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 order to improve the navigation accuracy of an inertial navigation system （INS）, composed of quartz gyroscopes, the existing real-time compensation methods for periodic errors in quartz gyroscope drift and the pe...In order to improve the navigation accuracy of an inertial navigation system （INS）, composed of quartz gyroscopes, the existing real-time compensation methods for periodic errors in quartz gyroscope drift and the periodic error term relationship between sampled original data and smoothed data are reviewed. On the base of the results, a new compensation method called using former period characteristics to compensate latter smoothness data （UFCL for short） method is proposed considering the INS working characteristics. This new method uses the original data without smoothing to work out an error conversion formula at the INS initial alignment time and then compensate the smoothed data errors by way of the formula at the navigation time. Both theoretical analysis and experimental results demonstrate that this method is able to cut down on computational time and raise the accuracy which makes it a better real-time compensation approach for periodic error terms of quartz micro electronic mechanical system （MEMS） gyroscope＇s zero drift.展开更多
Since any disturbance and fault may lead to significant performance degradation in practical dynamical systems,it is essential for a system to be robust to disturbances but sensitive to faults.For this purpose,this pa...Since any disturbance and fault may lead to significant performance degradation in practical dynamical systems,it is essential for a system to be robust to disturbances but sensitive to faults.For this purpose,this paper proposes a robust fault-detection filter for linear discrete time-varying systems.The algorithm uses H∞ estimator to minimize the worst possible amplification from disturbances to estimate errors,and H_ index to maximize the minimum effect of faults on the residual output of the filter.This approach is applied to the MEMS-based INS/GPS.And simulation results show that the new algorithm can reduce the effect of unknown disturbances and has a high sensitivity to faults.展开更多
Several new MEMS Inertial Measurement Unit(IMU) sensor products have been released recently with improved performance,which have the potential to support much higher precision applications.New MEMS IMUs include the Na...Several new MEMS Inertial Measurement Unit(IMU) sensor products have been released recently with improved performance,which have the potential to support much higher precision applications.New MEMS IMUs include the NavChip from InterSense,the Nav440 from Crossbow,the Landmark30/40 from GTI,the SDI500 from Systron Donner.Since they are new in the market,currently there is limited information about their error characterization which however is important for the construction of proper error models for their integration with other sensors such as GPS.This paper will investigate the error characterization of two new MEMS IMU sensors,namely the NavChip and Nav440,using Allan variance technique.In addition to identifying different error terms,different stochastic error modeling methods,such as Gauss-Markov(GM) and Autoregressive(AR) processes,will also be investigated to assess the MEMS IMU sensor biases.Investigation to integrate new MEMS IMU sensors with Precise Point Positioning(PPP) will also be conducted to address the re-convergence issues.展开更多
When an aircraft moves under a low carrier-to-noise ratio （CNR） or at a high speed, increasing the sensitivity of global navigation satellite system （GNSS） receiver is a goal quite hard to achieve. A novel acquisi...When an aircraft moves under a low carrier-to-noise ratio （CNR） or at a high speed, increasing the sensitivity of global navigation satellite system （GNSS） receiver is a goal quite hard to achieve. A novel acquisition scheme assisted with micro-electro-mechanical-sensor （MEMS） inertial navigation system （INS） is presented to estimate the Doppler caused by user dynamics relative to each satellite ahead of time. Based on tightly coupled GNSS/INS estimation algorithm, MEMS INS Doppler error that can be achieved is first described. Then, by analyzing the mean acquisition time and signal detection probability, the MEMS INS-assisted acquisition capabilities in cold, warm and hot starts are quantitatively determined and compared with the standard GNSS acquisition capability. The simulations and comparisons have shown that： the acquisition time in cold start can be shortened by at least 23 s, the time in warm start can be shortened to i s and the acquisition capability is improved 95%, and the reaequisition time in hot start can be shortened by around 0.090 s and the capability can be enhanced 40%. The results demonstrate the validity of the novel method.展开更多
随着位置服务(location based service,LBS)应用需求的日益增加以及多部位微机电系统(micro electro mechanical system,MEMS)导航传感器的广泛普及,行人航位推算(pedestrian dead reckoning,PDR)越来越受关注,成为行人导航研究中主流...随着位置服务(location based service,LBS)应用需求的日益增加以及多部位微机电系统(micro electro mechanical system,MEMS)导航传感器的广泛普及,行人航位推算(pedestrian dead reckoning,PDR)越来越受关注,成为行人导航研究中主流的技术之一。但是,低成本的MEMS传感器测量噪声大,PDR解算误差积累严重;且PDR算法的普适性差,不同穿戴位置的MEMS导航传感器约束条件的可用性差异明显。提出了一种基于穿戴式MEMS传感器状态识别的多部位PDR算法。首先,采用支持向量机(support vector machine,SVM)进行全监督训练,实现了静止状态及运动状态下手部、腿部、腰部、足部4种穿戴位置的准确识别;然后,分析了不同穿戴位置下PDR算法的适用性,根据适用性分析结果提出了多部位PDR的综合解算策略。实测结果表明,该方法能够动态、准确地实现穿戴式MEMS传感器的状态识别,正确率达97%以上;应用PDR综合解算策略后,足部PDR能够实现高精度解算,累计误差为0.74%,而其他位置(手部、腿部、腰部)解算效果得到显著改善,累计误差从识别前的6.76%~21.19%减小为2.92%~5.62%。展开更多
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.
基金New Century Program for Excellent Telents (NCET- 04-0162)National Defense Basic Research Program (K1204060116)
文摘In order to improve the navigation accuracy of an inertial navigation system （INS）, composed of quartz gyroscopes, the existing real-time compensation methods for periodic errors in quartz gyroscope drift and the periodic error term relationship between sampled original data and smoothed data are reviewed. On the base of the results, a new compensation method called using former period characteristics to compensate latter smoothness data （UFCL for short） method is proposed considering the INS working characteristics. This new method uses the original data without smoothing to work out an error conversion formula at the INS initial alignment time and then compensate the smoothed data errors by way of the formula at the navigation time. Both theoretical analysis and experimental results demonstrate that this method is able to cut down on computational time and raise the accuracy which makes it a better real-time compensation approach for periodic error terms of quartz micro electronic mechanical system （MEMS） gyroscope＇s zero drift.
基金supported by the National Natural Science Foundation of China(60774002)the Foundation of New Century Excellent Talents in University of China(NCET-05-0177)
文摘Since any disturbance and fault may lead to significant performance degradation in practical dynamical systems,it is essential for a system to be robust to disturbances but sensitive to faults.For this purpose,this paper proposes a robust fault-detection filter for linear discrete time-varying systems.The algorithm uses H∞ estimator to minimize the worst possible amplification from disturbances to estimate errors,and H_ index to maximize the minimum effect of faults on the residual output of the filter.This approach is applied to the MEMS-based INS/GPS.And simulation results show that the new algorithm can reduce the effect of unknown disturbances and has a high sensitivity to faults.
基金Excellent talents Program of Liaoning Province(LR2011007)supported by the Natural Sciences and Engineering Research Council(NSERC)of Canada and Tecterra as well as Program for Liaoning Excellent Talents in University,China~~
文摘Several new MEMS Inertial Measurement Unit(IMU) sensor products have been released recently with improved performance,which have the potential to support much higher precision applications.New MEMS IMUs include the NavChip from InterSense,the Nav440 from Crossbow,the Landmark30/40 from GTI,the SDI500 from Systron Donner.Since they are new in the market,currently there is limited information about their error characterization which however is important for the construction of proper error models for their integration with other sensors such as GPS.This paper will investigate the error characterization of two new MEMS IMU sensors,namely the NavChip and Nav440,using Allan variance technique.In addition to identifying different error terms,different stochastic error modeling methods,such as Gauss-Markov(GM) and Autoregressive(AR) processes,will also be investigated to assess the MEMS IMU sensor biases.Investigation to integrate new MEMS IMU sensors with Precise Point Positioning(PPP) will also be conducted to address the re-convergence issues.
基金the National High Technology Research and Development Program (863) of China(No.2009AA12Z322)
文摘When an aircraft moves under a low carrier-to-noise ratio （CNR） or at a high speed, increasing the sensitivity of global navigation satellite system （GNSS） receiver is a goal quite hard to achieve. A novel acquisition scheme assisted with micro-electro-mechanical-sensor （MEMS） inertial navigation system （INS） is presented to estimate the Doppler caused by user dynamics relative to each satellite ahead of time. Based on tightly coupled GNSS/INS estimation algorithm, MEMS INS Doppler error that can be achieved is first described. Then, by analyzing the mean acquisition time and signal detection probability, the MEMS INS-assisted acquisition capabilities in cold, warm and hot starts are quantitatively determined and compared with the standard GNSS acquisition capability. The simulations and comparisons have shown that： the acquisition time in cold start can be shortened by at least 23 s, the time in warm start can be shortened to i s and the acquisition capability is improved 95%, and the reaequisition time in hot start can be shortened by around 0.090 s and the capability can be enhanced 40%. The results demonstrate the validity of the novel method.
文摘随着位置服务(location based service,LBS)应用需求的日益增加以及多部位微机电系统(micro electro mechanical system,MEMS)导航传感器的广泛普及,行人航位推算(pedestrian dead reckoning,PDR)越来越受关注,成为行人导航研究中主流的技术之一。但是,低成本的MEMS传感器测量噪声大,PDR解算误差积累严重;且PDR算法的普适性差,不同穿戴位置的MEMS导航传感器约束条件的可用性差异明显。提出了一种基于穿戴式MEMS传感器状态识别的多部位PDR算法。首先,采用支持向量机(support vector machine,SVM)进行全监督训练,实现了静止状态及运动状态下手部、腿部、腰部、足部4种穿戴位置的准确识别;然后,分析了不同穿戴位置下PDR算法的适用性,根据适用性分析结果提出了多部位PDR的综合解算策略。实测结果表明,该方法能够动态、准确地实现穿戴式MEMS传感器的状态识别,正确率达97%以上;应用PDR综合解算策略后,足部PDR能够实现高精度解算,累计误差为0.74%,而其他位置(手部、腿部、腰部)解算效果得到显著改善,累计误差从识别前的6.76%~21.19%减小为2.92%~5.62%。
