Global Navigation Satellite System(GNSS)can provide all-weather,all-time,high-precision positioning,navigation and timing services,which plays an important role in national security,national economy,public life and ot...Global Navigation Satellite System(GNSS)can provide all-weather,all-time,high-precision positioning,navigation and timing services,which plays an important role in national security,national economy,public life and other aspects.However,in environments with limited satellite signals such as urban canyons,tunnels,and indoor spaces,it is difficult to provide accurate and reliable positioning services only by satellite navigation.Multi-source sensor integrated navigation can effectively overcome the limitations of single-sensor navigation through the fusion of different types of sensor data such as Inertial Measurement Unit(IMU),vision sensor,and LiDAR,and provide more accurate,stable and robust navigation information in complex environments.We summarizes the research status of multi-source sensor integrated navigation technology,and focuses on the representative innovations and applications of integrated navigation and positioning technology by major domestic scientific research institutions in China during 2019—2023.展开更多
This paper presents a new information fusion filter in integrated navigation. The method can improve the fault-tolerant performance and make well fault detection, isolation and reconfiguration of the integrated naviga...This paper presents a new information fusion filter in integrated navigation. The method can improve the fault-tolerant performance and make well fault detection, isolation and reconfiguration of the integrated navigation system exist. Based on three sensors'(strapdown system, GPS receiver, Doppler radar) information fusion, a fault-tolerant navigation system is designed with this information fusion filter and two-ellipsoid overlap test. Simulation results show that the design is efficient with the soft-failure of gyro, accelerator, GPS receiver and Doppler radar.展开更多
An effective autonomous navigation system for the integration of star sensor,infrared horizon sensor,magnetometer,radar altimeter and ultraviolet sensor is developed.The requirements of the integrated navigation syste...An effective autonomous navigation system for the integration of star sensor,infrared horizon sensor,magnetometer,radar altimeter and ultraviolet sensor is developed.The requirements of the integrated navigation system manager make optimum use of the various navigation sensors and allow rapid fault detection,isolation and recovery.The normal full fusion feedback method of federated unscented Kalman filter(UKF) cannot meet the needs of it.So a no-reset feedback federated Kalman filter architecture is developed and used in the autonomous navigation system.The minimal skew sigma points are chosen to improve the calculation speed.Simulation results are presented to demonstrate the advantages of the algorithm.These advantages include improved failure detection and correction,improved computational efficiency,and reliability.Additionally,its' accuracy is higher than that of the full fusion feedback method.展开更多
The interest for land navigation has increased for the recent years. With the advent of the Global Position System (GPS) we have now the ability to determine the absolute position anywhere on the globe. The problem is...The interest for land navigation has increased for the recent years. With the advent of the Global Position System (GPS) we have now the ability to determine the absolute position anywhere on the globe. The problem is that the GPS systems work well only in open environments with no overhead obstructions and they are subject to large unavoidable errors when the reception from some of the satellites are blocked. This occurs frequently in urban environments, forests and tunnels. GPS systems require at least four “visible” satellites to maintain a good position fix. In many situations in which higher level of accuracy is required, the navigation cannot be achieved by GPS alone. This paper discusses the design of a reliable multisensor fusion algorithm using GPS and Inertial Navigation System in order to decrease the implementation cost of such systems on land vehicles. The major contribution of this paper is in the definition of the possible developments and research axes in land navigation.展开更多
With the development of unmanned driving technology,intelligent robots and drones,high-precision localization,navigation and state estimation technologies have also made great progress.Traditional global navigation sa...With the development of unmanned driving technology,intelligent robots and drones,high-precision localization,navigation and state estimation technologies have also made great progress.Traditional global navigation satellite system/inertial navigation system(GNSS/INS)integrated navigation systems can provide high-precision navigation information continuously.However,when this system is applied to indoor or GNSS-denied environments,such as outdoor substations with strong electromagnetic interference and complex dense spaces,it is often unable to obtain high-precision GNSS positioning data.The positioning and orientation errors will diverge and accumulate rapidly,which cannot meet the high-precision localization requirements in large-scale and long-distance navigation scenarios.This paper proposes a method of high-precision state estimation with fusion of GNSS/INS/Vision using a nonlinear optimizer factor graph optimization as the basis for multi-source optimization.Through the collected experimental data and simulation results,this system shows good performance in the indoor environment and the environment with partial GNSS signal loss.展开更多
Inertial/gravity matching integrated navigation system can effectively improve the longendurance navigation ability of underwater vehicles.Through the analysis of the matching process,the problem of unequal-interval i...Inertial/gravity matching integrated navigation system can effectively improve the longendurance navigation ability of underwater vehicles.Through the analysis of the matching process,the problem of unequal-interval in matching trajectory is addressed by an unequal-interval data fusion algorithm which is based on the unequal-interval characteristics analysis of the matching trajectory.Compared with previously available methods,the proposed algorithm improves the location precision.In conclusion,simulations of the integrated navigation system demonstrated the effectiveness and superiority of the proposed algorithm.展开更多
<strong>Introduction:</strong> Sonography is the most universally used imaging technique for planning and performing thermal ablation in Hepatocellular carcinoma patients due to its efficiency and safety. ...<strong>Introduction:</strong> Sonography is the most universally used imaging technique for planning and performing thermal ablation in Hepatocellular carcinoma patients due to its efficiency and safety. However, the presence of HCC nodules that are hardly visible on traditional sonography is a major drawback to its use during thermal ablation. Real-time image fusion (fusion imaging) or real-time virtual sonography is a new technology that has been developed. <strong>Aim: </strong>To determine the value of fusion/navigation guided percutaneous thermal ablation in the management of hepatocellular carcinoma that has poor conspicuity at conventional sonography. <strong>Subjects and Methods:</strong> This study included 70 HCC patients (BCLC A and B). Percutaneous radiofrequency ablation was done via real-time image fusion for 14 patients with poorly visible HCC nodules (study group), while Percutaneous radiofrequency ablation was done via traditional sonography for 56 patients with HCC nodules (control group). <strong>Results:</strong> The median time to reach the tumor was significantly shorter by using fusion navigation technique (<strong><em>P</em> = 0.034)</strong>. By using fusion navigation technique 92% of the lesions were completely ablated while 55% only were completely ablated by using ultrasonography (<strong><em>P</em> = 0.014</strong>). One year after the procedure , by using fusion navigation technique 92% of the patients had complete response and only 55% of the patients had complete response by using conventional ultrasonography (<strong><em>P</em></strong><strong> = 0.011</strong>). The survival distributions for both interventions were statistically significantly different, χ<sup>2</sup> = 10.12, <strong><em>P </em>= 0.001</strong>. <strong>Conclusion:</strong> Fusion imaging-guided percutaneous RFA is a reasonable and efficient treatment of patients with HCC undetectable by traditional ultrasonography.展开更多
On the basis of the basic principles of weighted fusion, Kalman filtering and BP neural networks, the basic principles of information fusion methods used in integrated navigation systems are expounded. Through the ana...On the basis of the basic principles of weighted fusion, Kalman filtering and BP neural networks, the basic principles of information fusion methods used in integrated navigation systems are expounded. Through the analysis of the basic principles, the as-sociation of information fusion methods commonly used in integrated navigation systems and information failure modes is obtained: the information fault mode of weighted fusion method The model is closely related to the specific weight allocation method, which depends on the fault mode of the sensor or sub-system in which the weight is dominant;the information fault mode of the Kalman filtering information fusion method is a continuous mutation fault corresponding to the nonlinear time interval of the system;the in-formation fault mode of the BP neural network method is gradual with time. The information failure mode of the BP neural network method is a slowly varying fault that gradually accumulates over time. Starting from the complexity associated with the information fusion method and the information failure mode, it is pointed out that in order to systematically express the relationship between the information fusion method and the information failure mode, further research can be carried out.展开更多
At present,most experimental teaching systems lack guidance of an operator,and thus users often do not know what to do during an experiment.The user load is therefore increased,and the learning efficiency of the stude...At present,most experimental teaching systems lack guidance of an operator,and thus users often do not know what to do during an experiment.The user load is therefore increased,and the learning efficiency of the students is decreased.To solve the problem of insufficient system interactivity and guidance,an experimental navigation system based on multi-mode fusion is proposed in this paper.The system first obtains user information by sensing the hardware devices,intelligently perceives the user intention and progress of the experiment according to the information acquired,and finally carries out a multi-modal intelligent navigation process for users.As an innovative aspect of this study,an intelligent multi-mode navigation system is used to guide users in conducting experiments,thereby reducing the user load and enabling the users to effectively complete their experiments.The results prove that this system can guide users in completing their experiments,and can effectively reduce the user load during the interaction process and improve the efficiency.展开更多
In this paper, the multisensor data fusion technique of a fault tolerant integrated navigation system is discussed. A neural approach for data fusion is proposed for multisensor integrated systems. The simulation res...In this paper, the multisensor data fusion technique of a fault tolerant integrated navigation system is discussed. A neural approach for data fusion is proposed for multisensor integrated systems. The simulation results show that this neural approach for data fusion is feasible.展开更多
In order to take full advantage of federated filter in fault-tolerant design of integrated navigation system, the limitation of fault detection algorithm for gradual changing fault detection and the poor fault toleran...In order to take full advantage of federated filter in fault-tolerant design of integrated navigation system, the limitation of fault detection algorithm for gradual changing fault detection and the poor fault tolerance of global optimal fusion algorithm are the key problems to deal with. Based on theoretical analysis of the influencing factors of federated filtering fault tolerance, global fault-tolerant fusion algorithm and information sharing algorithm are proposed based on fuzzy assessment. It achieves intelligent fault-tolerant structure with two-stage and feedback, including real-time fault detection in sub-filters, and fault-tolerant fusion and information sharing in main filter. The simulation results demonstrate that the algorithm can effectively improve fault-tolerant ability and ensure relatively high positioning precision of integrated navigation system when a subsystem having gradual changing fault.展开更多
For the underwater integrated navigation system, information fusion is an important technology. This paper introduces the Kalman filter as the most useful information fusion technology, and then gives a summary of the...For the underwater integrated navigation system, information fusion is an important technology. This paper introduces the Kalman filter as the most useful information fusion technology, and then gives a summary of the Kalman filter applied in underwater integrated navigation system at present, and points out the further research directions in this field.展开更多
An integrated navlgation based on the kinematic or dynamic state model and the raw measurements has the advantages of high redundancy, high reliability, as well as high ability of fault tolerance and simplicity in cal...An integrated navlgation based on the kinematic or dynamic state model and the raw measurements has the advantages of high redundancy, high reliability, as well as high ability of fault tolerance and simplicity in calculation. In order to control the influences of measurements outliers and the kinematic model errors on the integrated navigation results, a robust estimation method and an adaptive data fusion method are applied. An integrated navigation example using simulated data is performed and analyzed.展开更多
This paper introduces the image fusion approach of multi-resolutionanalysis-based intensity modulation (MRAIM) to produce the high-resolution multi-spectral imagesfrom high-resolution panchromatic image and low-resolu...This paper introduces the image fusion approach of multi-resolutionanalysis-based intensity modulation (MRAIM) to produce the high-resolution multi-spectral imagesfrom high-resolution panchromatic image and low-resolution multi-spectral images for navigationinformation infrastructure. The mathematical model of image fusion is derived according to theprinciple of remote sensing image formation. It shows that the pixel values of a high-resolutionmulti-spectral images are determined by the pixel values of the approximation of a high-resolutionpanchromatic image at the resolution level of low-resolution multi-spectral images, and in the pixelvalae computation the M-band wavelet theory and the a trous algorithm are then used. In order toevaluate the MRAIM approach, an experiment has been carried out on the basis of the IKONOS 1 mpanchromatic image and 4 m multi-spectral images. The result demonstrates that MRAIM image fusionapproach gives promising fusion results and it can be used to produce the high-resolution remotesensing images required for navigation information infrastructures.展开更多
In the experiment of combined navigation filtering using wavelet neural network, the initial parameters of the network have the influence of randomness on network convergence and navigation accuracy. A combined naviga...In the experiment of combined navigation filtering using wavelet neural network, the initial parameters of the network have the influence of randomness on network convergence and navigation accuracy. A combined navigation filtering method based on wavelet neural network optimized by mind evolution algorithm is proposed. Firstly, the efficient global search ability of the mind evolution algorithm was used to quickly and accurately obtain the initial parameters of the appropriate wavelet neural network, and then the optimized wavelet neural network was applied to directly predict the position and velocity error data. This method is different from the traditional filtering method, while avoiding the drawbacks of the neural network. The simulation experiments with wavelet neural network and GA-wavelet network were carried out. The results show that the proposed method can effectively improve the accuracy of the integrated navigation system and provide a feasible path for combined navigation filtering.展开更多
基金National Key R&D Program of China(No.2021YFB2501102)。
文摘Global Navigation Satellite System(GNSS)can provide all-weather,all-time,high-precision positioning,navigation and timing services,which plays an important role in national security,national economy,public life and other aspects.However,in environments with limited satellite signals such as urban canyons,tunnels,and indoor spaces,it is difficult to provide accurate and reliable positioning services only by satellite navigation.Multi-source sensor integrated navigation can effectively overcome the limitations of single-sensor navigation through the fusion of different types of sensor data such as Inertial Measurement Unit(IMU),vision sensor,and LiDAR,and provide more accurate,stable and robust navigation information in complex environments.We summarizes the research status of multi-source sensor integrated navigation technology,and focuses on the representative innovations and applications of integrated navigation and positioning technology by major domestic scientific research institutions in China during 2019—2023.
文摘This paper presents a new information fusion filter in integrated navigation. The method can improve the fault-tolerant performance and make well fault detection, isolation and reconfiguration of the integrated navigation system exist. Based on three sensors'(strapdown system, GPS receiver, Doppler radar) information fusion, a fault-tolerant navigation system is designed with this information fusion filter and two-ellipsoid overlap test. Simulation results show that the design is efficient with the soft-failure of gyro, accelerator, GPS receiver and Doppler radar.
基金supported by the Aviation Science Foundation(20070852009)
文摘An effective autonomous navigation system for the integration of star sensor,infrared horizon sensor,magnetometer,radar altimeter and ultraviolet sensor is developed.The requirements of the integrated navigation system manager make optimum use of the various navigation sensors and allow rapid fault detection,isolation and recovery.The normal full fusion feedback method of federated unscented Kalman filter(UKF) cannot meet the needs of it.So a no-reset feedback federated Kalman filter architecture is developed and used in the autonomous navigation system.The minimal skew sigma points are chosen to improve the calculation speed.Simulation results are presented to demonstrate the advantages of the algorithm.These advantages include improved failure detection and correction,improved computational efficiency,and reliability.Additionally,its' accuracy is higher than that of the full fusion feedback method.
文摘The interest for land navigation has increased for the recent years. With the advent of the Global Position System (GPS) we have now the ability to determine the absolute position anywhere on the globe. The problem is that the GPS systems work well only in open environments with no overhead obstructions and they are subject to large unavoidable errors when the reception from some of the satellites are blocked. This occurs frequently in urban environments, forests and tunnels. GPS systems require at least four “visible” satellites to maintain a good position fix. In many situations in which higher level of accuracy is required, the navigation cannot be achieved by GPS alone. This paper discusses the design of a reliable multisensor fusion algorithm using GPS and Inertial Navigation System in order to decrease the implementation cost of such systems on land vehicles. The major contribution of this paper is in the definition of the possible developments and research axes in land navigation.
基金supported in part by the Guangxi Power Grid Company’s 2023 Science and Technol-ogy Innovation Project(No.GXKJXM20230169)。
文摘With the development of unmanned driving technology,intelligent robots and drones,high-precision localization,navigation and state estimation technologies have also made great progress.Traditional global navigation satellite system/inertial navigation system(GNSS/INS)integrated navigation systems can provide high-precision navigation information continuously.However,when this system is applied to indoor or GNSS-denied environments,such as outdoor substations with strong electromagnetic interference and complex dense spaces,it is often unable to obtain high-precision GNSS positioning data.The positioning and orientation errors will diverge and accumulate rapidly,which cannot meet the high-precision localization requirements in large-scale and long-distance navigation scenarios.This paper proposes a method of high-precision state estimation with fusion of GNSS/INS/Vision using a nonlinear optimizer factor graph optimization as the basis for multi-source optimization.Through the collected experimental data and simulation results,this system shows good performance in the indoor environment and the environment with partial GNSS signal loss.
基金Supported by the National Natural Science Foundation for Outstanding Youth(61422102)Special Fund for Basic Research on Scientific Instruments of the National Natural Science Foundation of China(61127004)
文摘Inertial/gravity matching integrated navigation system can effectively improve the longendurance navigation ability of underwater vehicles.Through the analysis of the matching process,the problem of unequal-interval in matching trajectory is addressed by an unequal-interval data fusion algorithm which is based on the unequal-interval characteristics analysis of the matching trajectory.Compared with previously available methods,the proposed algorithm improves the location precision.In conclusion,simulations of the integrated navigation system demonstrated the effectiveness and superiority of the proposed algorithm.
文摘<strong>Introduction:</strong> Sonography is the most universally used imaging technique for planning and performing thermal ablation in Hepatocellular carcinoma patients due to its efficiency and safety. However, the presence of HCC nodules that are hardly visible on traditional sonography is a major drawback to its use during thermal ablation. Real-time image fusion (fusion imaging) or real-time virtual sonography is a new technology that has been developed. <strong>Aim: </strong>To determine the value of fusion/navigation guided percutaneous thermal ablation in the management of hepatocellular carcinoma that has poor conspicuity at conventional sonography. <strong>Subjects and Methods:</strong> This study included 70 HCC patients (BCLC A and B). Percutaneous radiofrequency ablation was done via real-time image fusion for 14 patients with poorly visible HCC nodules (study group), while Percutaneous radiofrequency ablation was done via traditional sonography for 56 patients with HCC nodules (control group). <strong>Results:</strong> The median time to reach the tumor was significantly shorter by using fusion navigation technique (<strong><em>P</em> = 0.034)</strong>. By using fusion navigation technique 92% of the lesions were completely ablated while 55% only were completely ablated by using ultrasonography (<strong><em>P</em> = 0.014</strong>). One year after the procedure , by using fusion navigation technique 92% of the patients had complete response and only 55% of the patients had complete response by using conventional ultrasonography (<strong><em>P</em></strong><strong> = 0.011</strong>). The survival distributions for both interventions were statistically significantly different, χ<sup>2</sup> = 10.12, <strong><em>P </em>= 0.001</strong>. <strong>Conclusion:</strong> Fusion imaging-guided percutaneous RFA is a reasonable and efficient treatment of patients with HCC undetectable by traditional ultrasonography.
文摘On the basis of the basic principles of weighted fusion, Kalman filtering and BP neural networks, the basic principles of information fusion methods used in integrated navigation systems are expounded. Through the analysis of the basic principles, the as-sociation of information fusion methods commonly used in integrated navigation systems and information failure modes is obtained: the information fault mode of weighted fusion method The model is closely related to the specific weight allocation method, which depends on the fault mode of the sensor or sub-system in which the weight is dominant;the information fault mode of the Kalman filtering information fusion method is a continuous mutation fault corresponding to the nonlinear time interval of the system;the in-formation fault mode of the BP neural network method is gradual with time. The information failure mode of the BP neural network method is a slowly varying fault that gradually accumulates over time. Starting from the complexity associated with the information fusion method and the information failure mode, it is pointed out that in order to systematically express the relationship between the information fusion method and the information failure mode, further research can be carried out.
基金the the National Key R&D Program of China(No.2018YFB1004901)the Independent Innovation Team Project of Jinan City(No.2019GXRC013).
文摘At present,most experimental teaching systems lack guidance of an operator,and thus users often do not know what to do during an experiment.The user load is therefore increased,and the learning efficiency of the students is decreased.To solve the problem of insufficient system interactivity and guidance,an experimental navigation system based on multi-mode fusion is proposed in this paper.The system first obtains user information by sensing the hardware devices,intelligently perceives the user intention and progress of the experiment according to the information acquired,and finally carries out a multi-modal intelligent navigation process for users.As an innovative aspect of this study,an intelligent multi-mode navigation system is used to guide users in conducting experiments,thereby reducing the user load and enabling the users to effectively complete their experiments.The results prove that this system can guide users in completing their experiments,and can effectively reduce the user load during the interaction process and improve the efficiency.
文摘In this paper, the multisensor data fusion technique of a fault tolerant integrated navigation system is discussed. A neural approach for data fusion is proposed for multisensor integrated systems. The simulation results show that this neural approach for data fusion is feasible.
基金supported by the National Natural Science Foundationof China (60902055)
文摘In order to take full advantage of federated filter in fault-tolerant design of integrated navigation system, the limitation of fault detection algorithm for gradual changing fault detection and the poor fault tolerance of global optimal fusion algorithm are the key problems to deal with. Based on theoretical analysis of the influencing factors of federated filtering fault tolerance, global fault-tolerant fusion algorithm and information sharing algorithm are proposed based on fuzzy assessment. It achieves intelligent fault-tolerant structure with two-stage and feedback, including real-time fault detection in sub-filters, and fault-tolerant fusion and information sharing in main filter. The simulation results demonstrate that the algorithm can effectively improve fault-tolerant ability and ensure relatively high positioning precision of integrated navigation system when a subsystem having gradual changing fault.
文摘For the underwater integrated navigation system, information fusion is an important technology. This paper introduces the Kalman filter as the most useful information fusion technology, and then gives a summary of the Kalman filter applied in underwater integrated navigation system at present, and points out the further research directions in this field.
基金Project supported by the National Outstanding Youth Science Foundation ( No.49825107) and the Natural Science Foundation ( No.40244002 No.40174009) .
文摘An integrated navlgation based on the kinematic or dynamic state model and the raw measurements has the advantages of high redundancy, high reliability, as well as high ability of fault tolerance and simplicity in calculation. In order to control the influences of measurements outliers and the kinematic model errors on the integrated navigation results, a robust estimation method and an adaptive data fusion method are applied. An integrated navigation example using simulated data is performed and analyzed.
文摘This paper introduces the image fusion approach of multi-resolutionanalysis-based intensity modulation (MRAIM) to produce the high-resolution multi-spectral imagesfrom high-resolution panchromatic image and low-resolution multi-spectral images for navigationinformation infrastructure. The mathematical model of image fusion is derived according to theprinciple of remote sensing image formation. It shows that the pixel values of a high-resolutionmulti-spectral images are determined by the pixel values of the approximation of a high-resolutionpanchromatic image at the resolution level of low-resolution multi-spectral images, and in the pixelvalae computation the M-band wavelet theory and the a trous algorithm are then used. In order toevaluate the MRAIM approach, an experiment has been carried out on the basis of the IKONOS 1 mpanchromatic image and 4 m multi-spectral images. The result demonstrates that MRAIM image fusionapproach gives promising fusion results and it can be used to produce the high-resolution remotesensing images required for navigation information infrastructures.
文摘In the experiment of combined navigation filtering using wavelet neural network, the initial parameters of the network have the influence of randomness on network convergence and navigation accuracy. A combined navigation filtering method based on wavelet neural network optimized by mind evolution algorithm is proposed. Firstly, the efficient global search ability of the mind evolution algorithm was used to quickly and accurately obtain the initial parameters of the appropriate wavelet neural network, and then the optimized wavelet neural network was applied to directly predict the position and velocity error data. This method is different from the traditional filtering method, while avoiding the drawbacks of the neural network. The simulation experiments with wavelet neural network and GA-wavelet network were carried out. The results show that the proposed method can effectively improve the accuracy of the integrated navigation system and provide a feasible path for combined navigation filtering.