Accurate target angle estimation is one of the chal-lenges for wideband radars due to the fact that target occupies multiple range bins,resulting in lower energy or signal to noise ratio in a single range bin.This pap...Accurate target angle estimation is one of the chal-lenges for wideband radars due to the fact that target occupies multiple range bins,resulting in lower energy or signal to noise ratio in a single range bin.This paper proposes a processing technique for enhanced accuracy of target angle estimates for wideband monopulse radars.Firstly,to accumulate the energy of the received echo signals from different scatterers on a target,the phase difference between different scatterers on a target is estimated using the minimum entropy phase estimation method combining with the correlation between adjacent pulses.Then,the monopulse ratio is obtained by using the signals from the accumulated sum and difference channels.The target angle is estimated by weighting the accumulated echo energy for accu-racy enhancement.Experimental results based on both numeri-cal simulation and measured data are presented to validate the effectiveness of the proposed technique.展开更多
An algorithm to track multiple sharply maneuvering targets without prior knowledge about new target birth is proposed. These targets are capable of achieving sharp maneuvers within a short period of time, such as dron...An algorithm to track multiple sharply maneuvering targets without prior knowledge about new target birth is proposed. These targets are capable of achieving sharp maneuvers within a short period of time, such as drones and agile missiles.The probability hypothesis density (PHD) filter, which propagates only the first-order statistical moment of the full target posterior, has been shown to be a computationally efficient solution to multitarget tracking problems. However, the standard PHD filter operates on the single dynamic model and requires prior information about target birth distribution, which leads to many limitations in terms of practical applications. In this paper,we introduce a nonzero mean, white noise turn rate dynamic model and generalize jump Markov systems to multitarget case to accommodate sharply maneuvering dynamics. Moreover, to adaptively estimate newborn targets’information, a measurement-driven method based on the recursive random sampling consensus (RANSAC) algorithm is proposed. Simulation results demonstrate that the proposed method achieves significant improvement in tracking multiple sharply maneuvering targets with adaptive birth estimation.展开更多
An algorithm of highly maneuvering target tracking is proposed to solve the problem of large tracking error caused by strong maneuver. In this algorithm, a new estimator, named as multi-parameter fusion Singer (MF-Sin...An algorithm of highly maneuvering target tracking is proposed to solve the problem of large tracking error caused by strong maneuver. In this algorithm, a new estimator, named as multi-parameter fusion Singer (MF-Singer) model is derived based on the Singer model and the fuzzy reasoning method by using radial acceleration and velocity of the target, and applied to the problem of maneuvering target tracking in strong maneuvering environment and operating environment. The tracking performance of the MF-Singer model is evaluated and compared with other manuevering tracking models. It is shown that the MF-Singer model outperforms these algorithms in several examples.展开更多
In the signal processing for metrewave radar, the reflection paths of target echoes can cause severe error in the elevation estimation for the low-angle target tracking. The exact angles of the reflection paths are un...In the signal processing for metrewave radar, the reflection paths of target echoes can cause severe error in the elevation estimation for the low-angle target tracking. The exact angles of the reflection paths are unknown beforehand, and therefore, the reflection paths can not be suppressed easily. Therefore, in this article, an improved reflection paths suppression approach is presented. A block matrix aggregate is constructed based on the possible angles of the reflection paths. Combined with the beamforming-like processing, a generalized maximum likelihood estimation is derived to optimize the estimation. Moreover, the noise reduction method based on the Toeplitz covariance matrix is used for better performance. This approach is applied to the real data collected by the low-angle tracking radar with 8-channel vertical array. The experiment results show that the reflection effects are reduced and the accuracy of the elevation estimate is improved.展开更多
Traditional monopulse radar cannot resolve two targets present in one range and Doppler cell by means of the monopulse ratio. A novel algorithm is proposed to estimate the directions of two steady targets with two pul...Traditional monopulse radar cannot resolve two targets present in one range and Doppler cell by means of the monopulse ratio. A novel algorithm is proposed to estimate the directions of two steady targets with two pulses. The algorithm has a closedform expression and its variance is derived at high signal-to-noise ratios（SNRs）. Furthermore, the pulse pair selection criterion and the estimation method with multiple pulses are given. Finally, some numerical results are shown to validate the proposed algorithm and the effect of slight target fluctuations is tested.展开更多
This paper analyzes the effect of waveform parame- ters on the joint target location and velocity estimation by a non- coherent multiple input multiple output （MIMO） radar transmitting multiple subcarriers signals. ...This paper analyzes the effect of waveform parame- ters on the joint target location and velocity estimation by a non- coherent multiple input multiple output （MIMO） radar transmitting multiple subcarriers signals. How the number of subcarriers in- fluences the estimation accuracy is illustrated by considering the joint Cramer-Rao bound and the mean square error of the maxi- mum likelihood estimate. The non-coherent MIMO radar ambiguity function with multiple subcarriers is developed and investigated by changing the number of subcarriers, the pulse width and the frequency spacing between adjacent subcarriers. The numerical results show that more subcarriers mean more accurate estimates, higher localization resolution, and larger pulse width results in a worse performance of target location estimation, while the fre- quency spacing affects target location estimation little.展开更多
The rotational parameters estimation of maneuvering target is the key of cross-range scaling of ISAR （inverse synthetic aperture radar）, which can be used in the target feature extraction. The cross-range signal mod...The rotational parameters estimation of maneuvering target is the key of cross-range scaling of ISAR （inverse synthetic aperture radar）, which can be used in the target feature extraction. The cross-range signal model of rotating target with fixed acceleration is presented and the weighted linear least squares estimation of rotational parameters with fixed velocity or acceleration is proposed via the relationship of cross-range FM （frequency modulation） parameter, scatterers coordinates and rotational parameters. The FM parameter is calculated via RWT （Radon-Wigner transform）. The ISAR imaging and cross-range scaling based on scaled RWT imaging method are implemented after obtaining rotational parameters. The rotational parameters estimation and cross-range scaling are validated by the ISAR processing of experimental radar data, and the method presents good application foreground to the ISAR imaging and scaling of maneuvering target.展开更多
For localisation of unknown non-cooperative targets in space,the existence of interference points causes inaccuracy of pose estimation while utilizing point cloud registration.To address this issue,this paper proposes...For localisation of unknown non-cooperative targets in space,the existence of interference points causes inaccuracy of pose estimation while utilizing point cloud registration.To address this issue,this paper proposes a new iterative closest point(ICP)algorithm combined with distributed weights to intensify the dependability and robustness of the non-cooperative target localisation.As interference points in space have not yet been extensively studied,we classify them into two broad categories,far interference points and near interference points.For the former,the statistical outlier elimination algorithm is employed.For the latter,the Gaussian distributed weights,simultaneously valuing with the variation of the Euclidean distance from each point to the centroid,are commingled to the traditional ICP algorithm.In each iteration,the weight matrix W in connection with the overall localisation is obtained,and the singular value decomposition is adopted to accomplish high-precision estimation of the target pose.Finally,the experiments are implemented by shooting the satellite model and setting the position of interference points.The outcomes suggest that the proposed algorithm can effectively suppress interference points and enhance the accuracy of non-cooperative target pose estimation.When the interference point number reaches about 700,the average error of angle is superior to 0.88°.展开更多
A credible method of calculating the detection threshold is presented for the multiple target situations, which appear frequently in the lower Doppler velocity region during the surveillance of sea with HF ground wave...A credible method of calculating the detection threshold is presented for the multiple target situations, which appear frequently in the lower Doppler velocity region during the surveillance of sea with HF ground wave radar. This method defines a whole-peak-outlier elimination （WPOE） criterion, which is based on in-peak-samples correlation of each target echo spectra, to trim off the target signals and abnormal disturbances with great amplitude from the complex spectra. Therefore, cleaned background noise samples are obtained to improve the accuracy and reliability of noise level estimation. When the background noise is nonhomogeneous, the detection samples are limited and often occupied heavily with outliers. In this case, the problem that the detection threshold is overvalued can be solved. In applications on experimental data, it is verified that this method can reduce the miss alarm rate of signal detection effectively in multiple target situations as well as make the adaptability of the detector better.展开更多
It is always a challenging issue for radar systems to estimate the height of a low-angle target in the multipath propagation environment.The highly deterministic maximum likelihood estimator has a high accuracy,but th...It is always a challenging issue for radar systems to estimate the height of a low-angle target in the multipath propagation environment.The highly deterministic maximum likelihood estimator has a high accuracy,but the errors of the ground reflection coefficient and the reflecting surface height have serious influence on the method.In this paper,a robust es-timation method with less computation burden is proposed based on the compound reflection coefficient multipath model for low-angle targets.The compound reflection coefficient is es-timated from the received data of the array and then a one-di-mension generalized steering vector is constructed to estimate the target height.The algorithm is robust to the reflecting sur-face height error and the ground reflection coefficient error.Fi-nally,the experiment and simulation results demonstrate the validity of the proposed method.展开更多
This paper presents augmented input estimation(AIE)for multiple maneuvering target tracking.Multi-target tracking(MTT)is based on two main parts,data association and estimation.In data association(DA),the best observa...This paper presents augmented input estimation(AIE)for multiple maneuvering target tracking.Multi-target tracking(MTT)is based on two main parts,data association and estimation.In data association(DA),the best observations are assigned to the considered tracks.In real conditions,the number of observations is more than targets and also locations of observations are often so scattered that the association between targets and observations cannot be done simply.In this case,for general MTT problems with unknown numbers of targets,we present a Markov chain Monte-Carlo DA(MCMCDA)algorithm that approximates the optimal Bayesian filter with low complexity in computations.After DA,estimation and tracking should be done.Since in general cases,many targets can have maneuvering motions,then AIE is proposed to cover both the non-maneuvering and maneuvering parts of motion and the maneuver detection procedure is eliminated.This model with an input estimation(IE)approach is a special augmentation in the state space model which considers both the state vector and the unknown input vector as a new augmented state vector.Some comparisons based on the Monte-Carlo simulations are also made to evaluate the performances of the proposed method and other older methods in MTT.展开更多
The accuracy of background clutter model is a key factor which determines the performance of a constant false alarm rate(CFAR) target detection method. G0 distribution is one of the optimal statistic models in the syn...The accuracy of background clutter model is a key factor which determines the performance of a constant false alarm rate(CFAR) target detection method. G0 distribution is one of the optimal statistic models in the synthetic aperture radar(SAR) image background clutter modeling and can accurately model various complex background clutters in the SAR images. But the application of the distribution is greatly limited by its disadvantages that the parameter estimation is complex and the local detection threshold is difficult to be obtained. In order to solve the above-mentioned problems, an synthetic aperture radar CFAR target detection method using the logarithmic cumulant(Mo LC) + method of moment(Mo M)-based G0 distribution clutter model is proposed. In the method, G0 distribution is used for modeling the background clutters, a new Mo LC+Mo M-based parameter estimation method coupled with a fast iterative algorithm is used for estimating the parameters of G0 distribution and an exquisite dichotomy method is used for obtaining the local detection threshold of CFAR detection, which greatly improves the computational efficiency, detection performance and environmental adaptability of CFAR detection. Experimental results show that the proposed SAR CFAR target detection method has good target detection performance in various complex background clutter environments.展开更多
Compared with single-domain unmanned swarms,cross-domain unmanned swarms continue to face new challenges in terms of platform performance and constraints.In this paper,a joint unmanned swarm target assignment and miss...Compared with single-domain unmanned swarms,cross-domain unmanned swarms continue to face new challenges in terms of platform performance and constraints.In this paper,a joint unmanned swarm target assignment and mission trajectory planning method is proposed to meet the requirements of cross-domain unmanned swarm mission planning.Firstly,the different performances of cross-domain heterogeneous platforms and mission requirements of targets are characterised by using a collection of operational resources.Secondly,an algorithmic framework for joint target assignment and mission trajectory planning is proposed,in which the initial planning of the trajectory is performed in the target assignment phase,while the trajectory is further optimised afterwards.Next,the estimation of the distribution algorithms is combined with the genetic algorithm to solve the objective function.Finally,the algorithm is numerically simulated by specific cases.Simulation results indicate that the proposed algorithm can perform effective task assignment and trajectory planning for cross-domain unmanned swarms.Furthermore,the solution performance of the hybrid estimation of distribution algorithm(EDA)-genetic algorithm(GA)algorithm is better than that of GA and EDA.展开更多
In an active radar-tracking system,the target-motion model is usually modeled in the Cartesian coordinates,while the radar measurement usually is obtained in polar/spherical coordinates.Therefore the target-tracking p...In an active radar-tracking system,the target-motion model is usually modeled in the Cartesian coordinates,while the radar measurement usually is obtained in polar/spherical coordinates.Therefore the target-tracking problem in the Cartesian coordinates becomes a nonlinear state estimation problem.A number of measurement-conversion techniques,which are based on position measurements,are widely used such that the Kalman filter can be used in the Cartesian coordinates.However,they have fundamental limitations to result in filtering performance degradation.In fact,in addition to position measurements,the Doppler measurement or range rate,containing information of target velocity,has the potential capability to improve the tracking performance.A filter is proposed that can use converted Doppler measurements（i.e.the product of the range measurements and Doppler measurements） in the Cartesian coordinates.The novel filter is theoretically optimal in the rule of the best linear unbiased estimation among all linear unbiased filters in the Cartesian coordinates,and is free of the fundamental limitations of the measurement-conversion approach.Based on simulation experiments,an approximate,recursive implementation of the novel filter is compared with those obtained by four state-of-the-art conversion techniques recently.Simulation results demonstrate the effectiveness of the proposed filter.展开更多
In some tracking applications,due to the sensor characteristic,only range measurements are available.If this is the case,due to the lack of full position measurements,the observability of Cartesian states(e.g.,positio...In some tracking applications,due to the sensor characteristic,only range measurements are available.If this is the case,due to the lack of full position measurements,the observability of Cartesian states(e.g.,position and velocity)are limited to particular cases.For general cases,the range measurements can be utilized by developing a state estimation algorithm in range-Doppler(R-D)plane to obtain accurate range and Doppler estimates.In this paper,a state estimation method based on the proper dynamic model in the R-D plane is proposed.The unscented Kalman filter is employed to handle the strong nonlinearity in the dynamic model.Two filtering initialization methods are derived to extract the initial state estimate and the initial covariance in the R-D plane from the first several range measurements.One is derived based on the well-known two-point differencing method.The other incorporates the correct dynamic model information and uses the unscented transformation method to obtain the initial state estimates and covariance,resulting in a model-based method,which capitalizes the model information to yield better performance.Monte Carlo simulation results are provided to illustrate the effectiveness and superior performance of the proposed state estimation and filter initialization methods.展开更多
A correlation tracking algorithm based on template partition motion estimation proposed for improving real time performance of the conventional correlation matching algorithms. The target trajectory fitted using the l...A correlation tracking algorithm based on template partition motion estimation proposed for improving real time performance of the conventional correlation matching algorithms. The target trajectory fitted using the least square with equal space in whole interval and the target prediction point is found out. According to the requirements of block motion estimation(BME) algorithm,the template divided into some macro blocks. The searching process is conducted by using diamond search algorithm around the prediction point and the optimal motion vector of each block is calculated. A point corresponding to the motion vector with the best matching is taken as a rough matching point of the template. The relation of relative position between the block with matching point and the searching area determined to decide whether to conduct precise matching search or to construct a new search area in the gradient direction. The target tracking experiment results show that over 70% time cost can be reduced caompared with the conventional correlation matching algorithm based on full search method.展开更多
A Target State Estimator (TSE) for airborne radar system is proposed in this paper. It is very important for fire control system to obtain accurate estimation of the maneuvering target and the TSE becomes a key link i...A Target State Estimator (TSE) for airborne radar system is proposed in this paper. It is very important for fire control system to obtain accurate estimation of the maneuvering target and the TSE becomes a key link in the integrated Flight/Fire Control (IFFC) system. By adopting the Cartesian coordinates and pseudomeasurements ,the result ed TSE has it s advantages in computation.In addition, by employing accurate range and range-rate redundant filter, the range direction estimations obtained in Cartesian filter are greatly improved. The TSE shows its satisfaCtory performance in the Monte Carlo simulation of the IFFC system.展开更多
In order to estimate the systematic error in the processof maneuvering target adaptive tracking, a new method is proposed.The proposed method is a linear tracking scheme basedon a modified input estimation approach. A...In order to estimate the systematic error in the processof maneuvering target adaptive tracking, a new method is proposed.The proposed method is a linear tracking scheme basedon a modified input estimation approach. A special augmentationin the state space model is considered, in which both the systematicerror and the unknown input vector are attached to thestate vector. Then, an augmented state model and a measurementmodel are established in the case of systematic error, andthe corresponding filter formulas are also given. In the proposedscheme, the original state, the acceleration and the systematicerror vector can be estimated simultaneously. This method can notonly solve the maneuvering target adaptive tracking problem in thecase of systematic error, but also give the system error value inreal time. Simulation results show that the proposed tracking algorithmoperates in both the non-maneuvering and the maneuveringmodes, and the original state, the acceleration and the systematicerror vector can be estimated simultaneously.展开更多
文摘Accurate target angle estimation is one of the chal-lenges for wideband radars due to the fact that target occupies multiple range bins,resulting in lower energy or signal to noise ratio in a single range bin.This paper proposes a processing technique for enhanced accuracy of target angle estimates for wideband monopulse radars.Firstly,to accumulate the energy of the received echo signals from different scatterers on a target,the phase difference between different scatterers on a target is estimated using the minimum entropy phase estimation method combining with the correlation between adjacent pulses.Then,the monopulse ratio is obtained by using the signals from the accumulated sum and difference channels.The target angle is estimated by weighting the accumulated echo energy for accu-racy enhancement.Experimental results based on both numeri-cal simulation and measured data are presented to validate the effectiveness of the proposed technique.
基金supported by the National Natural Science Foundation of China (61773142)。
文摘An algorithm to track multiple sharply maneuvering targets without prior knowledge about new target birth is proposed. These targets are capable of achieving sharp maneuvers within a short period of time, such as drones and agile missiles.The probability hypothesis density (PHD) filter, which propagates only the first-order statistical moment of the full target posterior, has been shown to be a computationally efficient solution to multitarget tracking problems. However, the standard PHD filter operates on the single dynamic model and requires prior information about target birth distribution, which leads to many limitations in terms of practical applications. In this paper,we introduce a nonzero mean, white noise turn rate dynamic model and generalize jump Markov systems to multitarget case to accommodate sharply maneuvering dynamics. Moreover, to adaptively estimate newborn targets’information, a measurement-driven method based on the recursive random sampling consensus (RANSAC) algorithm is proposed. Simulation results demonstrate that the proposed method achieves significant improvement in tracking multiple sharply maneuvering targets with adaptive birth estimation.
基金supported by the National Natural Science Foundation of China(6153102061471383)
文摘An algorithm of highly maneuvering target tracking is proposed to solve the problem of large tracking error caused by strong maneuver. In this algorithm, a new estimator, named as multi-parameter fusion Singer (MF-Singer) model is derived based on the Singer model and the fuzzy reasoning method by using radial acceleration and velocity of the target, and applied to the problem of maneuvering target tracking in strong maneuvering environment and operating environment. The tracking performance of the MF-Singer model is evaluated and compared with other manuevering tracking models. It is shown that the MF-Singer model outperforms these algorithms in several examples.
文摘In the signal processing for metrewave radar, the reflection paths of target echoes can cause severe error in the elevation estimation for the low-angle target tracking. The exact angles of the reflection paths are unknown beforehand, and therefore, the reflection paths can not be suppressed easily. Therefore, in this article, an improved reflection paths suppression approach is presented. A block matrix aggregate is constructed based on the possible angles of the reflection paths. Combined with the beamforming-like processing, a generalized maximum likelihood estimation is derived to optimize the estimation. Moreover, the noise reduction method based on the Toeplitz covariance matrix is used for better performance. This approach is applied to the real data collected by the low-angle tracking radar with 8-channel vertical array. The experiment results show that the reflection effects are reduced and the accuracy of the elevation estimate is improved.
文摘Traditional monopulse radar cannot resolve two targets present in one range and Doppler cell by means of the monopulse ratio. A novel algorithm is proposed to estimate the directions of two steady targets with two pulses. The algorithm has a closedform expression and its variance is derived at high signal-to-noise ratios（SNRs）. Furthermore, the pulse pair selection criterion and the estimation method with multiple pulses are given. Finally, some numerical results are shown to validate the proposed algorithm and the effect of slight target fluctuations is tested.
基金supported by the National Natural Science Foundation of China (60972152 61001153)the Aeronautics Science Foundation of China (2009ZC53031)
文摘This paper analyzes the effect of waveform parame- ters on the joint target location and velocity estimation by a non- coherent multiple input multiple output （MIMO） radar transmitting multiple subcarriers signals. How the number of subcarriers in- fluences the estimation accuracy is illustrated by considering the joint Cramer-Rao bound and the mean square error of the maxi- mum likelihood estimate. The non-coherent MIMO radar ambiguity function with multiple subcarriers is developed and investigated by changing the number of subcarriers, the pulse width and the frequency spacing between adjacent subcarriers. The numerical results show that more subcarriers mean more accurate estimates, higher localization resolution, and larger pulse width results in a worse performance of target location estimation, while the fre- quency spacing affects target location estimation little.
基金supported by the National Natural Science Foundation of China (60875019)
文摘The rotational parameters estimation of maneuvering target is the key of cross-range scaling of ISAR （inverse synthetic aperture radar）, which can be used in the target feature extraction. The cross-range signal model of rotating target with fixed acceleration is presented and the weighted linear least squares estimation of rotational parameters with fixed velocity or acceleration is proposed via the relationship of cross-range FM （frequency modulation） parameter, scatterers coordinates and rotational parameters. The FM parameter is calculated via RWT （Radon-Wigner transform）. The ISAR imaging and cross-range scaling based on scaled RWT imaging method are implemented after obtaining rotational parameters. The rotational parameters estimation and cross-range scaling are validated by the ISAR processing of experimental radar data, and the method presents good application foreground to the ISAR imaging and scaling of maneuvering target.
基金supported by the National Natural Science Foundation of China(51875535)the Natural Science Foundation for Young Scientists of Shanxi Province(201901D211242201701D221017)。
文摘For localisation of unknown non-cooperative targets in space,the existence of interference points causes inaccuracy of pose estimation while utilizing point cloud registration.To address this issue,this paper proposes a new iterative closest point(ICP)algorithm combined with distributed weights to intensify the dependability and robustness of the non-cooperative target localisation.As interference points in space have not yet been extensively studied,we classify them into two broad categories,far interference points and near interference points.For the former,the statistical outlier elimination algorithm is employed.For the latter,the Gaussian distributed weights,simultaneously valuing with the variation of the Euclidean distance from each point to the centroid,are commingled to the traditional ICP algorithm.In each iteration,the weight matrix W in connection with the overall localisation is obtained,and the singular value decomposition is adopted to accomplish high-precision estimation of the target pose.Finally,the experiments are implemented by shooting the satellite model and setting the position of interference points.The outcomes suggest that the proposed algorithm can effectively suppress interference points and enhance the accuracy of non-cooperative target pose estimation.When the interference point number reaches about 700,the average error of angle is superior to 0.88°.
文摘A credible method of calculating the detection threshold is presented for the multiple target situations, which appear frequently in the lower Doppler velocity region during the surveillance of sea with HF ground wave radar. This method defines a whole-peak-outlier elimination （WPOE） criterion, which is based on in-peak-samples correlation of each target echo spectra, to trim off the target signals and abnormal disturbances with great amplitude from the complex spectra. Therefore, cleaned background noise samples are obtained to improve the accuracy and reliability of noise level estimation. When the background noise is nonhomogeneous, the detection samples are limited and often occupied heavily with outliers. In this case, the problem that the detection threshold is overvalued can be solved. In applications on experimental data, it is verified that this method can reduce the miss alarm rate of signal detection effectively in multiple target situations as well as make the adaptability of the detector better.
基金supported by the National Natural Science Foundation of China(61771367)the Science and Technology on Communication Networks Laboratory(6142104190204).
文摘It is always a challenging issue for radar systems to estimate the height of a low-angle target in the multipath propagation environment.The highly deterministic maximum likelihood estimator has a high accuracy,but the errors of the ground reflection coefficient and the reflecting surface height have serious influence on the method.In this paper,a robust es-timation method with less computation burden is proposed based on the compound reflection coefficient multipath model for low-angle targets.The compound reflection coefficient is es-timated from the received data of the array and then a one-di-mension generalized steering vector is constructed to estimate the target height.The algorithm is robust to the reflecting sur-face height error and the ground reflection coefficient error.Fi-nally,the experiment and simulation results demonstrate the validity of the proposed method.
文摘This paper presents augmented input estimation(AIE)for multiple maneuvering target tracking.Multi-target tracking(MTT)is based on two main parts,data association and estimation.In data association(DA),the best observations are assigned to the considered tracks.In real conditions,the number of observations is more than targets and also locations of observations are often so scattered that the association between targets and observations cannot be done simply.In this case,for general MTT problems with unknown numbers of targets,we present a Markov chain Monte-Carlo DA(MCMCDA)algorithm that approximates the optimal Bayesian filter with low complexity in computations.After DA,estimation and tracking should be done.Since in general cases,many targets can have maneuvering motions,then AIE is proposed to cover both the non-maneuvering and maneuvering parts of motion and the maneuver detection procedure is eliminated.This model with an input estimation(IE)approach is a special augmentation in the state space model which considers both the state vector and the unknown input vector as a new augmented state vector.Some comparisons based on the Monte-Carlo simulations are also made to evaluate the performances of the proposed method and other older methods in MTT.
基金Project(61105020)supported by the National Natural Science Foundation of ChinaProject(13zxtk08)supported by the Key Research Platform for Research Projects of Southwest University of Science and Technology,China
文摘The accuracy of background clutter model is a key factor which determines the performance of a constant false alarm rate(CFAR) target detection method. G0 distribution is one of the optimal statistic models in the synthetic aperture radar(SAR) image background clutter modeling and can accurately model various complex background clutters in the SAR images. But the application of the distribution is greatly limited by its disadvantages that the parameter estimation is complex and the local detection threshold is difficult to be obtained. In order to solve the above-mentioned problems, an synthetic aperture radar CFAR target detection method using the logarithmic cumulant(Mo LC) + method of moment(Mo M)-based G0 distribution clutter model is proposed. In the method, G0 distribution is used for modeling the background clutters, a new Mo LC+Mo M-based parameter estimation method coupled with a fast iterative algorithm is used for estimating the parameters of G0 distribution and an exquisite dichotomy method is used for obtaining the local detection threshold of CFAR detection, which greatly improves the computational efficiency, detection performance and environmental adaptability of CFAR detection. Experimental results show that the proposed SAR CFAR target detection method has good target detection performance in various complex background clutter environments.
文摘Compared with single-domain unmanned swarms,cross-domain unmanned swarms continue to face new challenges in terms of platform performance and constraints.In this paper,a joint unmanned swarm target assignment and mission trajectory planning method is proposed to meet the requirements of cross-domain unmanned swarm mission planning.Firstly,the different performances of cross-domain heterogeneous platforms and mission requirements of targets are characterised by using a collection of operational resources.Secondly,an algorithmic framework for joint target assignment and mission trajectory planning is proposed,in which the initial planning of the trajectory is performed in the target assignment phase,while the trajectory is further optimised afterwards.Next,the estimation of the distribution algorithms is combined with the genetic algorithm to solve the objective function.Finally,the algorithm is numerically simulated by specific cases.Simulation results indicate that the proposed algorithm can perform effective task assignment and trajectory planning for cross-domain unmanned swarms.Furthermore,the solution performance of the hybrid estimation of distribution algorithm(EDA)-genetic algorithm(GA)algorithm is better than that of GA and EDA.
基金supported by the National Natural Science Foundation of China(5130712811571133)+1 种基金the National Natural Science Foundation of Hubei Province(2013CFB437)the Natural Science Foundation of School of Science(HJGSK2014G121)
文摘In an active radar-tracking system,the target-motion model is usually modeled in the Cartesian coordinates,while the radar measurement usually is obtained in polar/spherical coordinates.Therefore the target-tracking problem in the Cartesian coordinates becomes a nonlinear state estimation problem.A number of measurement-conversion techniques,which are based on position measurements,are widely used such that the Kalman filter can be used in the Cartesian coordinates.However,they have fundamental limitations to result in filtering performance degradation.In fact,in addition to position measurements,the Doppler measurement or range rate,containing information of target velocity,has the potential capability to improve the tracking performance.A filter is proposed that can use converted Doppler measurements（i.e.the product of the range measurements and Doppler measurements） in the Cartesian coordinates.The novel filter is theoretically optimal in the rule of the best linear unbiased estimation among all linear unbiased filters in the Cartesian coordinates,and is free of the fundamental limitations of the measurement-conversion approach.Based on simulation experiments,an approximate,recursive implementation of the novel filter is compared with those obtained by four state-of-the-art conversion techniques recently.Simulation results demonstrate the effectiveness of the proposed filter.
基金This work was supported by the National Natural Science Foundation of China(61671181,62101162).
文摘In some tracking applications,due to the sensor characteristic,only range measurements are available.If this is the case,due to the lack of full position measurements,the observability of Cartesian states(e.g.,position and velocity)are limited to particular cases.For general cases,the range measurements can be utilized by developing a state estimation algorithm in range-Doppler(R-D)plane to obtain accurate range and Doppler estimates.In this paper,a state estimation method based on the proper dynamic model in the R-D plane is proposed.The unscented Kalman filter is employed to handle the strong nonlinearity in the dynamic model.Two filtering initialization methods are derived to extract the initial state estimate and the initial covariance in the R-D plane from the first several range measurements.One is derived based on the well-known two-point differencing method.The other incorporates the correct dynamic model information and uses the unscented transformation method to obtain the initial state estimates and covariance,resulting in a model-based method,which capitalizes the model information to yield better performance.Monte Carlo simulation results are provided to illustrate the effectiveness and superior performance of the proposed state estimation and filter initialization methods.
基金Sponsored by the National Defense Pre-Research Foundation of China
文摘A correlation tracking algorithm based on template partition motion estimation proposed for improving real time performance of the conventional correlation matching algorithms. The target trajectory fitted using the least square with equal space in whole interval and the target prediction point is found out. According to the requirements of block motion estimation(BME) algorithm,the template divided into some macro blocks. The searching process is conducted by using diamond search algorithm around the prediction point and the optimal motion vector of each block is calculated. A point corresponding to the motion vector with the best matching is taken as a rough matching point of the template. The relation of relative position between the block with matching point and the searching area determined to decide whether to conduct precise matching search or to construct a new search area in the gradient direction. The target tracking experiment results show that over 70% time cost can be reduced caompared with the conventional correlation matching algorithm based on full search method.
文摘A Target State Estimator (TSE) for airborne radar system is proposed in this paper. It is very important for fire control system to obtain accurate estimation of the maneuvering target and the TSE becomes a key link in the integrated Flight/Fire Control (IFFC) system. By adopting the Cartesian coordinates and pseudomeasurements ,the result ed TSE has it s advantages in computation.In addition, by employing accurate range and range-rate redundant filter, the range direction estimations obtained in Cartesian filter are greatly improved. The TSE shows its satisfaCtory performance in the Monte Carlo simulation of the IFFC system.
基金supported by the National Natural Science Foundation of China(91538201)
文摘In order to estimate the systematic error in the processof maneuvering target adaptive tracking, a new method is proposed.The proposed method is a linear tracking scheme basedon a modified input estimation approach. A special augmentationin the state space model is considered, in which both the systematicerror and the unknown input vector are attached to thestate vector. Then, an augmented state model and a measurementmodel are established in the case of systematic error, andthe corresponding filter formulas are also given. In the proposedscheme, the original state, the acceleration and the systematicerror vector can be estimated simultaneously. This method can notonly solve the maneuvering target adaptive tracking problem in thecase of systematic error, but also give the system error value inreal time. Simulation results show that the proposed tracking algorithmoperates in both the non-maneuvering and the maneuveringmodes, and the original state, the acceleration and the systematicerror vector can be estimated simultaneously.
