This work presents a method for the three-dimensional localization of individual shallow NV center in diamond,leveraging the near-field quenching effect of a gold tip.Our experimental setup involves the use of an atom...This work presents a method for the three-dimensional localization of individual shallow NV center in diamond,leveraging the near-field quenching effect of a gold tip.Our experimental setup involves the use of an atomic force microscope to precisely move the gold tip close to the NV center,while simultaneously employing a home-made confocal microscope to monitor the fluorescence of the NV center.This approach allows for lateral super-resolution,achieving a full width at half maximum(FWHM)of 38.0 nm and a location uncertainty of 0.7 nm.Additionally,we show the potential of this method for determining the depth of the NV centers.We also attempt to determine the depth of the NV centers in combination with finite-difference time-domain(FDTD)simulations.Compared to other depth determination methods,this approach allows for simultaneous lateral and longitudinal localization of individual NV centers,and holds promise for facilitating manipulation of the local environment surrounding the NV center.展开更多
Multiple quadrotors target encirclement is widely used in the intelligent field,as it can effectively monitor and control target behavior.However,it faces the danger of collision,as well as difficulties in localizatio...Multiple quadrotors target encirclement is widely used in the intelligent field,as it can effectively monitor and control target behavior.However,it faces the danger of collision,as well as difficulties in localization and tracking.Therefore,we propose a complete target encirclement method.Firstly,based on Hooke's law,a collision avoidance controller is designed to maintain a safe flying distance among quadrotors.Then,based on the consensus theory,a formation tracking controller is designed to meet the requirements of formation transformation and encirclement tasks,and a stability proof based on Lyapunov was provided.Besides,the target detection is designed based on YOLOv5s,and the target location model is constructed based on the principle of pinhole projection and triangle similarity.Finally,we conducted experiments on the built platform,with 3 reconnaissance quadrotors detecting and localization 3 target vehicles and 7 hunter quadrotors tracking them.The results show that the minimum average error for localization targets with reconnaissance quadrotors can reach 0.1354 m,while the minimum average error for tracking with hunter quadrotors is only 0.2960 m.No quadrotors collision occurred in the whole formation transformation and tracking experiment.In addition,compared with the advanced methods,the proposed method has better performance.展开更多
Most of the existing non-line-of-sight(NLOS)localization methods depend on the layout information of the scene which is difficult to be obtained in advance in the practical application scenarios.To solve the problem,a...Most of the existing non-line-of-sight(NLOS)localization methods depend on the layout information of the scene which is difficult to be obtained in advance in the practical application scenarios.To solve the problem,an NLOS target localization method in unknown L-shaped corridor based ultra-wideband(UWB)multiple-input multiple-output(MIMO)radar is proposed in this paper.Firstly,the multipath propagation model of Lshaped corridor is established.Then,the localization process is analyzed by the propagation characteristics of diffraction and reflection.Specifically,two different back-projection imaging processes are performed on the radar echo,and the positions of focus regions in the two images are extracted to generate candidate targets.Furthermore,the distances of propagation paths corresponding to each candidate target are calculated,and then the similarity between each candidate target and the target is evaluated by employing two matching factors.The locations of the targets and the width of the corridor are determined based on the matching rules.Finally,two experiments are carried out to demonstrate that the method can effectively obtain the target positions and unknown scene information even when partial paths are lost.展开更多
The multipath effect and movements of people in indoor environments lead to inaccurate localization. Through the test, calculation and analysis on the received signal strength indication （RSSI） and the variance of R...The multipath effect and movements of people in indoor environments lead to inaccurate localization. Through the test, calculation and analysis on the received signal strength indication （RSSI） and the variance of RSSI, we propose a novel variance-based fingerprint distance adjustment algorithm （VFDA）. Based on the rule that variance decreases with the increase of RSSI mean, VFDA calculates RSSI variance with the mean value of received RSSIs. Then, we can get the correction weight. VFDA adjusts the fingerprint distances with the correction weight based on the variance of RSSI, which is used to correct the fingerprint distance. Besides, a threshold value is applied to VFDA to improve its performance further. VFDA and VFDA with the threshold value are applied in two kinds of real typical indoor environments deployed with several Wi-Fi access points. One is a quadrate lab room, and the other is a long and narrow corridor of a building. Experimental results and performance analysis show that in indoor environments, both VFDA and VFDA with the threshold have better positioning accuracy and environmental adaptability than the current typical positioning methods based on the k-nearest neighbor algorithm and the weighted k-nearest neighbor algorithm with similar computational costs.展开更多
A target localization algorithm,which uses the measurement information from onboard GPS and onboard laser detector to acquire the target position,is proposed to obtain the accurate position of ground target in real ti...A target localization algorithm,which uses the measurement information from onboard GPS and onboard laser detector to acquire the target position,is proposed to obtain the accurate position of ground target in real time in the trajectory correction process of semi-active laser terminal correction projectile.A target localization model is established according to projectile position,attitude and line-of-sight angle.The effects of measurement errors of projectile position,attitude and line-of-sight angle on localization accuracy at different quadrant elevation angles are analyzed through Monte-Carlo simulation.The simulation results show that the measurement error of line-of-sight angle has the largest influence on the localization accuracy.The localization accuracy decreases with the increase in quadrant elevation angle.However,the maximum localization accuracy is less than 7 m.The proposed algorithm meets the accuracy and real-time requirements of target localization.展开更多
Geographic location of nodes is very useful in a sensor network. Previous localization algorithms assume that there exist some anchor nodes in this kind of network, and then other nodes are estimated to create their c...Geographic location of nodes is very useful in a sensor network. Previous localization algorithms assume that there exist some anchor nodes in this kind of network, and then other nodes are estimated to create their coordinates. Once there are not anchors to be deployed, those localization algorithms will be invalidated. Many papers in this field focus on anchor-based solutions. The use of anchors introduces many limitations, since anchors require external equipments such as global position system, cause additional power consumption. A novel positioning algorithm is proposed to use a virtual coordinate system based on a new concept--virtual anchor. It is executed in a distributed fashion according to the connectivity of a node and the measured distances to its neighbors. Both the adjacent member information and the ranging distance result are combined to generate the estimated position of a network, one of which is independently adopted for localization previously. At the position refinement stage the intermediate estimation of a node begins to be evaluated on its reliability for position mutation; thus the positioning optimization process of the whole network is avoided falling into a local optimal solution. Simulation results prove that the algorithm can resolve the distributed localization problem for anchor-free sensor networks, and is superior to previous methods in terms of its positioning capability under a variety of circumstances.展开更多
A new monostatic array system taking advantage of diverse waveforms to improve the performance of underwater tar- get localization is proposed. Unlike the coherent signals between different elements in common active a...A new monostatic array system taking advantage of diverse waveforms to improve the performance of underwater tar- get localization is proposed. Unlike the coherent signals between different elements in common active array, the transmitted signals from different elements here are spatially orthogonal waveforms which allow for array processing in the transit mode and result in an extension of array aperture. The mathematical derivation of Capon estimator for this sonar system is described in detail. And the performance of this orthogonal-waveform based sonar is an- alyzed and compared with that of its phased-array counterpart by water tank experiments. Experimental results show that this sonar system could achieve 12 dB-15 dB additional array gain over its phased-array counterpart, which means a doubling of maximum detection range. Moreover, the angular resolution is significantly improved at lower SNR.展开更多
Based on multiple unmanned aerial vehicles（UAVs） flight at a constant altitude,a fault-tolerant cooperative localization algorithm against global positioning system（GPS） signal loss due to GPS receiver malfunction...Based on multiple unmanned aerial vehicles（UAVs） flight at a constant altitude,a fault-tolerant cooperative localization algorithm against global positioning system（GPS） signal loss due to GPS receiver malfunction is proposed.Contrast to the traditional means with single UAV,the proposed method is based on the use of inter-UAV relative range measurements against GPS signal loss and more suitable for the small-size and low-cost UAV applications.Firstly,for re-localizing an UAV with a malfunction in its GPS receiver,an algorithm which makes use of any other three healthy UAVs in the cooperative flight as the reference points for re-localization is proposed.Secondly,by using the relative ranges from the faulty UAV to the other three UAVs,its horizontal location can be determined after the GPS signal is lost.In order to improve an accuracy of the localization,a Kalman filter is further exploited to provide the estimated location of the UAV with the GPS signal loss.The Kalman filter calculates the variance of observations in terms of horizontal dilution of positioning（HDOP） automatically.Then,during each discrete computing time step,the best reference points are selected adaptively by minimizing the HDOP.Finally,two simulation examples in Matlab/Simulink environment with five UAVs in cooperative flight are shown to evaluate the effectiveness of the proposed method.展开更多
Local invariant algorithm applied in downward-looking image registration,usually computes the camera＇s pose relative to visual landmarks.Generally,there are three requirements in the process of image registration whe...Local invariant algorithm applied in downward-looking image registration,usually computes the camera＇s pose relative to visual landmarks.Generally,there are three requirements in the process of image registration when using these approaches.First,the algorithm is apt to be influenced by illumination.Second,algorithm should have less computational complexity.Third,the depth information of images needs to be estimated without other sensors.This paper investigates a famous local invariant feature named speeded up robust feature（SURF）,and proposes a highspeed and robust image registration and localization algorithm based on it.With supports from feature tracking and pose estimation methods,the proposed algorithm can compute camera poses under different conditions of scale,viewpoint and rotation so as to precisely localize object＇s position.At last,the study makes registration experiment by scale invariant feature transform（SIFT）,SURF and the proposed algorithm,and designs a method to evaluate their performances.Furthermore,this study makes object retrieval test on remote sensing video.For there is big deformation on remote sensing frames,the registration algorithm absorbs the Kanade-Lucas-Tomasi（KLT） 3-D coplanar calibration feature tracker methods,which can localize interesting targets precisely and efficiently.The experimental results prove that the proposed method has a higher localization speed and lower localization error rate than traditional visual simultaneous localization and mapping（vSLAM） in a period of time.展开更多
An extended Kalman filter approach of simultaneous localization and mapping(SLAM) was proposed based on local maps. A local frame of reference was established periodically at the position of the robot, and then the ob...An extended Kalman filter approach of simultaneous localization and mapping(SLAM) was proposed based on local maps. A local frame of reference was established periodically at the position of the robot, and then the observations of the robot and landmarks were fused into the global frame of reference. Because of the independence of the local map, the approach does not cumulate the estimate and calculation errors which are produced by SLAM using Kalman filter directly. At the same time, it reduces the computational complexity. This method is proven correct and feasible in simulation experiments.展开更多
Due to defects of time-difference of arrival localization,which influences by speed differences of various model waveforms and waveform distortion in transmitting process,a neural network technique is introduced to ca...Due to defects of time-difference of arrival localization,which influences by speed differences of various model waveforms and waveform distortion in transmitting process,a neural network technique is introduced to calculate localization of the acoustic emission source.However,in back propagation（BP） neural network,the BP algorithm is a stochastic gradient algorithm virtually,the network may get into local minimum and the result of network training is dissatisfactory.It is a kind of genetic algorithms with the form of quantum chromosomes,the random observation which simulates the quantum collapse can bring diverse individuals,and the evolutionary operators characterized by a quantum mechanism are introduced to speed up convergence and avoid prematurity.Simulation results show that the modeling of neural network based on quantum genetic algorithm has fast convergent and higher localization accuracy,so it has a good application prospect and is worth researching further more.展开更多
A novel multi-observer passive localization algorithm based on the weighted restricted total least square （WRTLS） is proposed to solve the bearings-only localization problem in the presence of observer position erro...A novel multi-observer passive localization algorithm based on the weighted restricted total least square （WRTLS） is proposed to solve the bearings-only localization problem in the presence of observer position errors. Firstly, the unknown matrix perturbation information is utilized to form the WRTLS problem. Then, the corresponding constrained optimization problem is transformed into an unconstrained one, which is a generalized Rayleigh quotient minimization problem. Thus, the solution can be got through the generalized eigenvalue decomposition and requires no initial state guess process. Simulation results indicate that the proposed algorithm can approach the Cramer-Rao lower bound （CRLB）, and the localization solution is asymptotically unbiased.展开更多
This paper investigates the node localization problem for wireless sensor networks in three-dimension space. A distributed localization algorithm is presented based on the rigid graph. Before location, the communicati...This paper investigates the node localization problem for wireless sensor networks in three-dimension space. A distributed localization algorithm is presented based on the rigid graph. Before location, the communication radius is adaptively increasing to add the localizability. The localization process includes three steps: firstly, divide the whole globally rigid graph into several small rigid blocks; secondly, set up the local coordinate systems and transform them to global coordinate system; finally, use the quadrilateration iteration technology to locate the nodes in the wireless sensor network. This algorithm has the advantages of low energy consumption, low computational complexity as well as high expandability and high localizability. Moreover, it can achieve the unique and accurate localization. Finally, some simulations are provided to demonstrate the effectiveness of the proposed algorithm.展开更多
Software debugging accounts for a vast majority of the financial and time costs in software developing and maintenance. Thus, approaches of software fault localization that can help automate the debugging process have...Software debugging accounts for a vast majority of the financial and time costs in software developing and maintenance. Thus, approaches of software fault localization that can help automate the debugging process have become a hot topic in the field of software engineering. Given the great demand for software fault localization, an approach based on the artificial bee colony （ABC） algorithm is proposed to be integrated with other related techniques. In this process, the source program is initially instrumented after analyzing the dependence information. The test case sets are then compiled and run on the instrumented program, and execution results are input to the ABC algorithm. The algorithm can determine the largest fitness value and best food source by calculating the average fitness of the employed bees in the iteralive process. The program unit with the highest suspicion score corresponding to the best test case set is regarded as the final fault localization. Experiments are conducted with the TCAS program in the Siemens suite. Results demonstrate that the proposed fault localization method is effective and efficient. The ABC algorithm can efficiently avoid the local optimum, and ensure the validity of the fault location to a larger extent.展开更多
This paper introduces an indoor global localization method by extending and matching features. In the proposed method, the environment is partitioned into convex subdivisions. Local extended maps of the subdivisions a...This paper introduces an indoor global localization method by extending and matching features. In the proposed method, the environment is partitioned into convex subdivisions. Local extended maps of the subdivisions are then built by exten- ding features to constitute the local extended map set. While the robot is moving in the environment, the local extended map of the current local environment is established and then matched with the local extended map set. Therefore, global localization in an indoor environment can be achieved by integrating the position and ori- entation matching rates. Both theoretical analysis and comparison experimental result are provided to verify the effectiveness of the proposed method for global localization.展开更多
Time delay and Doppler shift between the echo signal and the reference signal are two most commonly used measurements in target localization for the passive radar. Doppler rate, which can be obtained from the extended...Time delay and Doppler shift between the echo signal and the reference signal are two most commonly used measurements in target localization for the passive radar. Doppler rate, which can be obtained from the extended cross ambiguity function, offers an opportunity to further enhance the localization accuracy. This paper considers using the measurement Doppler rate in addition to measurements of time delay and Doppler shift to locate a moving target. A closed-form solution is developed to accurately and efficiently estimate the target position and velocity.The proposed solution establishes a pseudolinear set of equations by introducing some additional variables, imposes weighted least squares formulation to yield a rough estimate, and utilizes the function relation among the target location parameters and additional variables to improve the estimation accuracy. Theoretical covariance and Cramer-Rao lower bound(CRLB) are derived and compared, analytically indicating that the proposed solution attains the CRLB. Numerical simulations corroborate this analysis and demonstrate that the proposed solution outperforms existing methods.展开更多
This paper considers the time difference of arrival(TDOA)and frequency difference of arrival(FDOA)estimation problem for joint localization using unmanned aerial vehicles(UAVs),involving range migration(RM)and Doppler...This paper considers the time difference of arrival(TDOA)and frequency difference of arrival(FDOA)estimation problem for joint localization using unmanned aerial vehicles(UAVs),involving range migration(RM)and Doppler ambiguity within observation interval.A robust estimation method based on interpolation and resampling is proposed.Specifically,the interpolation artificially increases the pulse repetition frequency(PRF).After that,the resampling eliminates the coupling between range frequency and slow time.Finally,a coherent integration step based on inverse discrete Fourier transform(IDFT)is used to achieve parameter estimation and suppress the grating lobes caused by interpolation.The proposed method could be efficiently implemented by fast Fourier transform(FFT),inverse FFT(IFFT)and non-uniform FFT(NUFFT)without parameter searching procedures.Numerical experiments indicate that the proposed method has nearly optimal anti-noise performance but much lower computational complexity than the maximum likelihood estimator,which makes it more competitive in practical applications.展开更多
This paper links parallel factor（PARAFAC） analysis to the problem of nominal direction-of-arrival（DOA） estimation for coherently distributed（CD） sources and proposes a fast PARAFACbased algorithm by establishing...This paper links parallel factor（PARAFAC） analysis to the problem of nominal direction-of-arrival（DOA） estimation for coherently distributed（CD） sources and proposes a fast PARAFACbased algorithm by establishing the trilinear PARAFAC model.Relying on the uniqueness of the low-rank three-way array decomposition and the trilinear alternating least squares regression, the proposed algorithm achieves nominal DOA estimation and outperforms the conventional estimation of signal parameter via rotational technique CD（ESPRIT-CD） and propagator method CD（PM-CD）methods in terms of estimation accuracy. Furthermore, by means of the initialization via the propagator method, this paper accelerates the convergence procedure of the proposed algorithm with no estimation performance degradation. In addition, the proposed algorithm can be directly applied to the multiple-source scenario,where sources have different angular distribution shapes. Numerical simulation results corroborate the effectiveness and superiority of the proposed fast PARAFAC-based algorithm.展开更多
Leakage is one of the most important reasons for failure of hydraulic systems.The accurate positioning of leakage is of great significance to ensure the safe and reliable operation of hydraulic systems.For early stage...Leakage is one of the most important reasons for failure of hydraulic systems.The accurate positioning of leakage is of great significance to ensure the safe and reliable operation of hydraulic systems.For early stage of leakage,the pressure of the hydraulic circuit does not change obviously and therefore cannot be monitored by pressure sensors.Meanwhile,the pressure of the hydraulic circuit changes frequently due to the influence of load and state of the switch,which further reduces the accuracy of leakage localization.In the work,a novel Bayesian networks(BNs)-based data-driven early leakage localization approach for multi-valve systems is proposed.Wavelet transform is used for signal noise reduction and BNs-based leak localization model is used to identify the location of leakage.A normalization model is developed to improve the robustness of the leakage localization model.A hydraulic system with eight valves is used to demonstrate the application of the proposed early micro-leakage detection and localization approach.展开更多
基金supported by the National Natural Science Foundation of China(T2325023,92265204,12104447)the National Key R&D Program of China(2023YFF0718400)+1 种基金the Innovation Program for Quantum Science and Technology(2021ZD0302200)the Fundamental Research Funds for the Central Universities。
文摘This work presents a method for the three-dimensional localization of individual shallow NV center in diamond,leveraging the near-field quenching effect of a gold tip.Our experimental setup involves the use of an atomic force microscope to precisely move the gold tip close to the NV center,while simultaneously employing a home-made confocal microscope to monitor the fluorescence of the NV center.This approach allows for lateral super-resolution,achieving a full width at half maximum(FWHM)of 38.0 nm and a location uncertainty of 0.7 nm.Additionally,we show the potential of this method for determining the depth of the NV centers.We also attempt to determine the depth of the NV centers in combination with finite-difference time-domain(FDTD)simulations.Compared to other depth determination methods,this approach allows for simultaneous lateral and longitudinal localization of individual NV centers,and holds promise for facilitating manipulation of the local environment surrounding the NV center.
基金the National Natural Science Foundation of China(Grant Nos.62303348 and 62173242)the Aeronautical Science Foundation of China(Grant No.2024M071048002)the National Science Fund for Distinguished Young Scholars(Grant No.62225308)to provide fund for conducting experiments.
文摘Multiple quadrotors target encirclement is widely used in the intelligent field,as it can effectively monitor and control target behavior.However,it faces the danger of collision,as well as difficulties in localization and tracking.Therefore,we propose a complete target encirclement method.Firstly,based on Hooke's law,a collision avoidance controller is designed to maintain a safe flying distance among quadrotors.Then,based on the consensus theory,a formation tracking controller is designed to meet the requirements of formation transformation and encirclement tasks,and a stability proof based on Lyapunov was provided.Besides,the target detection is designed based on YOLOv5s,and the target location model is constructed based on the principle of pinhole projection and triangle similarity.Finally,we conducted experiments on the built platform,with 3 reconnaissance quadrotors detecting and localization 3 target vehicles and 7 hunter quadrotors tracking them.The results show that the minimum average error for localization targets with reconnaissance quadrotors can reach 0.1354 m,while the minimum average error for tracking with hunter quadrotors is only 0.2960 m.No quadrotors collision occurred in the whole formation transformation and tracking experiment.In addition,compared with the advanced methods,the proposed method has better performance.
基金supported by National Natural Science Foundation of China(U20B2070,62001091)Sichuan Science and Technology Program(2022YFS0531).
文摘Most of the existing non-line-of-sight(NLOS)localization methods depend on the layout information of the scene which is difficult to be obtained in advance in the practical application scenarios.To solve the problem,an NLOS target localization method in unknown L-shaped corridor based ultra-wideband(UWB)multiple-input multiple-output(MIMO)radar is proposed in this paper.Firstly,the multipath propagation model of Lshaped corridor is established.Then,the localization process is analyzed by the propagation characteristics of diffraction and reflection.Specifically,two different back-projection imaging processes are performed on the radar echo,and the positions of focus regions in the two images are extracted to generate candidate targets.Furthermore,the distances of propagation paths corresponding to each candidate target are calculated,and then the similarity between each candidate target and the target is evaluated by employing two matching factors.The locations of the targets and the width of the corridor are determined based on the matching rules.Finally,two experiments are carried out to demonstrate that the method can effectively obtain the target positions and unknown scene information even when partial paths are lost.
基金supported by the National Natural Science Foundation of China(6120200461472192)+1 种基金the Special Fund for Fast Sharing of Science Paper in Net Era by CSTD(2013116)the Natural Science Fund of Higher Education of Jiangsu Province(14KJB520014)
文摘The multipath effect and movements of people in indoor environments lead to inaccurate localization. Through the test, calculation and analysis on the received signal strength indication （RSSI） and the variance of RSSI, we propose a novel variance-based fingerprint distance adjustment algorithm （VFDA）. Based on the rule that variance decreases with the increase of RSSI mean, VFDA calculates RSSI variance with the mean value of received RSSIs. Then, we can get the correction weight. VFDA adjusts the fingerprint distances with the correction weight based on the variance of RSSI, which is used to correct the fingerprint distance. Besides, a threshold value is applied to VFDA to improve its performance further. VFDA and VFDA with the threshold value are applied in two kinds of real typical indoor environments deployed with several Wi-Fi access points. One is a quadrate lab room, and the other is a long and narrow corridor of a building. Experimental results and performance analysis show that in indoor environments, both VFDA and VFDA with the threshold have better positioning accuracy and environmental adaptability than the current typical positioning methods based on the k-nearest neighbor algorithm and the weighted k-nearest neighbor algorithm with similar computational costs.
文摘A target localization algorithm,which uses the measurement information from onboard GPS and onboard laser detector to acquire the target position,is proposed to obtain the accurate position of ground target in real time in the trajectory correction process of semi-active laser terminal correction projectile.A target localization model is established according to projectile position,attitude and line-of-sight angle.The effects of measurement errors of projectile position,attitude and line-of-sight angle on localization accuracy at different quadrant elevation angles are analyzed through Monte-Carlo simulation.The simulation results show that the measurement error of line-of-sight angle has the largest influence on the localization accuracy.The localization accuracy decreases with the increase in quadrant elevation angle.However,the maximum localization accuracy is less than 7 m.The proposed algorithm meets the accuracy and real-time requirements of target localization.
基金the National Natural Science Foundation of China (60673054, 60773129)theExcellent Youth Science and Technology Foundation of Anhui Province of China.
文摘Geographic location of nodes is very useful in a sensor network. Previous localization algorithms assume that there exist some anchor nodes in this kind of network, and then other nodes are estimated to create their coordinates. Once there are not anchors to be deployed, those localization algorithms will be invalidated. Many papers in this field focus on anchor-based solutions. The use of anchors introduces many limitations, since anchors require external equipments such as global position system, cause additional power consumption. A novel positioning algorithm is proposed to use a virtual coordinate system based on a new concept--virtual anchor. It is executed in a distributed fashion according to the connectivity of a node and the measured distances to its neighbors. Both the adjacent member information and the ranging distance result are combined to generate the estimated position of a network, one of which is independently adopted for localization previously. At the position refinement stage the intermediate estimation of a node begins to be evaluated on its reliability for position mutation; thus the positioning optimization process of the whole network is avoided falling into a local optimal solution. Simulation results prove that the algorithm can resolve the distributed localization problem for anchor-free sensor networks, and is superior to previous methods in terms of its positioning capability under a variety of circumstances.
基金supported by the National Natural Science Foundation of China(60572098)
文摘A new monostatic array system taking advantage of diverse waveforms to improve the performance of underwater tar- get localization is proposed. Unlike the coherent signals between different elements in common active array, the transmitted signals from different elements here are spatially orthogonal waveforms which allow for array processing in the transit mode and result in an extension of array aperture. The mathematical derivation of Capon estimator for this sonar system is described in detail. And the performance of this orthogonal-waveform based sonar is an- alyzed and compared with that of its phased-array counterpart by water tank experiments. Experimental results show that this sonar system could achieve 12 dB-15 dB additional array gain over its phased-array counterpart, which means a doubling of maximum detection range. Moreover, the angular resolution is significantly improved at lower SNR.
基金supported by the National Natural Science Foundation of China(60974146)the Natural Science and Engineering Research Council of Canada(NSERC)
文摘Based on multiple unmanned aerial vehicles（UAVs） flight at a constant altitude,a fault-tolerant cooperative localization algorithm against global positioning system（GPS） signal loss due to GPS receiver malfunction is proposed.Contrast to the traditional means with single UAV,the proposed method is based on the use of inter-UAV relative range measurements against GPS signal loss and more suitable for the small-size and low-cost UAV applications.Firstly,for re-localizing an UAV with a malfunction in its GPS receiver,an algorithm which makes use of any other three healthy UAVs in the cooperative flight as the reference points for re-localization is proposed.Secondly,by using the relative ranges from the faulty UAV to the other three UAVs,its horizontal location can be determined after the GPS signal is lost.In order to improve an accuracy of the localization,a Kalman filter is further exploited to provide the estimated location of the UAV with the GPS signal loss.The Kalman filter calculates the variance of observations in terms of horizontal dilution of positioning（HDOP） automatically.Then,during each discrete computing time step,the best reference points are selected adaptively by minimizing the HDOP.Finally,two simulation examples in Matlab/Simulink environment with five UAVs in cooperative flight are shown to evaluate the effectiveness of the proposed method.
基金supported by the National Natural Science Foundation of China (60802043)the National Basic Research Program of China(973 Program) (2010CB327900)
文摘Local invariant algorithm applied in downward-looking image registration,usually computes the camera＇s pose relative to visual landmarks.Generally,there are three requirements in the process of image registration when using these approaches.First,the algorithm is apt to be influenced by illumination.Second,algorithm should have less computational complexity.Third,the depth information of images needs to be estimated without other sensors.This paper investigates a famous local invariant feature named speeded up robust feature（SURF）,and proposes a highspeed and robust image registration and localization algorithm based on it.With supports from feature tracking and pose estimation methods,the proposed algorithm can compute camera poses under different conditions of scale,viewpoint and rotation so as to precisely localize object＇s position.At last,the study makes registration experiment by scale invariant feature transform（SIFT）,SURF and the proposed algorithm,and designs a method to evaluate their performances.Furthermore,this study makes object retrieval test on remote sensing video.For there is big deformation on remote sensing frames,the registration algorithm absorbs the Kanade-Lucas-Tomasi（KLT） 3-D coplanar calibration feature tracker methods,which can localize interesting targets precisely and efficiently.The experimental results prove that the proposed method has a higher localization speed and lower localization error rate than traditional visual simultaneous localization and mapping（vSLAM） in a period of time.
基金Project(60234030) supported by the National Natural Science Foundation of China project(A1420060159) supported by the National Basic Research
文摘An extended Kalman filter approach of simultaneous localization and mapping(SLAM) was proposed based on local maps. A local frame of reference was established periodically at the position of the robot, and then the observations of the robot and landmarks were fused into the global frame of reference. Because of the independence of the local map, the approach does not cumulate the estimate and calculation errors which are produced by SLAM using Kalman filter directly. At the same time, it reduces the computational complexity. This method is proven correct and feasible in simulation experiments.
基金supported by the National Natural Science Foundation of China (51075068)the Southeast University Science Foundation Funded Program (KJ2009348)
文摘Due to defects of time-difference of arrival localization,which influences by speed differences of various model waveforms and waveform distortion in transmitting process,a neural network technique is introduced to calculate localization of the acoustic emission source.However,in back propagation（BP） neural network,the BP algorithm is a stochastic gradient algorithm virtually,the network may get into local minimum and the result of network training is dissatisfactory.It is a kind of genetic algorithms with the form of quantum chromosomes,the random observation which simulates the quantum collapse can bring diverse individuals,and the evolutionary operators characterized by a quantum mechanism are introduced to speed up convergence and avoid prematurity.Simulation results show that the modeling of neural network based on quantum genetic algorithm has fast convergent and higher localization accuracy,so it has a good application prospect and is worth researching further more.
基金supported by the Aeronautical Science Foundation of China (20105584004)the Science and Technology on Avionics Integration Laboratory
文摘A novel multi-observer passive localization algorithm based on the weighted restricted total least square （WRTLS） is proposed to solve the bearings-only localization problem in the presence of observer position errors. Firstly, the unknown matrix perturbation information is utilized to form the WRTLS problem. Then, the corresponding constrained optimization problem is transformed into an unconstrained one, which is a generalized Rayleigh quotient minimization problem. Thus, the solution can be got through the generalized eigenvalue decomposition and requires no initial state guess process. Simulation results indicate that the proposed algorithm can approach the Cramer-Rao lower bound （CRLB）, and the localization solution is asymptotically unbiased.
基金supported by the National Natural Science Foundation of China(61375105 61403334)
文摘This paper investigates the node localization problem for wireless sensor networks in three-dimension space. A distributed localization algorithm is presented based on the rigid graph. Before location, the communication radius is adaptively increasing to add the localizability. The localization process includes three steps: firstly, divide the whole globally rigid graph into several small rigid blocks; secondly, set up the local coordinate systems and transform them to global coordinate system; finally, use the quadrilateration iteration technology to locate the nodes in the wireless sensor network. This algorithm has the advantages of low energy consumption, low computational complexity as well as high expandability and high localizability. Moreover, it can achieve the unique and accurate localization. Finally, some simulations are provided to demonstrate the effectiveness of the proposed algorithm.
文摘Software debugging accounts for a vast majority of the financial and time costs in software developing and maintenance. Thus, approaches of software fault localization that can help automate the debugging process have become a hot topic in the field of software engineering. Given the great demand for software fault localization, an approach based on the artificial bee colony （ABC） algorithm is proposed to be integrated with other related techniques. In this process, the source program is initially instrumented after analyzing the dependence information. The test case sets are then compiled and run on the instrumented program, and execution results are input to the ABC algorithm. The algorithm can determine the largest fitness value and best food source by calculating the average fitness of the employed bees in the iteralive process. The program unit with the highest suspicion score corresponding to the best test case set is regarded as the final fault localization. Experiments are conducted with the TCAS program in the Siemens suite. Results demonstrate that the proposed fault localization method is effective and efficient. The ABC algorithm can efficiently avoid the local optimum, and ensure the validity of the fault location to a larger extent.
基金supported by the National Natural Science Foundation of China(61375079)
文摘This paper introduces an indoor global localization method by extending and matching features. In the proposed method, the environment is partitioned into convex subdivisions. Local extended maps of the subdivisions are then built by exten- ding features to constitute the local extended map set. While the robot is moving in the environment, the local extended map of the current local environment is established and then matched with the local extended map set. Therefore, global localization in an indoor environment can be achieved by integrating the position and ori- entation matching rates. Both theoretical analysis and comparison experimental result are provided to verify the effectiveness of the proposed method for global localization.
基金supported by the National Natural Science Foundation of China (61703433)。
文摘Time delay and Doppler shift between the echo signal and the reference signal are two most commonly used measurements in target localization for the passive radar. Doppler rate, which can be obtained from the extended cross ambiguity function, offers an opportunity to further enhance the localization accuracy. This paper considers using the measurement Doppler rate in addition to measurements of time delay and Doppler shift to locate a moving target. A closed-form solution is developed to accurately and efficiently estimate the target position and velocity.The proposed solution establishes a pseudolinear set of equations by introducing some additional variables, imposes weighted least squares formulation to yield a rough estimate, and utilizes the function relation among the target location parameters and additional variables to improve the estimation accuracy. Theoretical covariance and Cramer-Rao lower bound(CRLB) are derived and compared, analytically indicating that the proposed solution attains the CRLB. Numerical simulations corroborate this analysis and demonstrate that the proposed solution outperforms existing methods.
基金The authors would like to acknowledge National Natural Science Foundation of China(Grant No.xxxxxx)。
文摘This paper considers the time difference of arrival(TDOA)and frequency difference of arrival(FDOA)estimation problem for joint localization using unmanned aerial vehicles(UAVs),involving range migration(RM)and Doppler ambiguity within observation interval.A robust estimation method based on interpolation and resampling is proposed.Specifically,the interpolation artificially increases the pulse repetition frequency(PRF).After that,the resampling eliminates the coupling between range frequency and slow time.Finally,a coherent integration step based on inverse discrete Fourier transform(IDFT)is used to achieve parameter estimation and suppress the grating lobes caused by interpolation.The proposed method could be efficiently implemented by fast Fourier transform(FFT),inverse FFT(IFFT)and non-uniform FFT(NUFFT)without parameter searching procedures.Numerical experiments indicate that the proposed method has nearly optimal anti-noise performance but much lower computational complexity than the maximum likelihood estimator,which makes it more competitive in practical applications.
基金supported by the National Natural Science Foundation of China(6137116961601167)+2 种基金the Jiangsu Natural Science Foundation(BK20161489)the open research fund of State Key Laboratory of Millimeter Waves,Southeast University(K201826)the Fundamental Research Funds for the Central Universities(NE2017103)
文摘This paper links parallel factor（PARAFAC） analysis to the problem of nominal direction-of-arrival（DOA） estimation for coherently distributed（CD） sources and proposes a fast PARAFACbased algorithm by establishing the trilinear PARAFAC model.Relying on the uniqueness of the low-rank three-way array decomposition and the trilinear alternating least squares regression, the proposed algorithm achieves nominal DOA estimation and outperforms the conventional estimation of signal parameter via rotational technique CD（ESPRIT-CD） and propagator method CD（PM-CD）methods in terms of estimation accuracy. Furthermore, by means of the initialization via the propagator method, this paper accelerates the convergence procedure of the proposed algorithm with no estimation performance degradation. In addition, the proposed algorithm can be directly applied to the multiple-source scenario,where sources have different angular distribution shapes. Numerical simulation results corroborate the effectiveness and superiority of the proposed fast PARAFAC-based algorithm.
基金Project(51779267)supported by the National Natural Science Foundation of ChinaProject(2019YFE0105100)supported by the National Key Research and Development Program of China+2 种基金Project(tsqn201909063)supported by the Taishan Scholars Project,ChinaProject(20CX02301A)supported by the Fundamental Research Funds for the Central Universities,ChinaProject(2019KJB016)supported by the Science and Technology Support Plan for Youth Innovation of Universities in Shandong Province,China。
文摘Leakage is one of the most important reasons for failure of hydraulic systems.The accurate positioning of leakage is of great significance to ensure the safe and reliable operation of hydraulic systems.For early stage of leakage,the pressure of the hydraulic circuit does not change obviously and therefore cannot be monitored by pressure sensors.Meanwhile,the pressure of the hydraulic circuit changes frequently due to the influence of load and state of the switch,which further reduces the accuracy of leakage localization.In the work,a novel Bayesian networks(BNs)-based data-driven early leakage localization approach for multi-valve systems is proposed.Wavelet transform is used for signal noise reduction and BNs-based leak localization model is used to identify the location of leakage.A normalization model is developed to improve the robustness of the leakage localization model.A hydraulic system with eight valves is used to demonstrate the application of the proposed early micro-leakage detection and localization approach.
