Joint probabilistic data association is an effective method for tracking multiple targets in clutter, but only the target kinematic information is used in measure-to-track association. If the kinematic likelihoods are...Joint probabilistic data association is an effective method for tracking multiple targets in clutter, but only the target kinematic information is used in measure-to-track association. If the kinematic likelihoods are similar for different closely spaced targets, there is ambiguity in using the kinematic information alone; the correct association probability will decrease in conventional joint probabilistic data association algorithm and track coalescence will occur easily. A modified algorithm of joint probabilistic data association with classification-aided is presented, which avoids track coalescence when tracking multiple neighboring targets. Firstly, an identification matrix is defined, which is used to simplify validation matrix to decrease computational complexity. Then, target class information is integrated into the data association process. Performance comparisons with and without the use of class information in JPDA are presented on multiple closely spaced maneuvering targets tracking problem. Simulation results quantify the benefits of classification-aided JPDA for improved multiple targets tracking, especially in the presence of association uncertainty in the kinematic measurement and target maneuvering. Simulation results indicate that the algorithm is valid.展开更多
A specialized Hungarian algorithm was developed here for the maximum likelihood data association problem with two implementation versions due to presence of false alarms and missed detections. The maximum likelihood d...A specialized Hungarian algorithm was developed here for the maximum likelihood data association problem with two implementation versions due to presence of false alarms and missed detections. The maximum likelihood data association problem is formulated as a bipartite weighted matching problem. Its duality and the optimality conditions are given. The Hungarian algorithm with its computational steps, data structure and computational complexity is presented. The two implementation versions, Hungarian forest （HF） algorithm and Hungarian tree （HT） algorithm, and their combination with the naYve auction initialization are discussed. The computational results show that HT algorithm is slightly faster than HF algorithm and they are both superior to the classic Munkres algorithm.展开更多
Aiming at three-passive-sensor location system, a generalized 3-dimension （3-D） assignment model is constructed based on property information, and a multi-target programming model is proposed based on direction-find...Aiming at three-passive-sensor location system, a generalized 3-dimension （3-D） assignment model is constructed based on property information, and a multi-target programming model is proposed based on direction-finding and property fusion information. The multi-target programming model is transformed into a single target programming problem to resolve, and its data association result is compared with the results which are solved by using one kind of information only. Simulation experiments show the effectiveness of the multi-target programming algorithm with higher data association accuracy and less calculation.展开更多
In most of the passive tracking systems, only the target kinematical information is used in the measurement-to-track association, which results in error tracking in a multitarget environment, where the targets are too...In most of the passive tracking systems, only the target kinematical information is used in the measurement-to-track association, which results in error tracking in a multitarget environment, where the targets are too close to each other. To enhance the tracking accuracy, the target signal classification information （TSCI） should be used to improve the data association. The TSCI is integrated in the data association process using the JPDA （joint probabilistic data association）. The use of the TSCI in the data association can improve discrimination by yielding a purer track and preserving continuity. To verify the validity of the application of TSCI, two simulation experiments are done on an air target-tracing problem, that is, one using the TSCI and the other not using the TSCI. The final comparison shows that the use of the TSCI can effectively improve tracking accuracy.展开更多
Due to the advantages of ant colony optimization （ACO） in solving complex problems, a new data association algorithm based on ACO in a cluttered environment called DACDA is proposed. In the proposed method, the conc...Due to the advantages of ant colony optimization （ACO） in solving complex problems, a new data association algorithm based on ACO in a cluttered environment called DACDA is proposed. In the proposed method, the concept for tour and the length of tour are redefined. Additionally, the directional information is incorporated into the proposed method because it is one of the most important factors that affects the performance of data association. Kalman filter is employed to estimate target states. Computer simulation results show that the proposed method could carry out data association in an acceptable CPU time, and the correct data association rate is higher than that obtained by the data association （DA） algorithm not combined with directional information.展开更多
In the re-entry phase of a ballistic missile,decoys can be deployed as a mean to overburden enemy defenses.This results in a single track being split into multiple track-lets.Tracking of these track-lets is a critical...In the re-entry phase of a ballistic missile,decoys can be deployed as a mean to overburden enemy defenses.This results in a single track being split into multiple track-lets.Tracking of these track-lets is a critical task as any miss in the tracking procedure can become a cause of a major threat.The tracking process becomes more complicated in the presence of clutter.The low detection rate is one of the factors that may contribute to increasing the difficulty level in terms of tracking in the cluttered environment.This work introduces a new algorithm for the split event detection and target tracking under the framework of the joint integrated probabilistic data association(JIPDA)algorithm.The proposed algorithm is termed as split event-JIPDA(SE-JIPDA).This work establishes the mathematical foundation for the split target detection and tracking mechanism.The performance analysis is made under different simulation conditions to provide a clear insight into the merits of the proposed algorithm.The performance parameters in these simulations are the root mean square error(RMSE),confirmed true track rate(CTTR)and confirmed split true track rate(CSTTR).展开更多
Since the joint probabilistic data association(JPDA)algorithm results in calculation explosion with the increasing number of targets,a multi-target tracking algorithm based on Gaussian mixture model(GMM)clustering is ...Since the joint probabilistic data association(JPDA)algorithm results in calculation explosion with the increasing number of targets,a multi-target tracking algorithm based on Gaussian mixture model(GMM)clustering is proposed.The algorithm is used to cluster the measurements,and the association matrix between measurements and tracks is constructed by the posterior probability.Compared with the traditional data association algorithm,this algorithm has better tracking performance and less computational complexity.Simulation results demonstrate the effectiveness of the proposed algorithm.展开更多
There are many proposed optimal or suboptimal al- gorithms to update out-of-sequence measurement（s） （OoSM（s）） for linear-Gaussian systems, but few algorithms are dedicated to track a maneuvering target in clutte...There are many proposed optimal or suboptimal al- gorithms to update out-of-sequence measurement（s） （OoSM（s）） for linear-Gaussian systems, but few algorithms are dedicated to track a maneuvering target in clutter by using OoSMs. In order to address the nonlinear OoSMs obtained by the airborne radar located on a moving platform from a maneuvering target in clut- ter, an interacting multiple model probabilistic data association （IMMPDA） algorithm with the OoSM is developed. To be practical, the algorithm is based on the Earth-centered Earth-fixed （ECEF） coordinate system where it considers the effect of the platform＇s attitude and the curvature of the Earth. The proposed method is validated through the Monte Carlo test compared with the perfor- mance of the standard IMMPDA algorithm ignoring the OoSM, and the conclusions show that using the OoSM can improve the track- ing performance, and the shorter the lag step is, the greater degree the performance is improved, but when the lag step is large, the performance is not improved any more by using the OoSM, which can provide some references for engineering application.展开更多
The aim of this paper is to solve the problems of multitarget tracking in clutter. Firstly, the data association of measurement-to-target is formulated as an integer programming problem. Through using the linear progr...The aim of this paper is to solve the problems of multitarget tracking in clutter. Firstly, the data association of measurement-to-target is formulated as an integer programming problem. Through using the linear programming （LP） based branchand-bound method and adjusting the constraint conditions, an optimal set integer programming （OSIP） algorithm is then proposed for tracking multiple non-maneuvering targets in clutter. For the case of maneuvering targets, this paper introduces the OSIP algorithm into the filtering step of the interacting multiple model （IMM） algorithm resulting in the IMM based on OSIP algorithm. Extensive Monte Carlo simulations show that the presented algorithms can obtain superior estimations even in the case of high density noises.展开更多
An extension of 2-D assignment approach is proposed for measurement-to-target association for improving multiple targets vector miss distance measurement accuracy. When the multiple targets move so closely, the measur...An extension of 2-D assignment approach is proposed for measurement-to-target association for improving multiple targets vector miss distance measurement accuracy. When the multiple targets move so closely, the measurements can not be fully resolved due to finite resolution. The proposed method adopts an auction algorithm to compute the feasible measurement-to-target assignment with unresolved measurements for solving this 2-D assignment problem. Computer simulation results demonstrate the effectiveness and feasibility of this method.展开更多
The amplitude of frequency spectrum can he integrated with prohabilisfic data association （PDA） to distinguish the target with clutter echoes, especially in low SNR underwater environment. A new target-tracking algo...The amplitude of frequency spectrum can he integrated with prohabilisfic data association （PDA） to distinguish the target with clutter echoes, especially in low SNR underwater environment. A new target-tracking algorithm is presented which adopts the amplitude of frequency spectrum to improve target tracking in clutter. The prohabilisfic density distribution of frequency spectrum amplitude is analyzed. By simulation, the results show that the algorithm is superior to PDA. This approach enhances stability for the association probability and increases the performance of target tracking.展开更多
To avoid or reduce the influence of unpredictable motion mode on data association, a new computing method of weighted coefficients of measurements for PDAF is presented in which it is assumed that the current turn rat...To avoid or reduce the influence of unpredictable motion mode on data association, a new computing method of weighted coefficients of measurements for PDAF is presented in which it is assumed that the current turn rate of a maneuvering target changes within a limited range and its turn may be in arbitrary direction during data association. Thus, the predicted center for computing the weighted coefficients is a curved surface in 3-D space, which differs from the predicted center for setting up a validation gate, namely, a point in 3-D space. The distance between a measurement and the curved surface is used to compute its weighted coefficient. To reduce the computational complexity of weighted coefficients, the formulas for computing the maneuvering direction angle and turn rate corresponding to a measurement are presented. Simulation results show the proposed method reduces the percentage of lost tracks and improves the state estimation accuracy in tracking a maneuvering target using PDAF in the presence of clutter.展开更多
Usually, only the Cramer-Rao lower bound （CRLB） of single target is taken into consideration in the state estimate of passive tracking systems. As for the case of multitarget, there are few works done due to its com...Usually, only the Cramer-Rao lower bound （CRLB） of single target is taken into consideration in the state estimate of passive tracking systems. As for the case of multitarget, there are few works done due to its complexity. The recursion formula of the posterior Cramer-Rao lower bound （PCRLB） in multitarget bearings-only tracking with the three kinds of data association is presented. Meanwhile, computer simulation is carried out for data association. The final result shows that the accuracy probability of data association has an important impact on the PCRLB.展开更多
A new troubleshooting algorithm for solving assignment problem based on existing algorithms is proposed, and an analysis on the related theory is given. By applying the new troubleshooting algorithm to the Lagrange re...A new troubleshooting algorithm for solving assignment problem based on existing algorithms is proposed, and an analysis on the related theory is given. By applying the new troubleshooting algorithm to the Lagrange relaxation algorithm of the multi-dimensional assignment problem of data association for multi-passive-sensor multi-target location systems, and comparing the simulation results with that of the Hungarian algorithm which is the classical optimal solving algorithm, and the multi-layer ordersearching algorithm which is a sub-optimal solving algorithm, the performance and applying conditions of the new algorithm are summarized. Theory analysis and simulation results prove the effectiveness and superiority of the new algorithm.展开更多
基金Defense Advanced Research Project "the Techniques of Information Integrated Processing and Fusion" in the Eleventh Five-Year Plan (513060302).
文摘Joint probabilistic data association is an effective method for tracking multiple targets in clutter, but only the target kinematic information is used in measure-to-track association. If the kinematic likelihoods are similar for different closely spaced targets, there is ambiguity in using the kinematic information alone; the correct association probability will decrease in conventional joint probabilistic data association algorithm and track coalescence will occur easily. A modified algorithm of joint probabilistic data association with classification-aided is presented, which avoids track coalescence when tracking multiple neighboring targets. Firstly, an identification matrix is defined, which is used to simplify validation matrix to decrease computational complexity. Then, target class information is integrated into the data association process. Performance comparisons with and without the use of class information in JPDA are presented on multiple closely spaced maneuvering targets tracking problem. Simulation results quantify the benefits of classification-aided JPDA for improved multiple targets tracking, especially in the presence of association uncertainty in the kinematic measurement and target maneuvering. Simulation results indicate that the algorithm is valid.
基金This project was supported by the National Natural Science Foundation of China (60272024).
文摘A specialized Hungarian algorithm was developed here for the maximum likelihood data association problem with two implementation versions due to presence of false alarms and missed detections. The maximum likelihood data association problem is formulated as a bipartite weighted matching problem. Its duality and the optimality conditions are given. The Hungarian algorithm with its computational steps, data structure and computational complexity is presented. The two implementation versions, Hungarian forest （HF） algorithm and Hungarian tree （HT） algorithm, and their combination with the naYve auction initialization are discussed. The computational results show that HT algorithm is slightly faster than HF algorithm and they are both superior to the classic Munkres algorithm.
基金This project was supported by the National Natural Science Foundation of China (60172033) the Excellent Ph.D.PaperAuthor Foundation of China (200036 ,200237) .
文摘Aiming at three-passive-sensor location system, a generalized 3-dimension （3-D） assignment model is constructed based on property information, and a multi-target programming model is proposed based on direction-finding and property fusion information. The multi-target programming model is transformed into a single target programming problem to resolve, and its data association result is compared with the results which are solved by using one kind of information only. Simulation experiments show the effectiveness of the multi-target programming algorithm with higher data association accuracy and less calculation.
基金the Youth Science and Technology Foundection of University of Electronic Science andTechnology of China (JX0622).
文摘In most of the passive tracking systems, only the target kinematical information is used in the measurement-to-track association, which results in error tracking in a multitarget environment, where the targets are too close to each other. To enhance the tracking accuracy, the target signal classification information （TSCI） should be used to improve the data association. The TSCI is integrated in the data association process using the JPDA （joint probabilistic data association）. The use of the TSCI in the data association can improve discrimination by yielding a purer track and preserving continuity. To verify the validity of the application of TSCI, two simulation experiments are done on an air target-tracing problem, that is, one using the TSCI and the other not using the TSCI. The final comparison shows that the use of the TSCI can effectively improve tracking accuracy.
文摘Due to the advantages of ant colony optimization （ACO） in solving complex problems, a new data association algorithm based on ACO in a cluttered environment called DACDA is proposed. In the proposed method, the concept for tour and the length of tour are redefined. Additionally, the directional information is incorporated into the proposed method because it is one of the most important factors that affects the performance of data association. Kalman filter is employed to estimate target states. Computer simulation results show that the proposed method could carry out data association in an acceptable CPU time, and the correct data association rate is higher than that obtained by the data association （DA） algorithm not combined with directional information.
文摘In the re-entry phase of a ballistic missile,decoys can be deployed as a mean to overburden enemy defenses.This results in a single track being split into multiple track-lets.Tracking of these track-lets is a critical task as any miss in the tracking procedure can become a cause of a major threat.The tracking process becomes more complicated in the presence of clutter.The low detection rate is one of the factors that may contribute to increasing the difficulty level in terms of tracking in the cluttered environment.This work introduces a new algorithm for the split event detection and target tracking under the framework of the joint integrated probabilistic data association(JIPDA)algorithm.The proposed algorithm is termed as split event-JIPDA(SE-JIPDA).This work establishes the mathematical foundation for the split target detection and tracking mechanism.The performance analysis is made under different simulation conditions to provide a clear insight into the merits of the proposed algorithm.The performance parameters in these simulations are the root mean square error(RMSE),confirmed true track rate(CTTR)and confirmed split true track rate(CSTTR).
基金the National Natural Science Foundation of China(61771367)the Science and Technology on Communication Networks Laboratory(HHS19641X003).
文摘Since the joint probabilistic data association(JPDA)algorithm results in calculation explosion with the increasing number of targets,a multi-target tracking algorithm based on Gaussian mixture model(GMM)clustering is proposed.The algorithm is used to cluster the measurements,and the association matrix between measurements and tracks is constructed by the posterior probability.Compared with the traditional data association algorithm,this algorithm has better tracking performance and less computational complexity.Simulation results demonstrate the effectiveness of the proposed algorithm.
基金supported by the National Natural Science Foundation of China(61102168)
文摘There are many proposed optimal or suboptimal al- gorithms to update out-of-sequence measurement（s） （OoSM（s）） for linear-Gaussian systems, but few algorithms are dedicated to track a maneuvering target in clutter by using OoSMs. In order to address the nonlinear OoSMs obtained by the airborne radar located on a moving platform from a maneuvering target in clut- ter, an interacting multiple model probabilistic data association （IMMPDA） algorithm with the OoSM is developed. To be practical, the algorithm is based on the Earth-centered Earth-fixed （ECEF） coordinate system where it considers the effect of the platform＇s attitude and the curvature of the Earth. The proposed method is validated through the Monte Carlo test compared with the perfor- mance of the standard IMMPDA algorithm ignoring the OoSM, and the conclusions show that using the OoSM can improve the track- ing performance, and the shorter the lag step is, the greater degree the performance is improved, but when the lag step is large, the performance is not improved any more by using the OoSM, which can provide some references for engineering application.
基金supported by the National Natural Science Fundation of China (61203238 61134005+5 种基金 60921001 90916024 91116016)the National Basic Research Program of China (973 Program) (2012CB8212002012CB821201)the National Science Foundation for Postdoctoral Scientists of China (2012M520140)
文摘The aim of this paper is to solve the problems of multitarget tracking in clutter. Firstly, the data association of measurement-to-target is formulated as an integer programming problem. Through using the linear programming （LP） based branchand-bound method and adjusting the constraint conditions, an optimal set integer programming （OSIP） algorithm is then proposed for tracking multiple non-maneuvering targets in clutter. For the case of maneuvering targets, this paper introduces the OSIP algorithm into the filtering step of the interacting multiple model （IMM） algorithm resulting in the IMM based on OSIP algorithm. Extensive Monte Carlo simulations show that the presented algorithms can obtain superior estimations even in the case of high density noises.
文摘An extension of 2-D assignment approach is proposed for measurement-to-target association for improving multiple targets vector miss distance measurement accuracy. When the multiple targets move so closely, the measurements can not be fully resolved due to finite resolution. The proposed method adopts an auction algorithm to compute the feasible measurement-to-target assignment with unresolved measurements for solving this 2-D assignment problem. Computer simulation results demonstrate the effectiveness and feasibility of this method.
基金This project was supported by the Defense Pre-Research Project of the‘Tenth Five-Year-Plan’of China (40105010101)
文摘The amplitude of frequency spectrum can he integrated with prohabilisfic data association （PDA） to distinguish the target with clutter echoes, especially in low SNR underwater environment. A new target-tracking algorithm is presented which adopts the amplitude of frequency spectrum to improve target tracking in clutter. The prohabilisfic density distribution of frequency spectrum amplitude is analyzed. By simulation, the results show that the algorithm is superior to PDA. This approach enhances stability for the association probability and increases the performance of target tracking.
文摘To avoid or reduce the influence of unpredictable motion mode on data association, a new computing method of weighted coefficients of measurements for PDAF is presented in which it is assumed that the current turn rate of a maneuvering target changes within a limited range and its turn may be in arbitrary direction during data association. Thus, the predicted center for computing the weighted coefficients is a curved surface in 3-D space, which differs from the predicted center for setting up a validation gate, namely, a point in 3-D space. The distance between a measurement and the curved surface is used to compute its weighted coefficient. To reduce the computational complexity of weighted coefficients, the formulas for computing the maneuvering direction angle and turn rate corresponding to a measurement are presented. Simulation results show the proposed method reduces the percentage of lost tracks and improves the state estimation accuracy in tracking a maneuvering target using PDAF in the presence of clutter.
文摘Usually, only the Cramer-Rao lower bound （CRLB） of single target is taken into consideration in the state estimate of passive tracking systems. As for the case of multitarget, there are few works done due to its complexity. The recursion formula of the posterior Cramer-Rao lower bound （PCRLB） in multitarget bearings-only tracking with the three kinds of data association is presented. Meanwhile, computer simulation is carried out for data association. The final result shows that the accuracy probability of data association has an important impact on the PCRLB.
基金supported by the National Natural Science Foundation of China(61170161)the Natural Science Foundation of S handong (ZR2009GM002)the Technology Projects of Shandong University (J09LG01)
文摘A new troubleshooting algorithm for solving assignment problem based on existing algorithms is proposed, and an analysis on the related theory is given. By applying the new troubleshooting algorithm to the Lagrange relaxation algorithm of the multi-dimensional assignment problem of data association for multi-passive-sensor multi-target location systems, and comparing the simulation results with that of the Hungarian algorithm which is the classical optimal solving algorithm, and the multi-layer ordersearching algorithm which is a sub-optimal solving algorithm, the performance and applying conditions of the new algorithm are summarized. Theory analysis and simulation results prove the effectiveness and superiority of the new algorithm.
