A new nonlinear algorithm is proposed for strapdown inertial navigation system （SINS）/celestial navigation system （CNS）/global positioning system （GPS） integrated navigation systems. The algorithm employs a nonl...A new nonlinear algorithm is proposed for strapdown inertial navigation system （SINS）/celestial navigation system （CNS）/global positioning system （GPS） integrated navigation systems. The algorithm employs a nonlinear system error model which can be modified by unscented Kalman filter （UKF） to give predictions of local filters. And these predictions can be fused by the federated Kalman filter. In the system error model, the rotation vector is introduced to denote vehicle＇s attitude and has less variables than the quaternion. Also, the UKF method is simplified to estimate the system error model, which can both lead to less calculation and reduce algorithm implement time. In the information fusion section, a modified federated Kalman filter is proposed to solve the singular covariance problem. Specifically, the new algorithm is applied to maneuvering vehicles, and simulation results show that this algorithm is more accurate than the linear integrated navigation algorithm.展开更多
Fluorescence imaging in the second near-infrared window(NIR-II,900-1880 nm)offers high signalto-background ratio(SBR),enhanced definition,and superior tissue penetration,making it ideal for real-time surgical navigati...Fluorescence imaging in the second near-infrared window(NIR-II,900-1880 nm)offers high signalto-background ratio(SBR),enhanced definition,and superior tissue penetration,making it ideal for real-time surgical navigation.However,with single-channel imaging,surgeons must frequently switch between the surgi⁃cal field and the NIR-II images on the monitor.To address this,a coaxial dual-channel imaging system that com⁃bines visible light and 1100 nm longpass(1100LP)fluorescence was developed.The system features a custom⁃ized coaxial dual-channel lens with optimized distortion,achieving precise alignment with an error of less than±0.15 mm.Additionally,the shared focusing mechanism simplifies operation.Using FDA-approved indocya⁃nine green(ICG),the system was successfully applied in dual-channel guided rat lymph node excision,and blood supply assessment of reconstructed human flap.This approach enhances surgical precision,improves opera⁃tional efficiency,and provides a valuable reference for further clinical translation of NIR-II fluorescence imaging.展开更多
With the increase of international trade activities and the gradual melting of the polar ice cap,the importance of the Arctic route for marine transportation has been emphasized.Prediction of the polar navigation wind...With the increase of international trade activities and the gradual melting of the polar ice cap,the importance of the Arctic route for marine transportation has been emphasized.Prediction of the polar navigation window period is crucial for navigating in the Arctic route,which is of great significance to the selection of the route and the optimization of navigation.This paper introduces the establishment of a risk index system,determination of risk index weight,establishment of a risk evaluation model,and prediction algorithm for the window period.In addition,data sources of both environmental factors and ship factors are introducted,and their shortcomings are analyzed,followed by introduction of various methods involved in window prediction and analysis of their advantages and disadvantages.The quantitative risk evaluation and window period algorithm can provide a reference for the research of polar navigation window period prediction.展开更多
This paper presents a quadcopter system for naviga-tion in outdoor urban environments.The main contributions include the hardware design,the establishment of global occu-pancy grid maps based on millimeter-wave radars...This paper presents a quadcopter system for naviga-tion in outdoor urban environments.The main contributions include the hardware design,the establishment of global occu-pancy grid maps based on millimeter-wave radars,the trajec-tory planning scheme based on optimal virtual tube methods,and the controller structure based on dynamics.The proposed system focuses on utilizing a compact and lightweight quadro-tor with sensors to achieve navigation that conforms to the direction of urban roads with high computational efficiency and safety.Our work is an application of millimeter-wave radars and virtual tube planning for obstacle avoidance in navigation.The validness and effectiveness of the proposed system are verified by experiments.展开更多
Visual inertial odometry(VIO)problems have been extensively investigated in recent years.Existing VIO methods usually consider the localization or navigation issues of robots or autonomous vehicles in relatively small...Visual inertial odometry(VIO)problems have been extensively investigated in recent years.Existing VIO methods usually consider the localization or navigation issues of robots or autonomous vehicles in relatively small areas.This paper considers the problem of vision-aided inertial navigation(VIN)for aircrafts equipped with a strapdown inertial navigation system(SINS)and a downward-viewing camera.This is different from the traditional VIO problems in a larger working area with more precise inertial sensors.The goal is to utilize visual information to aid SINS to improve the navigation performance.In the multistate constraint Kalman filter(MSCKF)framework,we introduce an anchor frame to construct necessary models and derive corresponding Jacobians to implement a VIN filter to directly update the position in the Earth-centered Earth-fixed(ECEF)frame and the velocity and attitude in the local level frame by feature measurements.Due to its filtering-based property,the proposed method is naturally low computational demanding and is suitable for applications with high real-time requirements.Simulation and real-world data experiments demonstrate that the proposed method can considerably improve the navigation performance relative to the SINS.展开更多
The autonomous "celestial navigation scheme" for deep space probe departing from the earth and the autonomous "optical navigation scheme" for encountering object celestial body are presented. Then,...The autonomous "celestial navigation scheme" for deep space probe departing from the earth and the autonomous "optical navigation scheme" for encountering object celestial body are presented. Then, aiming at the conditions that large initial estimation errors and non-Gaussian distribution of state or measurement errors may exist in orbit determination process of the two phases, UPF (unscented particle filter) is introduced into the navigation schemes. By tackling nonlinear and non-Gaussian problems, UPF overcomes the accuracy influence brought by the traditional EKF (extended Kalman filter), UKF (unscented Kalman filter), and PF (particle filter) schemes in approximate treatment to nonlinear and non-Gaussian state model and measurement model. The numerical simulations demonstrate the feasibility and higher accuracy of the UPF navigation scheme.展开更多
For the improvement of accuracy and better fault-tolerant performance,a global position system(GPS)/vision navigation(VISNAV)integrated relative navigation and attitude determination approach is presented for ultra-cl...For the improvement of accuracy and better fault-tolerant performance,a global position system(GPS)/vision navigation(VISNAV)integrated relative navigation and attitude determination approach is presented for ultra-close spacecraft formation flying.Onboard GPS and VISNAV system are adopted and a federal Kalman filter architecture is used for the total navigation system design.Simulation results indicate that the integrated system can provide a total improvement of relative navigation and attitude estimation performance in accuracy and fault-tolerance.展开更多
A marine INS/GPS adaptive navigation system is presented. GPS with two antenna providing vessel＇ s altitude is selected as the auxiliary system fusing with INS to improve the performance of the hybrid system. The Kal...A marine INS/GPS adaptive navigation system is presented. GPS with two antenna providing vessel＇ s altitude is selected as the auxiliary system fusing with INS to improve the performance of the hybrid system. The Kalman filter is the most frequently used algorithm in the integrated navigation system, which is capable of estimating INS errors online based on the measured errors between INS and GPS. The standard Kalman filter （SKF） assumes that the statistics of the noise on each sensor are given. As long as the noise distributions do not change, the Kalman filter will give the optimal estimation. However GPS receiver will be disturbed easily and thus temporally changing measurement noise will join into the outputs of GPS, which will lead to performance degradation of the Kalman filter. Many researchers introduce fuzzy logic control method into innovation-based adaptive estimation adaptive Kalman filtering （IAE-AKF） algorithm, and accordingly propose various adaptive Kalman filters. However how to design the fuzzy logic controller is a very complicated problem still without a convincing solution. A novel IAE-AKF is proposed herein, which is based on the maximum likelihood criterion for the proper computation of the filter innovation covariance and hence of the filter gain. The approach is direct and simple without having to establish fuzzy inference rules. After having deduced the proposed IAEAKF algorithm theoretically in detail, the approach is tested by the simulation based on the system error model of the developed INS/GPS integrated marine navigation system. Simulation results show that the adaptive Kalman filter outperforms the SKF with higher accuracy, robustness and less computation. It is demonstra- ted that this proposed approach is a valid solution for the unknown changing measurement noise exited in the Kalman filter.展开更多
To improve the accuracy of strapdown inertial navigation system(SINS) for long term applications,the rotation technique is employed to modulate the errors of the inertial sensors into periodically varied signals,and,a...To improve the accuracy of strapdown inertial navigation system(SINS) for long term applications,the rotation technique is employed to modulate the errors of the inertial sensors into periodically varied signals,and,as a result,to suppress the divergence of SINS errors.However,the errors of rotation platform will be introduced into SINS and might affect the final navigation accuracy.Considering the disadvantages of the conventional navigation computation scheme,an improved computation scheme of the SINS using rotation technique is proposed which can reduce the effects of the rotation platform errors.And,the error characteristics of the SINS with this navigation computation scheme are analyzed.Theoretical analysis,simulations and real test results show that the proposed navigation computation scheme outperforms the conventional navigation computation scheme,meanwhile reduces the requirement to the measurement accuracy of rotation angles.展开更多
In order to improve the autonomous navigation capability of satellite,a pulsar/CNS(celestial navigation system)integrated navigation method based on federated unscented Kalman filter(UKF)is proposed.The celestial navi...In order to improve the autonomous navigation capability of satellite,a pulsar/CNS(celestial navigation system)integrated navigation method based on federated unscented Kalman filter(UKF)is proposed.The celestial navigation is a mature and stable navigation method.However,its position determination performance is not satisfied due to the low accuracy of horizon sensor.Single pulsar navigation is a new navigation method,which can provide highly accurate range measurements.The major drawback of single pulsar navigation is that the system is completely unobservable.As two methods are complementary to each other,the federated UKF is used here for fusing the navigation data from single pulsar navigation and CNS.Compared to the traditional celestial navigation method and single pulsar navigation,the integrated navigation method can provide better navigation performance.The simulation results demonstrate the feasibility and effectiveness of the navigation method.展开更多
This paper presents a bio-inspired geomagnetic navigation method for autonomous underwater vehicle(AUV) without using any a priori geomagnetic information. Firstly, the multi-objective search problem is raised. Second...This paper presents a bio-inspired geomagnetic navigation method for autonomous underwater vehicle(AUV) without using any a priori geomagnetic information. Firstly, the multi-objective search problem is raised. Secondly, the geomagnetic navigation model is established by constructing a cost function. Then, by taking into consideration the biological magneto-taxis movement behavior for the geomagnetic environment stimulus, the multiobjective evolutionary search algorithm is derived to describe the search process. Finally, compared to the state-of-the-art, the proposed method presents better robustness. The simulation results demonstrate the reliability and feasibility of the proposed method.展开更多
The dual-axis rotational inertial navigation system(INS)with dithered ring laser gyro(DRLG)is widely used in high precision navigation.The major inertial sensor errors such as drift errors of gyro and accelerometer ca...The dual-axis rotational inertial navigation system(INS)with dithered ring laser gyro(DRLG)is widely used in high precision navigation.The major inertial sensor errors such as drift errors of gyro and accelerometer can be averaged out,but the G-sensitive drifts of laser gyro cannot be averaged out by indexing.A 16-position rotational simulation experiment proves the G-sensitive drift will affect the long-term navigation error for the rotational INS quantitatively.The vibration coupling and asymmetric structure of the DRLG are the main errors.A new dithered mechanism and optimized DRLG is designed.The validity and efficiency of the optimized design are conformed by 1 g sinusoidal vibration experiments.An optimized inertial measurement unit(IMU)is formulated and measured experimentally.Laboratory and vehicle experimental results show that the divergence speed of longitude errors can be effectively slowed down in the optimized IMU.In long term independent navigation,the position accuracy of dual-axis rotational INS is improved close to 50%,and the G-sensitive drifts of laser gyro in the optimized IMU are less than 0.0002°/h.These results have important theoretical significance and practical value for improving the structural dynamic characteristics of DRLG INS,especially the highprecision inertial system.展开更多
With the development of positioning technology,loca-tion services are constantly in demand by people.As a primary location service pedestrian navigation has two main approaches based on radio and inertial navigation.T...With the development of positioning technology,loca-tion services are constantly in demand by people.As a primary location service pedestrian navigation has two main approaches based on radio and inertial navigation.The pedestrian naviga-tion based on radio is subject to environmental occlusion lead-ing to the degradation of positioning accuracy.The pedestrian navigation based on micro-electro-mechanical system inertial measurement unit(MIMU)is less susceptible to environmental interference,but its errors dissipate over time.In this paper,a chest card pedestrian navigation improvement method based on complementary correction is proposed in order to suppress the error divergence of inertial navigation methods.To suppress atti-tude errors,optimal feedback coefficients are established by pedestrian motion characteristics.To extend navigation time and improve positioning accuracy,the step length in subsequent movements is compensated by the first step length.The experi-mental results show that the positioning accuracy of the pro-posed method is improved by more than 47%and 44%com-pared with the pure inertia-based method combined with step compensation and the traditional complementary filtering com-bined method with step compensation.The proposed method can effectively suppress the error dispersion and improve the positioning accuracy.展开更多
This paper presents the rigorous study of mobile robot navigation techniques used so far.The step by step investigations of classical and reactive approaches are made here to understand the development of path plannin...This paper presents the rigorous study of mobile robot navigation techniques used so far.The step by step investigations of classical and reactive approaches are made here to understand the development of path planning strategies in various environmental conditions and to identify research gap.The classical approaches such as cell decomposition(CD),roadmap approach(RA),artificial potential field(APF);reactive approaches such as genetic algorithm(GA),fuzzy logic(FL),neural network(NN),firefly algorithm(FA),particle swarm optimization(PSO),ant colony optimization(ACO),bacterial foraging optimization(BFO),artificial bee colony(ABC),cuckoo search(CS),shuffled frog leaping algorithm(SFLA)and other miscellaneous algorithms(OMA)are considered for study.The navigation over static and dynamic condition is analyzed(for single and multiple robot systems)and it has been observed that the reactive approaches are more robust and perform well in all terrain when compared to classical approaches.It is also observed that the reactive approaches are used to improve the performance of the classical approaches as a hybrid algorithm.Hence,reactive approaches are more popular and widely used for path planning of mobile robot.The paper concludes with tabular data and charts comparing the frequency of individual navigational strategies which can be used for specific application in robotics.展开更多
In view of the failure of GNSS signals,this paper proposes an INS/GNSS integrated navigation method based on the recurrent neural network(RNN).This proposed method utilizes the calculation principle of INS and the mem...In view of the failure of GNSS signals,this paper proposes an INS/GNSS integrated navigation method based on the recurrent neural network(RNN).This proposed method utilizes the calculation principle of INS and the memory function of the RNN to estimate the errors of the INS,thereby obtaining a continuous,reliable and high-precision navigation solution.The performance of the proposed method is firstly demonstrated using an INS/GNSS simulation environment.Subsequently,an experimental test on boat is also conducted to validate the performance of the method.The results show a promising application prospect for RNN in the field of positioning for INS/GNSS integrated navigation in the absence of GNSS signal,as it outperforms extreme learning machine(ELM)and EKF by approximately 30%and 60%,respectively.展开更多
Strapdown inertial navigation system(SINS)/celestial navigation system(CNS)integrated navigation is widely used to achieve long-time and high-precision autonomous navigation for aircraft.In general,SINS/CNS integrated...Strapdown inertial navigation system(SINS)/celestial navigation system(CNS)integrated navigation is widely used to achieve long-time and high-precision autonomous navigation for aircraft.In general,SINS/CNS integrated navigation can be divided into two integrated modes:loosely coupled integrated navigation and tightly coupled integrated navigation.Because the loosely coupled SINS/CNS integrated system is only available in the condition of at least three stars,the latter one is becoming a research hotspot.One major challenge of SINS/CNS integrated navigation is obtaining a high-precision horizon reference.To solve this problem,an innovative tightly coupled rotational SINS/CNS integrated navigation method is proposed.In this method,the rotational SINS error equation in the navigation frame is used as the state model,and the starlight vector and star altitude are used as measurements.Semi-physical simulations are conducted to test the performance of this integrated method.Results show that this tightly coupled rotational SINS/CNS method has the best navigation accuracy compared with SINS,rotational SINS,and traditional tightly coupled SINS/CNS integrated navigation method.展开更多
With the increasing use of humanoid robots in several sectors of industrial automation and manufacturing, navigation and path planning of humanoids has emerged as one of the most promising area of research. In this pa...With the increasing use of humanoid robots in several sectors of industrial automation and manufacturing, navigation and path planning of humanoids has emerged as one of the most promising area of research. In this paper, a navigational controller has been developed for a humanoid by using fuzzy logic as an intelligent algorithm for avoiding the obstacles present in the environment and reach the desired target position safely. Here, the controller has been designed by careful consideration of the navigational parameters by the help of fuzzy rules. The sensory information regarding obstacle distances and bearing angle towards the target are considered as inputs to the controller and necessary velocities for avoiding the obstacles are obtained as outputs. The working of the controller has been tested on a NAO humanoid robot in V-REP simulation platform. To validate the simulation results, an experimental platform has been designed under laboratory conditions, and experimental analysis has been performed.Finally, the results obtained from both the environments are compared against each other with a good agreement between them.展开更多
Aiming at the problem that the traditional Unscented Kalman Filtering(UKF) algorithm can't solve the problem that the measurement covariance matrix is unknown and the measured value contains outliers,this paper pr...Aiming at the problem that the traditional Unscented Kalman Filtering(UKF) algorithm can't solve the problem that the measurement covariance matrix is unknown and the measured value contains outliers,this paper proposes a robust adaptive UKF algorithm based on Support Vector Regression(SVR).The algorithm combines the advantages of support vector regression with small samples,nonlinear learning ability and online estimation capability of adaptive algorithm based on innovation.Firstly,the SVR model is trained by using the innovation in the sliding window,and the new innovation is monitored.If the deviation between the estimated innovation and the measured innovation exceeds a given threshold,then measured innovation will be replaced by the predicted innovation,and then the processed innovation is used to calculate the measurement noise covariance matrix using the adaptive estimation algorithm.Simulation experiments and measured data experiments show that SVRUKF is significantly better than the traditional UKF,robust UKF and adaptive UKF algorithms for the case where the covariance matrix is unknown and the measured values have outliers.展开更多
To improve the reliability and accuracy of the global po- sitioning system （GPS）/micro electromechanical system （MEMS）- inertial navigation system （INS） integrated navigation system, this paper proposes two diff...To improve the reliability and accuracy of the global po- sitioning system （GPS）/micro electromechanical system （MEMS）- inertial navigation system （INS） integrated navigation system, this paper proposes two different methods. Based on wavelet threshold denoising and functional coefficient autoregressive （FAR） model- ing, a combined data processing method is presented for MEMS inertial sensor, and GPS attitude information is also introduced to improve the estimation accuracy of MEMS inertial sensor errors. Then the positioning accuracy during GPS signal short outage is enhanced. To improve the positioning accuracy when a GPS signal is blocked for long time and solve the problem of the tra- ditional adaptive neuro-fuzzy inference system （ANFIS） method with poor dynamic adaptation and large calculation amount, a self-constructive ANFIS （SCANFIS） combined with the extended Kalman filter （EKF） is proposed for MEMS-INS errors modeling and predicting. Experimental road test results validate the effi- ciency of the proposed methods.展开更多
A new proportional navigation(PN) guidance law,called combined proportional navigation(CPN),is proposed.The guidance law is designed to intercept high-speed targets,which is a common case for ballistic targets.The ran...A new proportional navigation(PN) guidance law,called combined proportional navigation(CPN),is proposed.The guidance law is designed to intercept high-speed targets,which is a common case for ballistic targets.The range of target-to-interceptor speed ratio during target interception is derived when guidance laws are applied in high-speed targets interception,and the effectiveness of negative navigation ratio in the PN-based guidance law is proven analytically in some lemmas.Based on the lemmas,the lateral acceleration command of CPN is defined,and the solution to the appearance of singularity in time-varying navigation ratio is given.The simulation results show that CPN can determine headon engagement(as PN) or tail-chase engagement(as RPN) through initial path angle compared with PN and retro proportional navigation(RPN),and can adjust the value of navigation ratio for head-on engagement or tail-chase engagement.Therefore,the capture region of CPN is larger than that of other guidance laws using PN-based methods.展开更多
基金supported by the National Natural Science Foundation of China (60535010)
文摘A new nonlinear algorithm is proposed for strapdown inertial navigation system （SINS）/celestial navigation system （CNS）/global positioning system （GPS） integrated navigation systems. The algorithm employs a nonlinear system error model which can be modified by unscented Kalman filter （UKF） to give predictions of local filters. And these predictions can be fused by the federated Kalman filter. In the system error model, the rotation vector is introduced to denote vehicle＇s attitude and has less variables than the quaternion. Also, the UKF method is simplified to estimate the system error model, which can both lead to less calculation and reduce algorithm implement time. In the information fusion section, a modified federated Kalman filter is proposed to solve the singular covariance problem. Specifically, the new algorithm is applied to maneuvering vehicles, and simulation results show that this algorithm is more accurate than the linear integrated navigation algorithm.
基金Supported by the National Natural Science Foundation of China(U23A20487)the National Key R&D Program of China(2022YFB3206000)+1 种基金Dr.Li Dak Sum&Yip Yio Chin Development Fund for Regenerative Medicine,Zhejiang Universitythe National Natural Science Foundation of China(61975172).
文摘Fluorescence imaging in the second near-infrared window(NIR-II,900-1880 nm)offers high signalto-background ratio(SBR),enhanced definition,and superior tissue penetration,making it ideal for real-time surgical navigation.However,with single-channel imaging,surgeons must frequently switch between the surgi⁃cal field and the NIR-II images on the monitor.To address this,a coaxial dual-channel imaging system that com⁃bines visible light and 1100 nm longpass(1100LP)fluorescence was developed.The system features a custom⁃ized coaxial dual-channel lens with optimized distortion,achieving precise alignment with an error of less than±0.15 mm.Additionally,the shared focusing mechanism simplifies operation.Using FDA-approved indocya⁃nine green(ICG),the system was successfully applied in dual-channel guided rat lymph node excision,and blood supply assessment of reconstructed human flap.This approach enhances surgical precision,improves opera⁃tional efficiency,and provides a valuable reference for further clinical translation of NIR-II fluorescence imaging.
文摘With the increase of international trade activities and the gradual melting of the polar ice cap,the importance of the Arctic route for marine transportation has been emphasized.Prediction of the polar navigation window period is crucial for navigating in the Arctic route,which is of great significance to the selection of the route and the optimization of navigation.This paper introduces the establishment of a risk index system,determination of risk index weight,establishment of a risk evaluation model,and prediction algorithm for the window period.In addition,data sources of both environmental factors and ship factors are introducted,and their shortcomings are analyzed,followed by introduction of various methods involved in window prediction and analysis of their advantages and disadvantages.The quantitative risk evaluation and window period algorithm can provide a reference for the research of polar navigation window period prediction.
基金supported by the National Key Research and Development Program of China(2022YFA1004703)the National Natural Science Foundation of China(62088101).
文摘This paper presents a quadcopter system for naviga-tion in outdoor urban environments.The main contributions include the hardware design,the establishment of global occu-pancy grid maps based on millimeter-wave radars,the trajec-tory planning scheme based on optimal virtual tube methods,and the controller structure based on dynamics.The proposed system focuses on utilizing a compact and lightweight quadro-tor with sensors to achieve navigation that conforms to the direction of urban roads with high computational efficiency and safety.Our work is an application of millimeter-wave radars and virtual tube planning for obstacle avoidance in navigation.The validness and effectiveness of the proposed system are verified by experiments.
基金supported by the National Natural Science Foundation of China(61773306).
文摘Visual inertial odometry(VIO)problems have been extensively investigated in recent years.Existing VIO methods usually consider the localization or navigation issues of robots or autonomous vehicles in relatively small areas.This paper considers the problem of vision-aided inertial navigation(VIN)for aircrafts equipped with a strapdown inertial navigation system(SINS)and a downward-viewing camera.This is different from the traditional VIO problems in a larger working area with more precise inertial sensors.The goal is to utilize visual information to aid SINS to improve the navigation performance.In the multistate constraint Kalman filter(MSCKF)framework,we introduce an anchor frame to construct necessary models and derive corresponding Jacobians to implement a VIN filter to directly update the position in the Earth-centered Earth-fixed(ECEF)frame and the velocity and attitude in the local level frame by feature measurements.Due to its filtering-based property,the proposed method is naturally low computational demanding and is suitable for applications with high real-time requirements.Simulation and real-world data experiments demonstrate that the proposed method can considerably improve the navigation performance relative to the SINS.
基金the National "863" High Technology Development Project of China (2005AA735080).
文摘The autonomous "celestial navigation scheme" for deep space probe departing from the earth and the autonomous "optical navigation scheme" for encountering object celestial body are presented. Then, aiming at the conditions that large initial estimation errors and non-Gaussian distribution of state or measurement errors may exist in orbit determination process of the two phases, UPF (unscented particle filter) is introduced into the navigation schemes. By tackling nonlinear and non-Gaussian problems, UPF overcomes the accuracy influence brought by the traditional EKF (extended Kalman filter), UKF (unscented Kalman filter), and PF (particle filter) schemes in approximate treatment to nonlinear and non-Gaussian state model and measurement model. The numerical simulations demonstrate the feasibility and higher accuracy of the UPF navigation scheme.
文摘For the improvement of accuracy and better fault-tolerant performance,a global position system(GPS)/vision navigation(VISNAV)integrated relative navigation and attitude determination approach is presented for ultra-close spacecraft formation flying.Onboard GPS and VISNAV system are adopted and a federal Kalman filter architecture is used for the total navigation system design.Simulation results indicate that the integrated system can provide a total improvement of relative navigation and attitude estimation performance in accuracy and fault-tolerance.
基金This project was supported by the National Natural Science Foundation of China (40125013 &40376011)
文摘A marine INS/GPS adaptive navigation system is presented. GPS with two antenna providing vessel＇ s altitude is selected as the auxiliary system fusing with INS to improve the performance of the hybrid system. The Kalman filter is the most frequently used algorithm in the integrated navigation system, which is capable of estimating INS errors online based on the measured errors between INS and GPS. The standard Kalman filter （SKF） assumes that the statistics of the noise on each sensor are given. As long as the noise distributions do not change, the Kalman filter will give the optimal estimation. However GPS receiver will be disturbed easily and thus temporally changing measurement noise will join into the outputs of GPS, which will lead to performance degradation of the Kalman filter. Many researchers introduce fuzzy logic control method into innovation-based adaptive estimation adaptive Kalman filtering （IAE-AKF） algorithm, and accordingly propose various adaptive Kalman filters. However how to design the fuzzy logic controller is a very complicated problem still without a convincing solution. A novel IAE-AKF is proposed herein, which is based on the maximum likelihood criterion for the proper computation of the filter innovation covariance and hence of the filter gain. The approach is direct and simple without having to establish fuzzy inference rules. After having deduced the proposed IAEAKF algorithm theoretically in detail, the approach is tested by the simulation based on the system error model of the developed INS/GPS integrated marine navigation system. Simulation results show that the adaptive Kalman filter outperforms the SKF with higher accuracy, robustness and less computation. It is demonstra- ted that this proposed approach is a valid solution for the unknown changing measurement noise exited in the Kalman filter.
基金Project(60604011) supported by the National Natural Science Foundation of China
文摘To improve the accuracy of strapdown inertial navigation system(SINS) for long term applications,the rotation technique is employed to modulate the errors of the inertial sensors into periodically varied signals,and,as a result,to suppress the divergence of SINS errors.However,the errors of rotation platform will be introduced into SINS and might affect the final navigation accuracy.Considering the disadvantages of the conventional navigation computation scheme,an improved computation scheme of the SINS using rotation technique is proposed which can reduce the effects of the rotation platform errors.And,the error characteristics of the SINS with this navigation computation scheme are analyzed.Theoretical analysis,simulations and real test results show that the proposed navigation computation scheme outperforms the conventional navigation computation scheme,meanwhile reduces the requirement to the measurement accuracy of rotation angles.
基金supported by the National High Technology Research and Development Program of China(2006AAJ109)Aviation Science Fund(20070818001)
文摘In order to improve the autonomous navigation capability of satellite,a pulsar/CNS(celestial navigation system)integrated navigation method based on federated unscented Kalman filter(UKF)is proposed.The celestial navigation is a mature and stable navigation method.However,its position determination performance is not satisfied due to the low accuracy of horizon sensor.Single pulsar navigation is a new navigation method,which can provide highly accurate range measurements.The major drawback of single pulsar navigation is that the system is completely unobservable.As two methods are complementary to each other,the federated UKF is used here for fusing the navigation data from single pulsar navigation and CNS.Compared to the traditional celestial navigation method and single pulsar navigation,the integrated navigation method can provide better navigation performance.The simulation results demonstrate the feasibility and effectiveness of the navigation method.
基金supported by the National Natural Science Foundation of China(5137917651179156)
文摘This paper presents a bio-inspired geomagnetic navigation method for autonomous underwater vehicle(AUV) without using any a priori geomagnetic information. Firstly, the multi-objective search problem is raised. Secondly, the geomagnetic navigation model is established by constructing a cost function. Then, by taking into consideration the biological magneto-taxis movement behavior for the geomagnetic environment stimulus, the multiobjective evolutionary search algorithm is derived to describe the search process. Finally, compared to the state-of-the-art, the proposed method presents better robustness. The simulation results demonstrate the reliability and feasibility of the proposed method.
基金supported by the National Natural Science Foundation of China(61503399).
文摘The dual-axis rotational inertial navigation system(INS)with dithered ring laser gyro(DRLG)is widely used in high precision navigation.The major inertial sensor errors such as drift errors of gyro and accelerometer can be averaged out,but the G-sensitive drifts of laser gyro cannot be averaged out by indexing.A 16-position rotational simulation experiment proves the G-sensitive drift will affect the long-term navigation error for the rotational INS quantitatively.The vibration coupling and asymmetric structure of the DRLG are the main errors.A new dithered mechanism and optimized DRLG is designed.The validity and efficiency of the optimized design are conformed by 1 g sinusoidal vibration experiments.An optimized inertial measurement unit(IMU)is formulated and measured experimentally.Laboratory and vehicle experimental results show that the divergence speed of longitude errors can be effectively slowed down in the optimized IMU.In long term independent navigation,the position accuracy of dual-axis rotational INS is improved close to 50%,and the G-sensitive drifts of laser gyro in the optimized IMU are less than 0.0002°/h.These results have important theoretical significance and practical value for improving the structural dynamic characteristics of DRLG INS,especially the highprecision inertial system.
文摘With the development of positioning technology,loca-tion services are constantly in demand by people.As a primary location service pedestrian navigation has two main approaches based on radio and inertial navigation.The pedestrian naviga-tion based on radio is subject to environmental occlusion lead-ing to the degradation of positioning accuracy.The pedestrian navigation based on micro-electro-mechanical system inertial measurement unit(MIMU)is less susceptible to environmental interference,but its errors dissipate over time.In this paper,a chest card pedestrian navigation improvement method based on complementary correction is proposed in order to suppress the error divergence of inertial navigation methods.To suppress atti-tude errors,optimal feedback coefficients are established by pedestrian motion characteristics.To extend navigation time and improve positioning accuracy,the step length in subsequent movements is compensated by the first step length.The experi-mental results show that the positioning accuracy of the pro-posed method is improved by more than 47%and 44%com-pared with the pure inertia-based method combined with step compensation and the traditional complementary filtering com-bined method with step compensation.The proposed method can effectively suppress the error dispersion and improve the positioning accuracy.
文摘This paper presents the rigorous study of mobile robot navigation techniques used so far.The step by step investigations of classical and reactive approaches are made here to understand the development of path planning strategies in various environmental conditions and to identify research gap.The classical approaches such as cell decomposition(CD),roadmap approach(RA),artificial potential field(APF);reactive approaches such as genetic algorithm(GA),fuzzy logic(FL),neural network(NN),firefly algorithm(FA),particle swarm optimization(PSO),ant colony optimization(ACO),bacterial foraging optimization(BFO),artificial bee colony(ABC),cuckoo search(CS),shuffled frog leaping algorithm(SFLA)and other miscellaneous algorithms(OMA)are considered for study.The navigation over static and dynamic condition is analyzed(for single and multiple robot systems)and it has been observed that the reactive approaches are more robust and perform well in all terrain when compared to classical approaches.It is also observed that the reactive approaches are used to improve the performance of the classical approaches as a hybrid algorithm.Hence,reactive approaches are more popular and widely used for path planning of mobile robot.The paper concludes with tabular data and charts comparing the frequency of individual navigational strategies which can be used for specific application in robotics.
基金supported in part by the National Natural Science Foundation of China(No.41876222)。
文摘In view of the failure of GNSS signals,this paper proposes an INS/GNSS integrated navigation method based on the recurrent neural network(RNN).This proposed method utilizes the calculation principle of INS and the memory function of the RNN to estimate the errors of the INS,thereby obtaining a continuous,reliable and high-precision navigation solution.The performance of the proposed method is firstly demonstrated using an INS/GNSS simulation environment.Subsequently,an experimental test on boat is also conducted to validate the performance of the method.The results show a promising application prospect for RNN in the field of positioning for INS/GNSS integrated navigation in the absence of GNSS signal,as it outperforms extreme learning machine(ELM)and EKF by approximately 30%and 60%,respectively.
基金supported by the National Natural Science Foundation of China(61722301)
文摘Strapdown inertial navigation system(SINS)/celestial navigation system(CNS)integrated navigation is widely used to achieve long-time and high-precision autonomous navigation for aircraft.In general,SINS/CNS integrated navigation can be divided into two integrated modes:loosely coupled integrated navigation and tightly coupled integrated navigation.Because the loosely coupled SINS/CNS integrated system is only available in the condition of at least three stars,the latter one is becoming a research hotspot.One major challenge of SINS/CNS integrated navigation is obtaining a high-precision horizon reference.To solve this problem,an innovative tightly coupled rotational SINS/CNS integrated navigation method is proposed.In this method,the rotational SINS error equation in the navigation frame is used as the state model,and the starlight vector and star altitude are used as measurements.Semi-physical simulations are conducted to test the performance of this integrated method.Results show that this tightly coupled rotational SINS/CNS method has the best navigation accuracy compared with SINS,rotational SINS,and traditional tightly coupled SINS/CNS integrated navigation method.
文摘With the increasing use of humanoid robots in several sectors of industrial automation and manufacturing, navigation and path planning of humanoids has emerged as one of the most promising area of research. In this paper, a navigational controller has been developed for a humanoid by using fuzzy logic as an intelligent algorithm for avoiding the obstacles present in the environment and reach the desired target position safely. Here, the controller has been designed by careful consideration of the navigational parameters by the help of fuzzy rules. The sensory information regarding obstacle distances and bearing angle towards the target are considered as inputs to the controller and necessary velocities for avoiding the obstacles are obtained as outputs. The working of the controller has been tested on a NAO humanoid robot in V-REP simulation platform. To validate the simulation results, an experimental platform has been designed under laboratory conditions, and experimental analysis has been performed.Finally, the results obtained from both the environments are compared against each other with a good agreement between them.
文摘Aiming at the problem that the traditional Unscented Kalman Filtering(UKF) algorithm can't solve the problem that the measurement covariance matrix is unknown and the measured value contains outliers,this paper proposes a robust adaptive UKF algorithm based on Support Vector Regression(SVR).The algorithm combines the advantages of support vector regression with small samples,nonlinear learning ability and online estimation capability of adaptive algorithm based on innovation.Firstly,the SVR model is trained by using the innovation in the sliding window,and the new innovation is monitored.If the deviation between the estimated innovation and the measured innovation exceeds a given threshold,then measured innovation will be replaced by the predicted innovation,and then the processed innovation is used to calculate the measurement noise covariance matrix using the adaptive estimation algorithm.Simulation experiments and measured data experiments show that SVRUKF is significantly better than the traditional UKF,robust UKF and adaptive UKF algorithms for the case where the covariance matrix is unknown and the measured values have outliers.
基金supported by the National Natural Science Foundation of China (60902055)
文摘To improve the reliability and accuracy of the global po- sitioning system （GPS）/micro electromechanical system （MEMS）- inertial navigation system （INS） integrated navigation system, this paper proposes two different methods. Based on wavelet threshold denoising and functional coefficient autoregressive （FAR） model- ing, a combined data processing method is presented for MEMS inertial sensor, and GPS attitude information is also introduced to improve the estimation accuracy of MEMS inertial sensor errors. Then the positioning accuracy during GPS signal short outage is enhanced. To improve the positioning accuracy when a GPS signal is blocked for long time and solve the problem of the tra- ditional adaptive neuro-fuzzy inference system （ANFIS） method with poor dynamic adaptation and large calculation amount, a self-constructive ANFIS （SCANFIS） combined with the extended Kalman filter （EKF） is proposed for MEMS-INS errors modeling and predicting. Experimental road test results validate the effi- ciency of the proposed methods.
文摘A new proportional navigation(PN) guidance law,called combined proportional navigation(CPN),is proposed.The guidance law is designed to intercept high-speed targets,which is a common case for ballistic targets.The range of target-to-interceptor speed ratio during target interception is derived when guidance laws are applied in high-speed targets interception,and the effectiveness of negative navigation ratio in the PN-based guidance law is proven analytically in some lemmas.Based on the lemmas,the lateral acceleration command of CPN is defined,and the solution to the appearance of singularity in time-varying navigation ratio is given.The simulation results show that CPN can determine headon engagement(as PN) or tail-chase engagement(as RPN) through initial path angle compared with PN and retro proportional navigation(RPN),and can adjust the value of navigation ratio for head-on engagement or tail-chase engagement.Therefore,the capture region of CPN is larger than that of other guidance laws using PN-based methods.
