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Zhang X.-Y.,Nanjing Southeast University | Zhang X.-Y.,Key Laboratory of Micro Inertial Instrument and Advanced Navigation Technology | Zhang X.-Y.,China Institute of Technology | Zhang T.,Nanjing Southeast University | And 6 more authors.
Applied Physics Letters | Year: 2012

We show theoretically plasmonic antennas based on two-step chemical synthesized silver nano-flags constructed by a silver nanowire and a nanoplate. The silver nano-flag antennas exhibit high polarization sensitivity and diversity of spectral signatures dependent on the structural parameters arising from the observed mode competition. With specific configuration engineering, the antennas show controllable electric-field enhancement and ultra narrow bandwidths down to about 2 nm. These nano-antennas promise exciting applications in lasing spaser, optical modulation, and enhanced nonlinear processes. © 2012 American Institute of Physics.


Xu Y.,Nanjing Southeast University | Xu Y.,Key Laboratory of Micro Inertial Instrument and Advanced Navigation Technology | Chen X.,Nanjing Southeast University | Chen X.,Key Laboratory of Micro Inertial Instrument and Advanced Navigation Technology | And 2 more authors.
The Scientific World Journal | Year: 2014

As the core of the integrated navigation system, the data fusion algorithm should be designed seriously. In order to improve the accuracy of data fusion, this work proposed an adaptive iterated extended Kalman (AIEKF) which used the noise statistics estimator in the iterated extended Kalman (IEKF), and then AIEKF is used to deal with the nonlinear problem in the inertial navigation systems (INS)/wireless sensors networks (WSNs)-integrated navigation system. Practical test has been done to evaluate the performance of the proposed method. The results show that the proposed method is effective to reduce the mean root-mean-square error (RMSE) of position by about 92.53%, 67.93%, 55.97%, and 30.09% compared with the INS only, WSN, EKF, and IEKF. © 2014 Yuan Xu et al.


Zhang X.-Y.,Nanjing Southeast University | Zhang X.-Y.,University of Waterloo | Zhang X.-Y.,Key Laboratory of Micro Inertial Instrument and Advanced Navigation Technology | Hu A.,University of Waterloo | And 6 more authors.
Applied Physics Letters | Year: 2010

We show theoretically that plasmonic waveguide structures in ZnO nanowires and nanotubes working at optical frequencies can achieve photonic waveguiding in a subdiffraction limit. The output intensity distribution, propagation length, and thermo-optical properties with different waveguide configurations are investigated. Our results show that these waveguides have the potential to develop either high performance thermally controlled nanoscale plasmonic devices or thermally insensitive waveguides by optimizing waveguide configurations. © 2010 American Institute of Physics.


Zhang T.,Nanjing Southeast University | Xu X.,Key Laboratory of Micro Inertial Instrument and Advanced Navigation Technology | Xu S.,Key Laboratory of Micro Inertial Instrument and Advanced Navigation Technology
Measurement: Journal of the International Measurement Confederation | Year: 2015

A high-precision underwater digital elevation model (DEM) is the premise of terrain-aided navigation. This study introduces the establishment of such a model. The process includes the construction and optimization of a triangular irregular network, selection of interpolation data based on terrain roughness degree, kriging interpolation, and error corrections. Results show that the established interpolation data selection method based on terrain roughness degree is better than other traditional interpolation methods in terms of accuracy. The proposed kriging interpolation method and error corrections exhibit excellent performance. © 2014 Elsevier Ltd. All rights reserved.


Xu Y.,Nanjing Southeast University | Xu Y.,Key Laboratory of Micro Inertial Instrument and Advanced Navigation Technology | Chen X.,Nanjing Southeast University | Chen X.,Key Laboratory of Micro Inertial Instrument and Advanced Navigation Technology | And 2 more authors.
Mathematical Problems in Engineering | Year: 2012

In order to achieve continuous navigation capability in areas such as tunnels, urban canyons, and indoors a new approach using least squares support vector machine (LS-SVM) and H filter (HF) for integration of INS/WSN is proposed. In the integrated system, HF estimates the errors of position and velocity while the signals in WSNs are available. Meanwhile, the compensation model is trained by LS-SVM with corresponding HF states. Once outages of the signals in WSNs, the model is used to correct INS solution as HF does. Moreover, due to device reasons, there are slight fluctuations in sampling period in practice. For overcoming this problem of integrated navigation, the theoretical analysis and implementation of HF for an integrated navigation system with stochastic uncertainty are also given. Simulation shows the performance of HF is more robust compared with INS-only solution and Kalman filter (KF) solution, and the prediction of LS-SVM has the smallest error compared with INS-only and back propagation (BP), the improvement is particularly obvious. Copyright © 2012 Yuan Xu et al.


Liu X.,Nanjing Southeast University | Xu X.,Key Laboratory of Micro Inertial Instrument and Advanced Navigation Technology | Liu Y.,Key Laboratory of Micro Inertial Instrument and Advanced Navigation Technology | Wang L.,Key Laboratory of Micro Inertial Instrument and Advanced Navigation Technology
Measurement: Journal of the International Measurement Confederation | Year: 2014

There are two viewpoints in the transfer alignment process given as follows: (1) the information used for matching in strapdown inertial navigation system (SINS) originates from the mathematical frame which cuts off the direct relationship between sensor measurement and misalignment angles; (2) in close correction mode, the estimated parameters from data fusion filter are used to participate in SINS navigation solution. Based on the above viewpoints, a novel transfer alignment method based on iterative calculation is designed, and in this method the alignment time is shortened and alignment accuracy is improved and the real-time property of alignment result is ensured with the following two methods: (1) during every data fusion period, sensor data and external reference navigation parameters are stored, and the backward and forward navigation solution and data fusion are executed once or several times with the help of high performance computer; (2) with the help of multi-tasking method, the operations for storing sensor data in the current fusion period, iterative calculation for the previous fusion period, and navigation solution for the current fusion period based on the stored data and real-time data are run in parallel but with different priorities. The simulation and turntable test under ship swinging condition indicate that alignment time of the proposed method is shortened compared with that of classical method when the data fusion times of two methods are equal; and alignment accuracy is improved when the alignment times are equal. © 2014 Elsevier Ltd. All rights reserved.


Lu Y.,Key Laboratory of Micro Inertial Instrument and Advanced Navigation Technology | Cheng X.,Nanjing Southeast University
Measurement: Journal of the International Measurement Confederation | Year: 2014

Shipborne aircrafts normally do not have regular position on the carrier. This would lead to large misalignment between the master strapdown inertial navigation system (M-SINS) and slave strapdown inertial navigation system (S-SINS) as well as random lever arm vector. It is critical for the accuracy of the transfer alignment. The large attitude error will make the linear alignment algorithm invalid. And the lever arm vector caused by the location difference will lead to the lever arm effect which is sensed by the accelerometers in the S-SINS. Therefore it is necessary for the shipborne aircraft to estimate the lever arm vector and misalignment before the transfer alignment takes place. In this paper, a new misalignment and lever arm vector online estimation method based on gyroscope, accelerometer measurement and filtering is presented. Sensor measurements of M-SINS and S-SINS will be recorded for a few seconds. Misalignment and the lever arm vector will be calculated from these measurements directly. The values will be filtered according to the chosen threshold of the error gain. Then a second stage estimation based on least square estimation will be applied to acquire a better result. Simulation results demonstrate the effectiveness of the estimation algorithm in the situation when both large misalignment and random lever arm vector exist. © 2013 Elsevier Ltd. All rights reserved.


Liu X.,Nanjing Southeast University | Xu X.,Key Laboratory of Micro inertial Instrument and Advanced Navigation Technology | Zhao Y.,Key Laboratory of Micro inertial Instrument and Advanced Navigation Technology | Wang L.,Key Laboratory of Micro inertial Instrument and Advanced Navigation Technology | Liu Y.,Key Laboratory of Micro inertial Instrument and Advanced Navigation Technology
Measurement: Journal of the International Measurement Confederation | Year: 2014

Inspired by the alignment mechanism of Octans, an initial alignment method for strapdown gyrocompass is designed based on gravitational apparent motion in inertial frame. In this method, the gyro outputs are used to trace the body frame and the measurement from accelerometers are projected to the inertial frame to form the track of gravitational apparent motion. According to the calculations on the vectors involved in this track, the attitude matrix between the inertial frame and navigation frame can be obtained and further alignment can be finished. In order to identify the true gravitational apparent motion from the accelerometer measurement containing random noise as well as to avoid the collinear of vectors in vector operation, a reconstruction algorithm concerning parameter identification and reconstruction of apparent motion is devised and simulated. Simulation and turntable test show that the proposed alignment method can realize self-alignment in a swinging condition. The alignment accuracy is able to reach the theoretical one determined by sensor errors and no external information is needed. © 2014 Elsevier Ltd. All rights reserved.


Liu X.,Nanjing Southeast University | Liu X.,Key Laboratory of Micro Inertial Instrument and Advanced Navigation Technology | Xu X.,Nanjing Southeast University | Xu X.,Key Laboratory of Micro Inertial Instrument and Advanced Navigation Technology | And 4 more authors.
Measurement: Journal of the International Measurement Confederation | Year: 2013

Compared with Gimbaled Inertial Navigation System (GINS), there are two differences in the compass alignment process for Strapdown INS (SINS) as follows: (1) the input signal is the projected sensor data from body frame to calculated navigation frame, not the sensor data; (2) the output control signal participates in navigation solution rather than driving navigation frame directly. Considering these characteristics, a fast compass alignment method based on iterative calculation is designed for SINS in this paper. With the help of high performance computer, the iterative process can be finished fast and the alignment time can be shortened obviously. However, there exist two problems in the new method, one of which is how to use the saved data, and the other is how to ensure the real-time property of alignment result. For the first problem, our simulation result shows that the forward-forward navigation solution method is more effective for compass alignment than the backward-forward one. And to solve the second problem, Multi-tasking method combined with Real Time Multi-tasking Operating System (RTOS) is used to trace the change of body frame and update the body frame of attitude matrix when the alignment is finished. The car test on a type of fiber-optic gyro SINS indicates that the alignment accuracy of the proposed method processed for 142 s is as precise as that of the classical compass alignment method for 720 s. © 2013 Elsevier Ltd. All rights reserved.


Liu X.,Nanjing Southeast University | Liu X.,Key Laboratory of Micro inertial Instrument and Advanced Navigation Technology | Song Q.,Key Laboratory of Micro inertial Instrument and Advanced Navigation Technology | Yang Y.,Key Laboratory of Micro inertial Instrument and Advanced Navigation Technology | And 2 more authors.
Measurement: Journal of the International Measurement Confederation | Year: 2015

Based on the alignment idea of tracing gravitational apparent motion in inertial frame, a novel self-alignment and latitude calculation method for Strapdown Inertial Navigation System (SINS) is designed. In this method, the problem of acquiring attitude matrix between body frame and navigation frame is attributed to acquiring the matrix between initial body frame and current navigation frame, and the gravitational apparent motion vectors at three moments are used to construct corresponding vectors and matrix through vector-operation. Meanwhile, the latitude information can be obtained by virtue of the geometric relationships among gravitational apparent vectors. Furthermore, the validity of the proposed method is proved by mathematical proof, and the theoretical expressions for evaluating accuracies of initial alignment and latitude calculation are deduced detailedly. Simulation and turntable results indicate that the proposed method can fulfill self-alignment and latitude calculation under a swinging condition without translational motion. © 2014 Elsevier Ltd. All rights reserved.

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