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
This paper presents the design and ground verification for vision-based relative navigation systems of microsatellites,which offers a comprehensive hardware design solution and a robust experimental verification metho...This paper presents the design and ground verification for vision-based relative navigation systems of microsatellites,which offers a comprehensive hardware design solution and a robust experimental verification methodology for practical implementation of vision-based navigation technology on the microsatellite platform.Firstly,a low power consumption,light weight,and high performance vision-based relative navigation optical sensor is designed.Subsequently,a set of ground verification system is designed for the hardware-in-the-loop testing of the vision-based relative navigation systems.Finally,the designed vision-based relative navigation optical sensor and the proposed angles-only navigation algorithms are tested on the ground verification system.The results verify that the optical simulator after geometrical calibration can meet the requirements of the hardware-in-the-loop testing of vision-based relative navigation systems.Based on experimental results,the relative position accuracy of the angles-only navigation filter at terminal time is increased by 25.5%,and the relative speed accuracy is increased by 31.3% compared with those of optical simulator before geometrical calibration.展开更多
Endoscopic transnasal optic nerve decompression surgery plays a crucial role in minimal invasive treatment of complex traumatic optic neuropathy.However,a major challenge faced during the procedure is the inability to...Endoscopic transnasal optic nerve decompression surgery plays a crucial role in minimal invasive treatment of complex traumatic optic neuropathy.However,a major challenge faced during the procedure is the inability to visualize the optic nerve intraoperatively.To address this issue,an endoscopic image-based augmented reality surgical navigation system is developed in this study.The system aims to virtually fuse the optic nerve onto the endoscopic images,assisting surgeons in determining the optic nerve’s position and reducing surgical risks.First,a calibration algorithm based on a checkerboard grid of immobile points is proposed,building upon existing calibration methods.Additionally,to tackle accuracy issues associated with augmented reality technology,an optical navigation and visual fusion compensation algorithm is proposed to improve the intraoperative tracking accuracy.To evaluate the system’s performance,model experiments were meticulously designed and conducted.The results confirm the accuracy and stability of the proposed system,with an average tracking error of(0.99±0.46)mm.This outcome demonstrates the effectiveness of the proposed algorithm in improving the augmented reality surgical navigation system’s accuracy.Furthermore,the system successfully displays hidden optic nerves and other deep tissues,thus showcasing the promising potential for future applications in orbital and maxillofacial surgery.展开更多
The angle/range-based integrated navigation system is a favorable navigation solution for deep space explorers.However,the statistical characteristics of the measurement noise are time-varying,leading to inaccuracies ...The angle/range-based integrated navigation system is a favorable navigation solution for deep space explorers.However,the statistical characteristics of the measurement noise are time-varying,leading to inaccuracies in the derived measurement covariance even causing filter divergence.To reduce the gap between theoretical and actual covariances,some adaptive methods use empirically determined and unchanged forgetting factors to scale innovations within the sliding window.However,the constant weighting sequence cannot accurately adapt to the time-varying measurement noise in dynamic processes.Therefore,this paper proposes an Adaptive Robust Unscented Kalman Filter with Time-varying forgetting factors(TFF-ARUKF)for the angle/range integrated navigation system.Firstly,based on a statistically linear regression model approximating the nonlinear measurement model,the M-estimator is adopted to suppress the interference of outliers.Secondly,the covariance matching method is combined with the Huber linear regression problem to adaptively adjust the measurement noise covariance used in the M-estimation.Thirdly,to capture the time-varying characteristics of the measurement noise in each estimation,a new timevarying forgetting factors selection strategy is designed to dynamically adjust the adaptive matrix used in the covariance matching method.Simulations and experimental analysis compared with EKF,AMUKF,ARUKF,and Student's t-based methods have validated the effectiveness and robustness of the proposed algorithm.展开更多
Traditional machine vision algorithms have difficulty handling the interference of light and shadow changes,broken rows,and weeds in the complex growth circumstances of soybean fields,which leads to erroneous navigati...Traditional machine vision algorithms have difficulty handling the interference of light and shadow changes,broken rows,and weeds in the complex growth circumstances of soybean fields,which leads to erroneous navigation route segmentation.There are additional shortcomings in the feature extractFion capabilities of the conventional U-Net network.Our suggestion is to utilize an improved U-Net-based method to tackle these difficulties.First,we use ResNet’s powerful feature extraction capabilities to replace the original U-Net encoder.To enhance the concentration on characteristics unique to soybeans,we integrate a multi-scale high-performance attention mechanism.Furthermore,to do multi-scale feature extraction and capture a wider variety of contextual information,we employ atrous spatial pyramid pooling.The segmented image generated by our upgraded U-Net model is then analyzed using the CenterNet method to extract key spots.The RANSAC algorithm then uses these important spots to delineate the soybean seedling belt line.Finally,the navigation line is determined using the angle tangency theory.The experimental findings illustrate the superiority of our method.Our improved model significantly outperforms the original U-Net regarding mean Pixel Accuracy(mPA)and mean Intersection over Union(mIOU)indices,showing a more accurate segmentation of soybean routes.Furthermore,our soybean route navigation system’s outstanding accuracy is demonstrated by the deviation angle,which is only 3°between the actual deviation and the navigation line.This technology makes a substantial contribution to the sustainable growth of agriculture and shows potential for real-world applications.展开更多
To improve the navigation accuracy of an autonomous underwater vehicle （AUV）, a novel terrain passive integrated navigation system （TPINS） is presented. According to the characteristics of the underwater environme...To improve the navigation accuracy of an autonomous underwater vehicle （AUV）, a novel terrain passive integrated navigation system （TPINS） is presented. According to the characteristics of the underwater environment and AUV navigation requirements of low cost and high accuracy, a novel TPINS is designed with a configuration of the strapdown inertial navigation system （SINS）, the terrain reference navigation system （TRNS）, the Doppler velocity sonar （DVS）, the magnetic compass and the navigation computer utilizing the unscented Kalman filter （UKF） to fuse the navigation information from various navigation sensors. Linear filter equations for the extended Kalman filter （EKF）, nonlinear filter equations for the UKF and measurement equations of navigation sensors are addressed. It is indicated from the comparable simulation experiments of the EKF and the UKF that AUV navigation precision is improved substantially with the proposed sensors and the UKF when compared to the EKF. The TPINS designed with the proposed sensors and the UKF is effective in reducing AUV navigation position errors and improving the stability and precision of the AUV underwater integrated navigation.展开更多
The cost of the gravity passive inertial navigation system will be lower witha rate azimuth platform and gravity sensor constituting a gravity measurement and navigationsystem. According to the system performance char...The cost of the gravity passive inertial navigation system will be lower witha rate azimuth platform and gravity sensor constituting a gravity measurement and navigationsystem. According to the system performance characteristics, we study the rate azimuth platforminertial navigation system (RAPINS), give the system navigation algorithm, error equations of theattitude, velocity and position of the rate azimuth platform, and random error models of theaccelerometer and gyro. Using the MATLAB/Simulink tools, we study the RAPINS and RAPINS withvelocity damping. Simulation results demonstrate that the RAPINS with velocity damping has smallerrors in platform attitude and position and satisfies gravity measurement and navigationrequirement.展开更多
In this study, the problem of measuring noise pollution distribution by the intertial-based integrated navigation system is effectively suppressed. Based on nonlinear inertial navigation error modeling, a nested dual ...In this study, the problem of measuring noise pollution distribution by the intertial-based integrated navigation system is effectively suppressed. Based on nonlinear inertial navigation error modeling, a nested dual Kalman filter framework structure is developed. It consists of unscented Kalman filter (UKF)master filter and Kalman filter slave filter. This method uses nonlinear UKF for integrated navigation state estimation. At the same time, the exact noise measurement covariance is estimated by the Kalman filter dependency filter. The algorithm based on dual adaptive UKF (Dual-AUKF) has high accuracy and robustness, especially in the case of measurement information interference. Finally, vehicle-mounted and ship-mounted integrated navigation tests are conducted. Compared with traditional UKF and the Sage-Husa adaptive UKF (SH-AUKF), this method has comparable filtering accuracy and better filtering stability. The effectiveness of the proposed algorithm is verified.展开更多
BACKGROUND Computer-assisted systems obtained an increased interest in orthopaedic surgery over the last years,as they enhance precision compared to conventional hardware.The expansion of computer assistance is evolvi...BACKGROUND Computer-assisted systems obtained an increased interest in orthopaedic surgery over the last years,as they enhance precision compared to conventional hardware.The expansion of computer assistance is evolving with the employment of augmented reality.Yet,the accuracy of augmented reality navigation systems has not been determined.AIM To examine the accuracy of component alignment and restoration of the affected limb’s mechanical axis in primary total knee arthroplasty(TKA),utilizing an augmented reality navigation system and to assess whether such systems are conspicuously fruitful for an accomplished knee surgeon.METHODS From May 2021 to December 2021,30 patients,25 women and five men,under-went a primary unilateral TKA.Revision cases were excluded.A preoperative radiographic procedure was performed to evaluate the limb’s axial alignment.All patients were operated on by the same team,without a tourniquet,utilizing three distinct prostheses with the assistance of the Knee+™augmented reality navigation system in every operation.Postoperatively,the same radiographic exam protocol was executed to evaluate the implants’position,orientation and coronal plane alignment.We recorded measurements in 3 stages regarding femoral varus and flexion,tibial varus and posterior slope.Firstly,the expected values from the Augmented Reality system were documented.Then we calculated the same values after each cut and finally,the same measurements were recorded radiolo-gically after the operations.Concerning statistical analysis,Lin’s concordance correlation coefficient was estimated,while Wilcoxon Signed Rank Test was performed when needed.RESULTS A statistically significant difference was observed regarding mean expected values and radiographic mea-surements for femoral flexion measurements only(Z score=2.67,P value=0.01).Nonetheless,this difference was statistically significantly lower than 1 degree(Z score=-4.21,P value<0.01).In terms of discrepancies in the calculations of expected values and controlled measurements,a statistically significant difference between tibial varus values was detected(Z score=-2.33,P value=0.02),which was also statistically significantly lower than 1 degree(Z score=-4.99,P value<0.01).CONCLUSION The results indicate satisfactory postoperative coronal alignment without outliers across all three different implants utilized.Augmented reality navigation systems can bolster orthopaedic surgeons’accuracy in achieving precise axial alignment.However,further research is required to further evaluate their efficacy and potential.展开更多
Based on error analysis, the influence of error sources on strapdown inertial navigation systems is discussed. And the maximum permissible component tolerances are established. In order to achieve the desired accuracy...Based on error analysis, the influence of error sources on strapdown inertial navigation systems is discussed. And the maximum permissible component tolerances are established. In order to achieve the desired accuracy (defined by circular error probability), the types of appropriate sensors are chosen. The inertial measurement unit (IMU) is composed of those sensors. It is necessary to calibrate the sensors to obtain their error model coefficients of IMU. After calibration tests, the accuracy is calculated by uniform design method and it is proved that the accuracy of IMU is satisfied for the desired goal.展开更多
The principle of the inertial navigation system（INS） with rotating inertial measurement unit （IMU） is analyzed. A new IMU is established to rotate round each axis in three directions. Then, the related error model...The principle of the inertial navigation system（INS） with rotating inertial measurement unit （IMU） is analyzed. A new IMU is established to rotate round each axis in three directions. Then, the related error models for the designed system during rotating are deduced and the improved system is built. Finally, the performance simulation of the proposed system is provided. The simulation result indicates that the designed system can improve the accuracy of the roll and the pitch as well as heading by rotating three axes, thus guaranting the heading accuracy. Moreover, based on the principle of rotation at six different positions, such structure can carry out real-time calibration, and improve the system performance.展开更多
At the stage of preliminary scheme and algorithm design for spaceborne navigation systems, a precise and high-fidelity software global positioning system （GPS） simulator is a necessary and feasible testing facility ...At the stage of preliminary scheme and algorithm design for spaceborne navigation systems, a precise and high-fidelity software global positioning system （GPS） simulator is a necessary and feasible testing facility in laboratory environments, with consideration of the tradeoffs where possible. This article presents a software GPS measurements simulator on the L1 C/A code and carrier signal for space-oriented navigation system design. The simulator, coded in MATLAB language, generates both C/A code pseudorange and carrier phase measurements. Mathematical models in the Earth centered inertial （ECI） frame are formulated to simulate the GPS constellation and to generate GPS measurements. A series of efficient measures are investigated and utilized to rationalize the enhanced simulator, in terms of ephemeris data selection, space ionospheric model and range rate calculation, etc. Such an enhanced simulator has been facilitating our current work for designing a space integrated GPS/inertial navigation system （INS） navigation system. Consequently, it will promote our future research on space-oriented navigation system.展开更多
The strapdown inertial navigation system （SINS）/two-antenna GPS integrated navigation system is discussed. Corresponding error and the measurement models are built, especially the double differenced GPS carrier phas...The strapdown inertial navigation system （SINS）/two-antenna GPS integrated navigation system is discussed. Corresponding error and the measurement models are built, especially the double differenced GPS carrier phase model. The extended Kalman filtering is proposed. And the hardware composition and connection are designed to simulate the SINS/two-antenna GPS integrated navigation system. Results show that the performances of the system, the precision of the navigation and the positioning, the reliability and the practicability are im proved.展开更多
Based on the inertial navigation system, the influences of the excursion of the inertial navigation system and the measurement error of the wireless pressure altimeter on the rotation and scale of the real image are q...Based on the inertial navigation system, the influences of the excursion of the inertial navigation system and the measurement error of the wireless pressure altimeter on the rotation and scale of the real image are quantitatively analyzed in scene matching. The log-polar transform （LPT） is utilized and an anti-rotation and anti- scale image matching algorithm is proposed based on the image edge feature point extraction. In the algorithm, the center point is combined with its four-neighbor points, and the corresponding computing process is put forward. Simulation results show that in the image rotation and scale variation range resulted from the navigation system error and the measurement error of the wireless pressure altimeter, the proposed image matching algo- rithm can satisfy the accuracy demands of the scene aided navigation system and provide the location error-correcting information of the system.展开更多
According to the characteristics of gravity passive navigation, this paper presents a novel gravity passive navigation system （GPNS）, which consists of the rate azimuth platform （RAP）, gravity sensor, digitally st...According to the characteristics of gravity passive navigation, this paper presents a novel gravity passive navigation system （GPNS）, which consists of the rate azimuth platform （RAP）, gravity sensor, digitally stored gravity maps, depth sensor and relative log. The algorithm of rate azimuth platform inertial navigation system, error state-space equations, measurement equations and GPNS optimal filter are described. In view of the measurements made by an onboard gravity sensor the Eotvos effect is introduced in the gravity measurement equation of a GPNS optimal filter. A GPNS is studied with the Matlab/Simulink tools; simulation results demonstrate that a GPNS has small errors in platform attitude and position. Because the inertial navigation platform is the rate azimuth platform in the GPNS and gravity sensor is mounted on the rate azimuth platform, the cost of the GPNS is lower than existing GPNS＇s and according to the above results the GPNS meets the need to maintain accuracy navigation for underwater vehicles over long intervals.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
In micro-electro-mechanical system based inertial navigation system（MEMS-INS）/global position system（GPS） integrated navigation systems, there exist unknown disturbances and abnormal measurements. In order to obta...In micro-electro-mechanical system based inertial navigation system（MEMS-INS）/global position system（GPS） integrated navigation systems, there exist unknown disturbances and abnormal measurements. In order to obtain high estimation accuracy and enhance detection sensitivity to faults in measurements, this paper deals with the problem of model-based robust estimation（RE） and fault detection（FD）. A filter gain matrix and a post-filter are designed to obtain a RE and FD algorithm with current measurements, which is different from most of the existing priori filters using measurements in one-step delay. With the designed filter gain matrix, the H-infinity norm of the transfer function from noise inputs to estimation error outputs is limited within a certain range; with the designed post-filter, the residual signal is robust to disturbances but sensitive to faults. Therefore, the algorithm can guarantee small estimation errors in the presence of disturbances and have high sensitivity to faults. The proposed method is evaluated in an integrated navigation system, and the simulation results show that it is more effective in position estimation and fault signal detection than priori RE and FD algorithms.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
In this work,a fast and accurate stationary alignment method for strapdown inertial navigation system （SINS） is proposed. It has been demonstrated that the stationary alignment of SINS can be improved by employing t...In this work,a fast and accurate stationary alignment method for strapdown inertial navigation system （SINS） is proposed. It has been demonstrated that the stationary alignment of SINS can be improved by employing the multiposition technique,but the alignment time of the azimuth error is relatively longer. Over here, the two-position alignment principle is presented. On the basis of this SINS error model, a fast estimation algorithm of the azimuth error for the initial alignment of SINS on stationary base is derived fully from the horizontal velocity outputs and the output rates, and the novel azimuth error estimation algorithm is used for the two-position alignment. Consequently, the speed and accuracy of the SINS＇ s initial alignment is enhanced greatly. The computer simulation results illustrate the efficiency of this alignment method.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
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.
基金supported in part by the Doctoral Initiation Fund of Nanchang Hangkong University(No.EA202403107)Jiangxi Province Early Career Youth Science and Technology Talent Training Project(No.CK202403509).
文摘This paper presents the design and ground verification for vision-based relative navigation systems of microsatellites,which offers a comprehensive hardware design solution and a robust experimental verification methodology for practical implementation of vision-based navigation technology on the microsatellite platform.Firstly,a low power consumption,light weight,and high performance vision-based relative navigation optical sensor is designed.Subsequently,a set of ground verification system is designed for the hardware-in-the-loop testing of the vision-based relative navigation systems.Finally,the designed vision-based relative navigation optical sensor and the proposed angles-only navigation algorithms are tested on the ground verification system.The results verify that the optical simulator after geometrical calibration can meet the requirements of the hardware-in-the-loop testing of vision-based relative navigation systems.Based on experimental results,the relative position accuracy of the angles-only navigation filter at terminal time is increased by 25.5%,and the relative speed accuracy is increased by 31.3% compared with those of optical simulator before geometrical calibration.
基金the National Natural Science Foundation of China(Nos.82330063 and M-0019)the Interdisciplinary Program of Shanghai Jiao Tong University(Nos.YG2022QN056,YG2023ZD19,and YG2023ZD15)+2 种基金the Cross Disciplinary Research Fund of Shanghai Ninth People’s Hospital,Shanghai Jiao Tong University School of Medicine(No.JYJC202115)the Translation Clinical R&D Project of Medical Robot of Shanghai Ninth People’s Hospital,Shanghai Jiao Tong University School of Medicine(No.IMR-NPH202002)the Shanghai Key Clinical Specialty,Shanghai Eye Disease Research Center(No.2022ZZ01003)。
文摘Endoscopic transnasal optic nerve decompression surgery plays a crucial role in minimal invasive treatment of complex traumatic optic neuropathy.However,a major challenge faced during the procedure is the inability to visualize the optic nerve intraoperatively.To address this issue,an endoscopic image-based augmented reality surgical navigation system is developed in this study.The system aims to virtually fuse the optic nerve onto the endoscopic images,assisting surgeons in determining the optic nerve’s position and reducing surgical risks.First,a calibration algorithm based on a checkerboard grid of immobile points is proposed,building upon existing calibration methods.Additionally,to tackle accuracy issues associated with augmented reality technology,an optical navigation and visual fusion compensation algorithm is proposed to improve the intraoperative tracking accuracy.To evaluate the system’s performance,model experiments were meticulously designed and conducted.The results confirm the accuracy and stability of the proposed system,with an average tracking error of(0.99±0.46)mm.This outcome demonstrates the effectiveness of the proposed algorithm in improving the augmented reality surgical navigation system’s accuracy.Furthermore,the system successfully displays hidden optic nerves and other deep tissues,thus showcasing the promising potential for future applications in orbital and maxillofacial surgery.
基金supported by the Strategic Priority Research Program of the Chinese Academy of Sciences(No.XDA0350400)。
文摘The angle/range-based integrated navigation system is a favorable navigation solution for deep space explorers.However,the statistical characteristics of the measurement noise are time-varying,leading to inaccuracies in the derived measurement covariance even causing filter divergence.To reduce the gap between theoretical and actual covariances,some adaptive methods use empirically determined and unchanged forgetting factors to scale innovations within the sliding window.However,the constant weighting sequence cannot accurately adapt to the time-varying measurement noise in dynamic processes.Therefore,this paper proposes an Adaptive Robust Unscented Kalman Filter with Time-varying forgetting factors(TFF-ARUKF)for the angle/range integrated navigation system.Firstly,based on a statistically linear regression model approximating the nonlinear measurement model,the M-estimator is adopted to suppress the interference of outliers.Secondly,the covariance matching method is combined with the Huber linear regression problem to adaptively adjust the measurement noise covariance used in the M-estimation.Thirdly,to capture the time-varying characteristics of the measurement noise in each estimation,a new timevarying forgetting factors selection strategy is designed to dynamically adjust the adaptive matrix used in the covariance matching method.Simulations and experimental analysis compared with EKF,AMUKF,ARUKF,and Student's t-based methods have validated the effectiveness and robustness of the proposed algorithm.
基金Support Project(ZRCPY201805)2023 Heilongjiang Province Key Research and Development Plan“Open the List”(2023ZXJ07B02).
文摘Traditional machine vision algorithms have difficulty handling the interference of light and shadow changes,broken rows,and weeds in the complex growth circumstances of soybean fields,which leads to erroneous navigation route segmentation.There are additional shortcomings in the feature extractFion capabilities of the conventional U-Net network.Our suggestion is to utilize an improved U-Net-based method to tackle these difficulties.First,we use ResNet’s powerful feature extraction capabilities to replace the original U-Net encoder.To enhance the concentration on characteristics unique to soybeans,we integrate a multi-scale high-performance attention mechanism.Furthermore,to do multi-scale feature extraction and capture a wider variety of contextual information,we employ atrous spatial pyramid pooling.The segmented image generated by our upgraded U-Net model is then analyzed using the CenterNet method to extract key spots.The RANSAC algorithm then uses these important spots to delineate the soybean seedling belt line.Finally,the navigation line is determined using the angle tangency theory.The experimental findings illustrate the superiority of our method.Our improved model significantly outperforms the original U-Net regarding mean Pixel Accuracy(mPA)and mean Intersection over Union(mIOU)indices,showing a more accurate segmentation of soybean routes.Furthermore,our soybean route navigation system’s outstanding accuracy is demonstrated by the deviation angle,which is only 3°between the actual deviation and the navigation line.This technology makes a substantial contribution to the sustainable growth of agriculture and shows potential for real-world applications.
基金Pre-Research Program of General Armament Department during the11th Five-Year Plan Period (No51309020503)the National Defense Basic Research Program of China (973Program)(No973-61334)+1 种基金the National Natural Science Foundation of China(No50575042)Specialized Research Fund for the Doctoral Program of Higher Education (No20050286026)
文摘To improve the navigation accuracy of an autonomous underwater vehicle （AUV）, a novel terrain passive integrated navigation system （TPINS） is presented. According to the characteristics of the underwater environment and AUV navigation requirements of low cost and high accuracy, a novel TPINS is designed with a configuration of the strapdown inertial navigation system （SINS）, the terrain reference navigation system （TRNS）, the Doppler velocity sonar （DVS）, the magnetic compass and the navigation computer utilizing the unscented Kalman filter （UKF） to fuse the navigation information from various navigation sensors. Linear filter equations for the extended Kalman filter （EKF）, nonlinear filter equations for the UKF and measurement equations of navigation sensors are addressed. It is indicated from the comparable simulation experiments of the EKF and the UKF that AUV navigation precision is improved substantially with the proposed sensors and the UKF when compared to the EKF. The TPINS designed with the proposed sensors and the UKF is effective in reducing AUV navigation position errors and improving the stability and precision of the AUV underwater integrated navigation.
文摘The cost of the gravity passive inertial navigation system will be lower witha rate azimuth platform and gravity sensor constituting a gravity measurement and navigationsystem. According to the system performance characteristics, we study the rate azimuth platforminertial navigation system (RAPINS), give the system navigation algorithm, error equations of theattitude, velocity and position of the rate azimuth platform, and random error models of theaccelerometer and gyro. Using the MATLAB/Simulink tools, we study the RAPINS and RAPINS withvelocity damping. Simulation results demonstrate that the RAPINS with velocity damping has smallerrors in platform attitude and position and satisfies gravity measurement and navigationrequirement.
基金supported by China Postdoctoral Science Foundation(2023M741882)the National Natural Science Foundation of China(62103222,62273195)。
文摘In this study, the problem of measuring noise pollution distribution by the intertial-based integrated navigation system is effectively suppressed. Based on nonlinear inertial navigation error modeling, a nested dual Kalman filter framework structure is developed. It consists of unscented Kalman filter (UKF)master filter and Kalman filter slave filter. This method uses nonlinear UKF for integrated navigation state estimation. At the same time, the exact noise measurement covariance is estimated by the Kalman filter dependency filter. The algorithm based on dual adaptive UKF (Dual-AUKF) has high accuracy and robustness, especially in the case of measurement information interference. Finally, vehicle-mounted and ship-mounted integrated navigation tests are conducted. Compared with traditional UKF and the Sage-Husa adaptive UKF (SH-AUKF), this method has comparable filtering accuracy and better filtering stability. The effectiveness of the proposed algorithm is verified.
文摘BACKGROUND Computer-assisted systems obtained an increased interest in orthopaedic surgery over the last years,as they enhance precision compared to conventional hardware.The expansion of computer assistance is evolving with the employment of augmented reality.Yet,the accuracy of augmented reality navigation systems has not been determined.AIM To examine the accuracy of component alignment and restoration of the affected limb’s mechanical axis in primary total knee arthroplasty(TKA),utilizing an augmented reality navigation system and to assess whether such systems are conspicuously fruitful for an accomplished knee surgeon.METHODS From May 2021 to December 2021,30 patients,25 women and five men,under-went a primary unilateral TKA.Revision cases were excluded.A preoperative radiographic procedure was performed to evaluate the limb’s axial alignment.All patients were operated on by the same team,without a tourniquet,utilizing three distinct prostheses with the assistance of the Knee+™augmented reality navigation system in every operation.Postoperatively,the same radiographic exam protocol was executed to evaluate the implants’position,orientation and coronal plane alignment.We recorded measurements in 3 stages regarding femoral varus and flexion,tibial varus and posterior slope.Firstly,the expected values from the Augmented Reality system were documented.Then we calculated the same values after each cut and finally,the same measurements were recorded radiolo-gically after the operations.Concerning statistical analysis,Lin’s concordance correlation coefficient was estimated,while Wilcoxon Signed Rank Test was performed when needed.RESULTS A statistically significant difference was observed regarding mean expected values and radiographic mea-surements for femoral flexion measurements only(Z score=2.67,P value=0.01).Nonetheless,this difference was statistically significantly lower than 1 degree(Z score=-4.21,P value<0.01).In terms of discrepancies in the calculations of expected values and controlled measurements,a statistically significant difference between tibial varus values was detected(Z score=-2.33,P value=0.02),which was also statistically significantly lower than 1 degree(Z score=-4.99,P value<0.01).CONCLUSION The results indicate satisfactory postoperative coronal alignment without outliers across all three different implants utilized.Augmented reality navigation systems can bolster orthopaedic surgeons’accuracy in achieving precise axial alignment.However,further research is required to further evaluate their efficacy and potential.
文摘Based on error analysis, the influence of error sources on strapdown inertial navigation systems is discussed. And the maximum permissible component tolerances are established. In order to achieve the desired accuracy (defined by circular error probability), the types of appropriate sensors are chosen. The inertial measurement unit (IMU) is composed of those sensors. It is necessary to calibrate the sensors to obtain their error model coefficients of IMU. After calibration tests, the accuracy is calculated by uniform design method and it is proved that the accuracy of IMU is satisfied for the desired goal.
基金Supported by the National Natural Science Foundation of China(60702003)~~
文摘The principle of the inertial navigation system（INS） with rotating inertial measurement unit （IMU） is analyzed. A new IMU is established to rotate round each axis in three directions. Then, the related error models for the designed system during rotating are deduced and the improved system is built. Finally, the performance simulation of the proposed system is provided. The simulation result indicates that the designed system can improve the accuracy of the roll and the pitch as well as heading by rotating three axes, thus guaranting the heading accuracy. Moreover, based on the principle of rotation at six different positions, such structure can carry out real-time calibration, and improve the system performance.
基金Research Fund of Shanghai Academy of Spaceflight Technology
文摘At the stage of preliminary scheme and algorithm design for spaceborne navigation systems, a precise and high-fidelity software global positioning system （GPS） simulator is a necessary and feasible testing facility in laboratory environments, with consideration of the tradeoffs where possible. This article presents a software GPS measurements simulator on the L1 C/A code and carrier signal for space-oriented navigation system design. The simulator, coded in MATLAB language, generates both C/A code pseudorange and carrier phase measurements. Mathematical models in the Earth centered inertial （ECI） frame are formulated to simulate the GPS constellation and to generate GPS measurements. A series of efficient measures are investigated and utilized to rationalize the enhanced simulator, in terms of ephemeris data selection, space ionospheric model and range rate calculation, etc. Such an enhanced simulator has been facilitating our current work for designing a space integrated GPS/inertial navigation system （INS） navigation system. Consequently, it will promote our future research on space-oriented navigation system.
文摘The strapdown inertial navigation system （SINS）/two-antenna GPS integrated navigation system is discussed. Corresponding error and the measurement models are built, especially the double differenced GPS carrier phase model. The extended Kalman filtering is proposed. And the hardware composition and connection are designed to simulate the SINS/two-antenna GPS integrated navigation system. Results show that the performances of the system, the precision of the navigation and the positioning, the reliability and the practicability are im proved.
文摘Based on the inertial navigation system, the influences of the excursion of the inertial navigation system and the measurement error of the wireless pressure altimeter on the rotation and scale of the real image are quantitatively analyzed in scene matching. The log-polar transform （LPT） is utilized and an anti-rotation and anti- scale image matching algorithm is proposed based on the image edge feature point extraction. In the algorithm, the center point is combined with its four-neighbor points, and the corresponding computing process is put forward. Simulation results show that in the image rotation and scale variation range resulted from the navigation system error and the measurement error of the wireless pressure altimeter, the proposed image matching algo- rithm can satisfy the accuracy demands of the scene aided navigation system and provide the location error-correcting information of the system.
文摘According to the characteristics of gravity passive navigation, this paper presents a novel gravity passive navigation system （GPNS）, which consists of the rate azimuth platform （RAP）, gravity sensor, digitally stored gravity maps, depth sensor and relative log. The algorithm of rate azimuth platform inertial navigation system, error state-space equations, measurement equations and GPNS optimal filter are described. In view of the measurements made by an onboard gravity sensor the Eotvos effect is introduced in the gravity measurement equation of a GPNS optimal filter. A GPNS is studied with the Matlab/Simulink tools; simulation results demonstrate that a GPNS has small errors in platform attitude and position. Because the inertial navigation platform is the rate azimuth platform in the GPNS and gravity sensor is mounted on the rate azimuth platform, the cost of the GPNS is lower than existing GPNS＇s and according to the above results the GPNS meets the need to maintain accuracy navigation for underwater vehicles over long intervals.
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co-supported by the National Natural Science Foundation of China(No.61153002)the Aeronautical Science Foundation of China(No.20130153002)
文摘In micro-electro-mechanical system based inertial navigation system（MEMS-INS）/global position system（GPS） integrated navigation systems, there exist unknown disturbances and abnormal measurements. In order to obtain high estimation accuracy and enhance detection sensitivity to faults in measurements, this paper deals with the problem of model-based robust estimation（RE） and fault detection（FD）. A filter gain matrix and a post-filter are designed to obtain a RE and FD algorithm with current measurements, which is different from most of the existing priori filters using measurements in one-step delay. With the designed filter gain matrix, the H-infinity norm of the transfer function from noise inputs to estimation error outputs is limited within a certain range; with the designed post-filter, the residual signal is robust to disturbances but sensitive to faults. Therefore, the algorithm can guarantee small estimation errors in the presence of disturbances and have high sensitivity to faults. The proposed method is evaluated in an integrated navigation system, and the simulation results show that it is more effective in position estimation and fault signal detection than priori RE and FD algorithms.
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In this work,a fast and accurate stationary alignment method for strapdown inertial navigation system （SINS） is proposed. It has been demonstrated that the stationary alignment of SINS can be improved by employing the multiposition technique,but the alignment time of the azimuth error is relatively longer. Over here, the two-position alignment principle is presented. On the basis of this SINS error model, a fast estimation algorithm of the azimuth error for the initial alignment of SINS on stationary base is derived fully from the horizontal velocity outputs and the output rates, and the novel azimuth error estimation algorithm is used for the two-position alignment. Consequently, the speed and accuracy of the SINS＇ s initial alignment is enhanced greatly. The computer simulation results illustrate the efficiency of this alignment method.
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.
