orbital period of the MEO satellite (48h and 84h), and the prediction accuracy is the highest, and the prediction accuracy within 1h is better than 0.3ns. © 2024 IEEE.

关键词： Prediction models

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Design and research of kalman filter in multi-GNSS receiver

Design and research of kalman filter in multi-GNSS receiver

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IET International Radar Conference 2015

作者： Liu, Shuo Zhang, Lei Li, Jian Liu, Feng School of Information and Electronics Beijing Institute of Technology Beijing China Key Laboratory of Electronic and Information Technology in Satellite Navigation Beijing Institute of Technology Ministry of Education China

ISBN: (纸本)9781849199940

With the rapid development of GNSS receiver's performance and the coming of each GNSS's Full Operational Capability (FOC), compatibility and interoperability must be one of the developing trends of GNSS positioning. In this study, a compatible kalman filter was designed. The performances of the compatible kalman filter (KF) and traditional Least Square (LS) were compared through BDS, GPS, and GLONASS real static data in different conditions. The result shows that the compatible KF has more stability and robustness than LS. Position solutions can be obtained from the compatible KF even when the number of satellites is not enough for LS.

关键词： Kalman filters

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Design of satellite Constellations for Maximizing Regional Coverage Time Using Genetic Algorithms 2

Design of Satellite Constellations for Maximizing Regional C...

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2nd IEEE International Conference on Signal, information and Data Processing, ICSIDP 2024

作者： Guo, Zhijun Chen, Xinliang Li, Yuanshuai Zhang, Hao Liu, Quanhua Beijing Institute of Technology School of Information and Electronics Beijing China Beijing Institute of Technology Yangtze Delta Region Academy Jiaxing China Beijing Institute of Technology Key Laboratory of Electronic and Information Technology in Satellite Navigation School of Information and Electronics Beijing China Key Laboratory of Electronic and Information Technology in Satellite Navigation Beijing Institute of Technology Chongqing Innovation Center Beijing China

ISBN: (纸本)9798331515669

The satellite's payload collects and transmits information only within its field of view. To accomplish the detection mission, a satellite constellation of a certain scale needs to be designed. In this paper, a genetic algorithm is used to optimize the satellite combination on a fixed orbit to maximize the coverage time of the target area. The interconnection between MATLAB and STK is implemented through the COM interface, and a hash table is introduced to eliminate duplicate calculations, significantly improving the algorithm's performance. Simulation results show that this method has potential for application in large-scale satellite network coverage optimization. © 2024 IEEE.

关键词： MATLAB

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DDMA MIMO radar system for low, slow, and small target detection

DDMA MIMO radar system for low, slow, and small target detec...

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IET International Radar Conference 2018, IRC 2018

作者： Yang, Fawei Xu, Feng Yang, Xiaopeng Liu, Quanhua Key Laboratory of Electronic and Information Technology in Satellite Navigation Beijing Institute of Technology Ministry of Education Beijing100081 China

The low, slow, and small (LSS) target detection has always been a problem for both ground-based and air-borne radar systems. The factors such as weak target reflection energy, ground clutter, and random Doppler component will have a severe impact on radar detection performance. In recent years, researches on multiple-input multiple-output (MIMO) radar system have achieved great progress. By utilising multi-channel and multi-waveform technology, MIMO radar can form equivalent phase centres and virtual apertures to provide more system freedom and enhance detection performance. To address the LSS target-detection problem, the authors propose a novel Doppler division multiple access (DDMA) MIMO radar system, which employ DDMA waveform to ensure the orthogonality of the transmit signal and avoid some of the problems in the application of frequency division multiple access (FDMA) and code division multiple access (CDMA) for the actual radar system. The sparse array is employed to supress the grating lobe of the beam pattern and improve the angle estimation performance by optimising the position of the antenna array elements. Finally, the architecture of the designed radar system is introduced and the results of the detection performance to LSS targets based on real measured data is given. © 2019 Institution of Engineering and technology. All rights reserved.

关键词： MIMO systems

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An approach of gross error elimination in GNSS receiver hot start

An approach of gross error elimination in GNSS receiver hot ...

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IET International Radar Conference 2015

作者： Liu, Shuo Zhang, Lei Li, Jian Long, Teng School of Information and Electronics Beijing Institute of Technology Beijing China Key Laboratory of Electronic and Information Technology in Satellite Navigation Beijing Institute of Technology Ministry of Education China

ISBN: (纸本)9781849199940

With the rapid development of the GNSS receiver's performance, almost all the commercial receivers have the ability of hot start. The main algorithm of fast positioning is how to get the position before frame synchronization when hot start. Because of the incomplete information of the pseudorange calculation before frame synchronization, the pseudorange is calculated by its estimation of integer millisecond part and inside millisecond part. If the estimation is wrong, the position error will be huge because of the huge pseudorange error, and it need to be researched and improved further. Firstly, the principle of fast positioning when hot start is introduced, the estimation and combination of pseudorange before frame synchronization and the correction of the position of satellite because of the unknown of the send time are derived in detail. The influence of the shift of general position and coarse receiver time error to fast positioning is discussed, the result shows the accuracy of fast positioning when the shifting is not abnormal and original least squares are nearly the same. When the pseudorange combination is just in the middle of a millisecond, a little shift of general position and coarse receiver time error will lead to a huge estimation error in pseudorange. For the gross error coming from the misestimating of the pseudorange, robust least squares are proposed to correct the gross error, the result of the simulation shows it's an effective way to correct the gross error.

关键词： Errors

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Lightweight Image Super-Resolution via Weighted Multi-Scale Residual Network

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IEEE/CAA Journal of Automatica Sinica 2021年第7期8卷 1271-1280页

作者： Long Sun Zhenbing Liu Xiyan Sun Licheng Liu Rushi Lan Xiaonan Luo Guangxi Key Laboratory of Image and Graphic intelligent processing Guilin University of Electronic TechnologyGuilin 541004China National Local Joint Engineering Research Center of Satellite Navigation and Location Service Guilin University of Electronic TechnologyGuilin 541004China the College of Electrical and Information Engineering Hunan UniversityChangsha 410082China

The tradeoff between efficiency and model size of the convolutional neural network(CNN)is an essential issue for applications of CNN-based algorithms to diverse real-world *** deep learning-based methods have achieved significant improvements in image super-resolution(SR),current CNNbased techniques mainly contain massive parameters and a high computational complexity,limiting their practical *** this paper,we present a fast and lightweight framework,named weighted multi-scale residual network(WMRN),for a better tradeoff between SR performance and computational *** the modified residual structure,depthwise separable convolutions(DS Convs)are employed to improve convolutional operations’***,several weighted multi-scale residual blocks(WMRBs)are stacked to enhance the multi-scale representation *** the reconstruction subnetwork,a group of Conv layers are introduced to filter feature maps to reconstruct the final high-quality *** experiments were conducted to evaluate the proposed model,and the comparative results with several state-of-the-art algorithms demonstrate the effectiveness of WMRN.

关键词： Convolutional neural network(CNN) lightweight framework multi-scale super-resolution

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A PC software design for monitoring receiver of BeiDou navigation satellite system

A PC software design for monitoring receiver of BeiDou Navig...

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IET International Radar Conference 2015

作者： Luo, Yiran Zhang, Lei Li, Jian Key Laboratory of Electronic and Information Technology in Satellite Navigation Beijing Institute of Technology Ministry of Education China Radar Research Laboratory Beijing Institute of Technology Beijing China

ISBN: (纸本)9781849199940

satellite navigation monitoring receiver makes it possible that navigation system can provide high-reliability and high-precise measurement data. In this paper, the Personal Computer (PC) software controls the work status of a receiver. Therefore, it is necessary to design a reliable PC software for receiver working. This paper proposes a programming method with Microsoft Foundation Classes (MFC) of PC software for monitoring receiver which monitors the BeiDou navigation satellite System (BDS) of new civil signal. PC software reads the data from NPort and necessary information can be exactly displayed on the interface. Besides, the information can also be saved as a specified file. Compared to the traditional serial port, data can be transmitted by more than one port simultaneously through NPort. It has been proved that this method makes the transmission more effective than the traditional serial port.

关键词： Personal computers

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Cooperative Angles-Only Relative navigation Algorithm for Multi-Spacecraft Formation in Close-Range

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Computer Modeling in Engineering & Sciences 2023年第1期134卷 121-134页

作者： Sha Wang Chenglong He Baichun Gong Xin Ding Yanhua Yuan State Key Laboratory of Satellite Navigation System and Equipment Technology Shijiazhuang050081China Nanjing University of Aeronautics and Astronautics Nanjing210016China Beijing Institute of Control and Electronic Technology Beijing100038China

As to solve the collaborative relative navigation problem for near-circular orbiting small satellites in close-range under GNSS denied environment,a novel consensus constrained relative navigation algorithm based on the lever arm effect of the sensor offset from the spacecraft center of mass is ***,the orbital propagation model for the relative motion of multi-spacecraft is established based on Hill-Clohessy-Wiltshire dynamics and the line-of-sight measurement under sensor offset condition is modeled in Local Vertical Local Horizontal ***,the consensus constraint model for the relative orbit state is constructed by introducing the geometry constraint between the spacecraft,based on which the consensus unscented Kalman filter is ***,the observability analysis is done and the necessary conditions of the sensor offset to make the state observable are ***,digital simulations are conducted to verify the proposed algorithm,where the comparison to the unconstrained case is also *** results show that the estimated error of the relative position converges very quickly,the location error is smaller than 10m under the condition of 10−3 rad level camera and 5m offset.

关键词： Relative navigation spacecraft formation observability analysis angles-only measurement

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