Perception and manipulation tasks for robotic manipulators involving highly-cluttered objects have become increasingly indemand for achieving a more efficient problem solving method in modern industrial environments.B...Perception and manipulation tasks for robotic manipulators involving highly-cluttered objects have become increasingly indemand for achieving a more efficient problem solving method in modern industrial environments.But,most of the available methods for performing such cluttered tasks failed in terms of performance,mainly due to inability to adapt to the change of the environment and the handled objects.Here,we propose a new,near real-time approach to suction-based grasp point estimation in a highly cluttered environment by employing an affordance-based approach.Compared to the state-of-the-art,our proposed method offers two distinctive contributions.First,we use a modified deep neural network backbone for the input of the semantic segmentation,to classify pixel elements of the input red,green,blue and depth(RGBD)channel image which is then used to produce an affordance map,a pixel-wise probability map representing the probability of a successful grasping action in those particular pixel regions.Later,we incorporate a high speed semantic segmentation to the system,which makes our solution have a lower computational time.This approach does not need to have any prior knowledge or models of the objects since it removes the step of pose estimation and object recognition entirely compared to most of the current approaches and uses an assumption to grasp first then recognize later,which makes it possible to have an object-agnostic property.The system was designed to be used for household objects,but it can be easily extended to any kind of objects provided that the right dataset is used for training the models.Experimental results show the benefit of our approach which achieves a precision of 88.83%,compared to the 83.4%precision of the current state-of-the-art.展开更多
This paper proposed an autonomous planning,navigation and control framework for lightweight unmanned aerial vehicles(UAVs)in obstacle-dense environments with limited computational resources.The framework employed a po...This paper proposed an autonomous planning,navigation and control framework for lightweight unmanned aerial vehicles(UAVs)in obstacle-dense environments with limited computational resources.The framework employed a polynomial-based minimum-snap trajectory generation method to ensure obstacle-free in confined three-dimensional(3D)spaces.A gradient-based trajectory optimization strategy integrated smoothness constraints,collision avoidance and dynamic feasibility was proposed to ensure safety and motion smoothness.The model predictive control(MPC)method was utilized to enhance the trajectory tracking ability of UAVs by reconciling the optimized reference path with real-time sensory inputs.Simulations and outdoor flight experiments demonstrated the effectiveness of the proposed framework.展开更多
Accurate modeling and parameter estimation of sea clutter are fundamental for effective sea surface target detection.With the improvement of radar resolution,sea clutter exhibits a pronounced heavy-tailed characterist...Accurate modeling and parameter estimation of sea clutter are fundamental for effective sea surface target detection.With the improvement of radar resolution,sea clutter exhibits a pronounced heavy-tailed characteristic,rendering traditional distribution models and parameter estimation methods less effective.To address this,this paper proposes a dual compound-Gaussian model with inverse Gaussian texture(CG-IG)distribution model and combines it with an improved Adam algorithm to introduce a method for parameter correction.This method effectively fits sea clutter with heavy-tailed characteristics.Experiments with real measured sea clutter data show that the dual CGIG distribution model,after parameter correction,accurately describes the heavy-tailed phenomenon in sea clutter amplitude distribution,and the overall mean square error of the distribution is reduced.展开更多
To address the issues of unknown target size,blurred edges,background interference and low contrast in infrared small target detection,this paper proposes a method based on density peaks searching and weighted multi-f...To address the issues of unknown target size,blurred edges,background interference and low contrast in infrared small target detection,this paper proposes a method based on density peaks searching and weighted multi-feature local difference.Firstly,an improved high-boost filter is used for preprocessing to eliminate background clutter and high-brightness interference,thereby increasing the probability of capturing real targets in the density peak search.Secondly,a triple-layer window is used to extract features from the area surrounding candidate targets,addressing the uncertainty of small target sizes.By calculating multi-feature local differences between the triple-layer windows,the problems of blurred target edges and low contrast are resolved.To balance the contribution of different features,intra-class distance is used to calculate weights,achieving weighted fusion of multi-feature local differences to obtain the weighted multi-feature local differences of candidate targets.The real targets are then extracted using the interquartile range.Experiments on datasets such as SIRST and IRSTD-IK show that the proposed method is suitable for various complex types and demonstrates good robustness and detection performance.展开更多
Life science research aims to continuously improve the quality and standard of human life. One of the major challenges in this area is to maintain food safety and security. A number of image processing techniques have...Life science research aims to continuously improve the quality and standard of human life. One of the major challenges in this area is to maintain food safety and security. A number of image processing techniques have been used to investigate the quality of food products. In this paper, we propose a new algorithm to effectively segment connected grains so that each of them can be inspected in a later processing stage. One family of the existing segmentation methods is based on the idea of watersheding, and it has shown promising results in practice. However, due to the over-segmentation issue, this technique has experienced poor performance in various applications, such as inhomogeneous background and connected targets. To solve this problem, we present a combination of two classical techniques to handle this issue. In the first step, a mean shift filter is used to eliminate the inhomogeneous background,where entropy is used to be a converging criterion. Secondly, a color gradient algorithm is used in order to detect the most significant edges, and a marked watershed transform is applied to segment cluttered objects out of the previous processing stages. The proposed framework is capable of compromising among execution time, usability, efficiency and segmentation outcome in analyzing ring die pellets. The experimental results demonstrate that the proposed approach is effectiveness and robust.展开更多
The detection and ima ging of moving targets based on airborne synthetic aperture radar (SAR) is a cru cial technique for the modern radar. Firstly, the mathematical model of SAR ech o signal which comes from moving t...The detection and ima ging of moving targets based on airborne synthetic aperture radar (SAR) is a cru cial technique for the modern radar. Firstly, the mathematical model of SAR ech o signal which comes from moving targets is constructed. Based on this model, th e features of moving target imaging are introduced and the effects of target mov ement to SAR imaging are analyzed. Then the development and the status of this t echnique are reviewed in detail. Finally, some frontiers of this field are point ed out.展开更多
The desire to speed up secondary storage systems has lead to the development of redundant arrays of independent disks （RAID） which incorporate redundancy utilizing erasure codes. A ＇cluttered ordering＇ is utilized...The desire to speed up secondary storage systems has lead to the development of redundant arrays of independent disks （RAID） which incorporate redundancy utilizing erasure codes. A ＇cluttered ordering＇ is utilized for designing an effective writing order to a RAID system. Cohen, Colboum and Froncek （2001） gave a cyclic construction of cluttered orderings for the complete graph by utilizing the notion of a ＇wrapped p-labelling＇. Since wrapped p-labellings as cluttered orderings for the complete graph look such as ladders, they are also called as ladder orderings. Cohen and Colboum （2004） gave a characteristic of ladder orderings. In this paper, we give an algorithm in order to generate ladder orderings.展开更多
The design of large disk array architectures leads to interesting combinatorial problems. Minimizing the number of disk operations when writing to consecutive disks leads to the concept of “cluttered orderings” whic...The design of large disk array architectures leads to interesting combinatorial problems. Minimizing the number of disk operations when writing to consecutive disks leads to the concept of “cluttered orderings” which were introduced for the complete graph by Cohen et al. (2001). Mueller et al. (2005) adapted the concept of wrapped Δ-labellings to the complete bipartite case. In this paper, we give some sequence in order to generate wrapped Δ-labellings as cluttered orderings for the complete bipartite graph. New sequence we give is different from the sequences Mueller et al. gave, though the same graphs in which these sequences are labeled.展开更多
Robotic grasps play an important role in the service and industrial fields,and the robotic arm can grasp the object properly depends on the accuracy of the grasping detection result.In order to predict grasping detect...Robotic grasps play an important role in the service and industrial fields,and the robotic arm can grasp the object properly depends on the accuracy of the grasping detection result.In order to predict grasping detection positions for known or unknown objects by a modular robotic system,a convolutional neural network(CNN)with the residual block is proposed,which can be used to generate accurate grasping detection for input images of the scene.The proposed model architecture was trained on the standard Cornell grasp dataset and evaluated on the test dataset.Moreover,it was evaluated on different types of household objects and cluttered multi-objects.On the Cornell grasp dataset,the accuracy of the model on image-wise splitting detection and object-wise splitting detection achieved 95.5%and 93.6%,respectively.Further,the real detection time per image was 109 ms.The experimental results show that the model can quickly detect the grasping positions of a single object or multiple objects in image pixels in real time,and it keeps good stability and robustness.展开更多
This paper presents a new kernel-based algorithm for video object tracking called rebound of region of interest (RROI). The novel algorithm uses a rectangle-shaped section as region of interest (ROI) to represent and ...This paper presents a new kernel-based algorithm for video object tracking called rebound of region of interest (RROI). The novel algorithm uses a rectangle-shaped section as region of interest (ROI) to represent and track specific objects in videos. The proposed algorithm is constituted by two stages. The first stage seeks to determine the direction of the object’s motion by analyzing the changing regions around the object being tracked between two consecutive frames. Once the direction of the object’s motion has been predicted, it is initialized an iterative process that seeks to minimize a function of dissimilarity in order to find the location of the object being tracked in the next frame. The main advantage of the proposed algorithm is that, unlike existing kernel-based methods, it is immune to highly cluttered conditions. The results obtained by the proposed algorithm show that the tracking process was successfully carried out for a set of color videos with different challenging conditions such as occlusion, illumination changes, cluttered conditions, and object scale changes.展开更多
GPR has become an important geophysical method in UXO and landmine detection, for it can detect both metal and non-metallic targets. However, it is difficult to remove the strong clutters from surface-layer reflection...GPR has become an important geophysical method in UXO and landmine detection, for it can detect both metal and non-metallic targets. However, it is difficult to remove the strong clutters from surface-layer reflection and soil due to the low signal to noise ratio of GPR data. In this paper, we use the adaptive chirplet transform to reject these clutters based on their character and then pick up the signal from the UXO by the transform based on the Radon-Wigner distribution. The results from the processing show that the clutter can be rejected effectively and the target response can be measured with high SNR.展开更多
The high resolution radar target detection is addressed in the non-Gaussian clutter.An adaptive detector is derived for range-spread target based on a novel covariance matrix estimator.It is proved that the new detect...The high resolution radar target detection is addressed in the non-Gaussian clutter.An adaptive detector is derived for range-spread target based on a novel covariance matrix estimator.It is proved that the new detector is constant false alarm rate(CFAR)to both of the clutter covariance matrix structure and power level theoretically for match cases.The simulation results show that the new detector is almost CFAR for mismatch cases,and it outperforms the existing adaptive detector based on the sample covariance matrix.It also shows that the detection performance improves,as the number of pulses,the number of secondary data or the clutter spike increases.In addition,the derived detector is robust to different subsets,estimated clutter group sizes and correlations of clutter.Importantly,the number of iterations for practical application is just one.展开更多
Measurement of shipborne radar sea echo is instrumental in collecting the sea clutter data in open sea areas.However,the ship movement would introduce an extra Doppler component into the spectrum of the sea clutter,so...Measurement of shipborne radar sea echo is instrumental in collecting the sea clutter data in open sea areas.However,the ship movement would introduce an extra Doppler component into the spectrum of the sea clutter,so the sea clutter inherent spectrum must be estimated prior to investigating the sea clutter Doppler characteristics from the shipborne radar sea echo.In this paper we show some results about a shipborne sea clutter measurement experiment that was conducted in the South China Sea in a period between 2017 and 2018;abundant clutter data have been collected by using a shipborne S-band clutter measurement radar.To obtain the sea clutter inherent Doppler spectrum from these data,an estimation method,based on the mapping relationship between the shipborne clutter spectrum and the inherent clutter spectrum,is proposed.This method is validated by shipborne clutter data sets under the same measuring conditions except for the ship speed.Using this method,the characteristics of the Doppler spectrum lineshapes in the South China Sea are calculated and analyzed according to different sea states,wave directions,and radar resolutions,which can be instrumental in designing the radar target detection algorithms.展开更多
A novel efficient track initiation method is proposed for the harsh underwater target tracking environment(heavy clutter and large measurement errors): track splitting, evaluating, pruning and merging method(TSEPM). T...A novel efficient track initiation method is proposed for the harsh underwater target tracking environment(heavy clutter and large measurement errors): track splitting, evaluating, pruning and merging method(TSEPM). Track initiation demands that the method should determine the existence and initial state of a target quickly and correctly.Heavy clutter and large measurement errors certainly pose additional difficulties and challenges, which deteriorate and complicate the track initiation in the harsh underwater target tracking environment. There are three primary shortcomings for the current track initiation methods to initialize a target:(a) they cannot eliminate the turbulences of clutter effectively;(b) there may be a high false alarm probability and low detection probability of a track;(c) they cannot estimate the initial state for a new confirmed track correctly. Based on the multiple hypotheses tracking principle and modified logic-based track initiation method, in order to increase the detection probability of a track,track splitting creates a large number of tracks which include the true track originated from the target. And in order to decrease the false alarm probability, based on the evaluation mechanism, track pruning and track merging are proposed to reduce the false tracks. TSEPM method can deal with the track initiation problems derived from heavy clutter and large measurement errors, determine the target’s existence and estimate its initial state with the least squares method. What’s more, our method is fully automatic and does not require any kind manual input for initializing and tuning any parameter. Simulation results indicate that our new method improves significantly the performance of the track initiation in the harsh underwater target tracking environment.展开更多
In this paper,a comprehensive overview of radar detection methods for low-altitude targets in maritime environments is presented,focusing on the challenges posed by sea clutter and multipath scattering.The performance...In this paper,a comprehensive overview of radar detection methods for low-altitude targets in maritime environments is presented,focusing on the challenges posed by sea clutter and multipath scattering.The performance of the radar detection methods under sea clutter,multipath,and combined conditions is categorized and summarized,and future research directions are outlined to enhance radar detection performance for low-altitude targets in maritime environments.展开更多
Based on the target scatterer density, the range-spread target detection of high-resolution radar is addressed in additive non-Gaussian clutter, which is modeled as a spherically invariant random vector. Firstly, for ...Based on the target scatterer density, the range-spread target detection of high-resolution radar is addressed in additive non-Gaussian clutter, which is modeled as a spherically invariant random vector. Firstly, for sparse scatterer density, the detection of target scatterer in each range cell is derived, and then an M/K detector is proposed to detect the whole range-spread target. Se- condly, an integrating detector is devised to detect a range-spread target with dense scatterer density. Finally, to make the best of the advantages of M/K detector and integrating detector, a robust detector based on scatterer density （DBSD） is designed, which can reduce the probable collapsing loss or quantization error ef- fectively. Moreover, the density decision factor of DBSD is also determined. The formula of the false alarm probability is derived for DBSD. It is proved that the DBSD ensures a constant false alarm rate property. Furthermore, the computational results indi- cate that the DBSD is robust to different clutter one-lag correlations and target scatterer densities. It is also shown that the DBSD out- performs the existing scatterer-density-dependent detector.展开更多
With the increment of the number of Gaussian components, the computation cost increases in the Gaussian mixture probability hypothesis density(GM-PHD) filter. Based on the theory of Chen et al, we propose an improved ...With the increment of the number of Gaussian components, the computation cost increases in the Gaussian mixture probability hypothesis density(GM-PHD) filter. Based on the theory of Chen et al, we propose an improved pruning algorithm for the GM-PHD filter, which utilizes not only the Gaussian components’ means and covariance, but their weights as a new criterion to improve the estimate accuracy of the conventional pruning algorithm for tracking very closely proximity targets. Moreover, it solves the end-less while-loop problem without the need of a second merging step. Simulation results show that this improved algorithm is easier to implement and more robust than the formal ones.展开更多
Airborne Distributed Coherent Aperture Radar(ADCAR)is one of the most promising next-generation radars to significantly improve target detection and discrimination abilities.However,time and phase synchronization amon...Airborne Distributed Coherent Aperture Radar(ADCAR)is one of the most promising next-generation radars to significantly improve target detection and discrimination abilities.However,time and phase synchronization among unit radars should be done before an ADCAR is intended to cohere on a potential target.To address this problem,a time and phase synchronization technique using clutter observations is proposed in this paper.Clutter returns from different azimuths and elevations on the surface of the earth are employed to calibrate system uncertainties.Two stages are mainly considered:a scene registration among range-Doppler units from different transmit/receive pairs is performed to enhance the clutter coherence in the first stage,followed by a joint estimation of those synchronization errors in the second stage.To relieve the computational burden,a novel Separable and Sequential Estimation(SSE)method is provided to separate the unknowns at the sacrifice of a range-Doppler unit.Moreover,performance analyses including the clutter coherence ability,estimation lower bound,and signal coherence loss are also performed.Finally,simulation results indicate that ADCAR time and phase synchronization is realized by using our methods.展开更多
The estimation of lower atmospheric refractivity from radar sea clutter（RFC） is a complicated nonlinear optimization problem.This paper deals with the RFC problem in a Bayesian framework.It uses the unbiased Markov ...The estimation of lower atmospheric refractivity from radar sea clutter（RFC） is a complicated nonlinear optimization problem.This paper deals with the RFC problem in a Bayesian framework.It uses the unbiased Markov Chain Monte Carlo（MCMC） sampling technique,which can provide accurate posterior probability distributions of the estimated refractivity parameters by using an electromagnetic split-step fast Fourier transform terrain parabolic equation propagation model within a Bayesian inversion framework.In contrast to the global optimization algorithm,the Bayesian-MCMC can obtain not only the approximate solutions,but also the probability distributions of the solutions,that is,uncertainty analyses of solutions.The Bayesian-MCMC algorithm is implemented on the simulation radar sea-clutter data and the real radar seaclutter data.Reference data are assumed to be simulation data and refractivity profiles are obtained using a helicopter.The inversion algorithm is assessed（i） by comparing the estimated refractivity profiles from the assumed simulation and the helicopter sounding data;（ii） the one-dimensional（1D） and two-dimensional（2D） posterior probability distribution of solutions.展开更多
文摘Perception and manipulation tasks for robotic manipulators involving highly-cluttered objects have become increasingly indemand for achieving a more efficient problem solving method in modern industrial environments.But,most of the available methods for performing such cluttered tasks failed in terms of performance,mainly due to inability to adapt to the change of the environment and the handled objects.Here,we propose a new,near real-time approach to suction-based grasp point estimation in a highly cluttered environment by employing an affordance-based approach.Compared to the state-of-the-art,our proposed method offers two distinctive contributions.First,we use a modified deep neural network backbone for the input of the semantic segmentation,to classify pixel elements of the input red,green,blue and depth(RGBD)channel image which is then used to produce an affordance map,a pixel-wise probability map representing the probability of a successful grasping action in those particular pixel regions.Later,we incorporate a high speed semantic segmentation to the system,which makes our solution have a lower computational time.This approach does not need to have any prior knowledge or models of the objects since it removes the step of pose estimation and object recognition entirely compared to most of the current approaches and uses an assumption to grasp first then recognize later,which makes it possible to have an object-agnostic property.The system was designed to be used for household objects,but it can be easily extended to any kind of objects provided that the right dataset is used for training the models.Experimental results show the benefit of our approach which achieves a precision of 88.83%,compared to the 83.4%precision of the current state-of-the-art.
基金supported by the National Natural Science Foundation of China(No.62403025)the Basic Science Center Program of the National Natural Science Foundation of China(No.62388101)
文摘This paper proposed an autonomous planning,navigation and control framework for lightweight unmanned aerial vehicles(UAVs)in obstacle-dense environments with limited computational resources.The framework employed a polynomial-based minimum-snap trajectory generation method to ensure obstacle-free in confined three-dimensional(3D)spaces.A gradient-based trajectory optimization strategy integrated smoothness constraints,collision avoidance and dynamic feasibility was proposed to ensure safety and motion smoothness.The model predictive control(MPC)method was utilized to enhance the trajectory tracking ability of UAVs by reconciling the optimized reference path with real-time sensory inputs.Simulations and outdoor flight experiments demonstrated the effectiveness of the proposed framework.
文摘Accurate modeling and parameter estimation of sea clutter are fundamental for effective sea surface target detection.With the improvement of radar resolution,sea clutter exhibits a pronounced heavy-tailed characteristic,rendering traditional distribution models and parameter estimation methods less effective.To address this,this paper proposes a dual compound-Gaussian model with inverse Gaussian texture(CG-IG)distribution model and combines it with an improved Adam algorithm to introduce a method for parameter correction.This method effectively fits sea clutter with heavy-tailed characteristics.Experiments with real measured sea clutter data show that the dual CGIG distribution model,after parameter correction,accurately describes the heavy-tailed phenomenon in sea clutter amplitude distribution,and the overall mean square error of the distribution is reduced.
基金supported by the National Natural Science Foundation of China (No.52205548)。
文摘To address the issues of unknown target size,blurred edges,background interference and low contrast in infrared small target detection,this paper proposes a method based on density peaks searching and weighted multi-feature local difference.Firstly,an improved high-boost filter is used for preprocessing to eliminate background clutter and high-brightness interference,thereby increasing the probability of capturing real targets in the density peak search.Secondly,a triple-layer window is used to extract features from the area surrounding candidate targets,addressing the uncertainty of small target sizes.By calculating multi-feature local differences between the triple-layer windows,the problems of blurred target edges and low contrast are resolved.To balance the contribution of different features,intra-class distance is used to calculate weights,achieving weighted fusion of multi-feature local differences to obtain the weighted multi-feature local differences of candidate targets.The real targets are then extracted using the interquartile range.Experiments on datasets such as SIRST and IRSTD-IK show that the proposed method is suitable for various complex types and demonstrates good robustness and detection performance.
基金supported by National Key Scientific Apparatus Development of Special Item of China(No.2012YQ15008703)Nantong Research Program of Application Foundation(No.BK2012030)Key Project of Science and Technology Commission of Shanghai Municipality(No.14JC1402200)
文摘Life science research aims to continuously improve the quality and standard of human life. One of the major challenges in this area is to maintain food safety and security. A number of image processing techniques have been used to investigate the quality of food products. In this paper, we propose a new algorithm to effectively segment connected grains so that each of them can be inspected in a later processing stage. One family of the existing segmentation methods is based on the idea of watersheding, and it has shown promising results in practice. However, due to the over-segmentation issue, this technique has experienced poor performance in various applications, such as inhomogeneous background and connected targets. To solve this problem, we present a combination of two classical techniques to handle this issue. In the first step, a mean shift filter is used to eliminate the inhomogeneous background,where entropy is used to be a converging criterion. Secondly, a color gradient algorithm is used in order to detect the most significant edges, and a marked watershed transform is applied to segment cluttered objects out of the previous processing stages. The proposed framework is capable of compromising among execution time, usability, efficiency and segmentation outcome in analyzing ring die pellets. The experimental results demonstrate that the proposed approach is effectiveness and robust.
文摘The detection and ima ging of moving targets based on airborne synthetic aperture radar (SAR) is a cru cial technique for the modern radar. Firstly, the mathematical model of SAR ech o signal which comes from moving targets is constructed. Based on this model, th e features of moving target imaging are introduced and the effects of target mov ement to SAR imaging are analyzed. Then the development and the status of this t echnique are reviewed in detail. Finally, some frontiers of this field are point ed out.
文摘The desire to speed up secondary storage systems has lead to the development of redundant arrays of independent disks （RAID） which incorporate redundancy utilizing erasure codes. A ＇cluttered ordering＇ is utilized for designing an effective writing order to a RAID system. Cohen, Colboum and Froncek （2001） gave a cyclic construction of cluttered orderings for the complete graph by utilizing the notion of a ＇wrapped p-labelling＇. Since wrapped p-labellings as cluttered orderings for the complete graph look such as ladders, they are also called as ladder orderings. Cohen and Colboum （2004） gave a characteristic of ladder orderings. In this paper, we give an algorithm in order to generate ladder orderings.
文摘The design of large disk array architectures leads to interesting combinatorial problems. Minimizing the number of disk operations when writing to consecutive disks leads to the concept of “cluttered orderings” which were introduced for the complete graph by Cohen et al. (2001). Mueller et al. (2005) adapted the concept of wrapped Δ-labellings to the complete bipartite case. In this paper, we give some sequence in order to generate wrapped Δ-labellings as cluttered orderings for the complete bipartite graph. New sequence we give is different from the sequences Mueller et al. gave, though the same graphs in which these sequences are labeled.
基金National Natural Science Foundation of China(No.52101346)Fundamental Research Funds for the Central Universities,China(No.2232019D3-61)Initial Research Fund for the Young Teachers of Donghua University,China。
文摘Robotic grasps play an important role in the service and industrial fields,and the robotic arm can grasp the object properly depends on the accuracy of the grasping detection result.In order to predict grasping detection positions for known or unknown objects by a modular robotic system,a convolutional neural network(CNN)with the residual block is proposed,which can be used to generate accurate grasping detection for input images of the scene.The proposed model architecture was trained on the standard Cornell grasp dataset and evaluated on the test dataset.Moreover,it was evaluated on different types of household objects and cluttered multi-objects.On the Cornell grasp dataset,the accuracy of the model on image-wise splitting detection and object-wise splitting detection achieved 95.5%and 93.6%,respectively.Further,the real detection time per image was 109 ms.The experimental results show that the model can quickly detect the grasping positions of a single object or multiple objects in image pixels in real time,and it keeps good stability and robustness.
文摘This paper presents a new kernel-based algorithm for video object tracking called rebound of region of interest (RROI). The novel algorithm uses a rectangle-shaped section as region of interest (ROI) to represent and track specific objects in videos. The proposed algorithm is constituted by two stages. The first stage seeks to determine the direction of the object’s motion by analyzing the changing regions around the object being tracked between two consecutive frames. Once the direction of the object’s motion has been predicted, it is initialized an iterative process that seeks to minimize a function of dissimilarity in order to find the location of the object being tracked in the next frame. The main advantage of the proposed algorithm is that, unlike existing kernel-based methods, it is immune to highly cluttered conditions. The results obtained by the proposed algorithm show that the tracking process was successfully carried out for a set of color videos with different challenging conditions such as occlusion, illumination changes, cluttered conditions, and object scale changes.
基金This work was supported by U.S. Department of Defense Science Research Fund （Grant No. DAAD 19-03-1-0375） and the National Natural Science Foundation of China （Grant No. 40774055）.
文摘GPR has become an important geophysical method in UXO and landmine detection, for it can detect both metal and non-metallic targets. However, it is difficult to remove the strong clutters from surface-layer reflection and soil due to the low signal to noise ratio of GPR data. In this paper, we use the adaptive chirplet transform to reject these clutters based on their character and then pick up the signal from the UXO by the transform based on the Radon-Wigner distribution. The results from the processing show that the clutter can be rejected effectively and the target response can be measured with high SNR.
基金supported by Program for New Century Excellent Talents in University(05-0912)the National Natural Science Foundation of China(60672140)the Scientific Research Foundation of Naval Aeronautical and Astronautical University for Young Scholars(HYQN201013)
文摘The high resolution radar target detection is addressed in the non-Gaussian clutter.An adaptive detector is derived for range-spread target based on a novel covariance matrix estimator.It is proved that the new detector is constant false alarm rate(CFAR)to both of the clutter covariance matrix structure and power level theoretically for match cases.The simulation results show that the new detector is almost CFAR for mismatch cases,and it outperforms the existing adaptive detector based on the sample covariance matrix.It also shows that the detection performance improves,as the number of pulses,the number of secondary data or the clutter spike increases.In addition,the derived detector is robust to different subsets,estimated clutter group sizes and correlations of clutter.Importantly,the number of iterations for practical application is just one.
基金National Natural Science Foundation of China(Grant No.61801446).
文摘Measurement of shipborne radar sea echo is instrumental in collecting the sea clutter data in open sea areas.However,the ship movement would introduce an extra Doppler component into the spectrum of the sea clutter,so the sea clutter inherent spectrum must be estimated prior to investigating the sea clutter Doppler characteristics from the shipborne radar sea echo.In this paper we show some results about a shipborne sea clutter measurement experiment that was conducted in the South China Sea in a period between 2017 and 2018;abundant clutter data have been collected by using a shipborne S-band clutter measurement radar.To obtain the sea clutter inherent Doppler spectrum from these data,an estimation method,based on the mapping relationship between the shipborne clutter spectrum and the inherent clutter spectrum,is proposed.This method is validated by shipborne clutter data sets under the same measuring conditions except for the ship speed.Using this method,the characteristics of the Doppler spectrum lineshapes in the South China Sea are calculated and analyzed according to different sea states,wave directions,and radar resolutions,which can be instrumental in designing the radar target detection algorithms.
基金financially supported by the Key Research Program of the Chinese Academy of Sciences(Grant No.KGFZD-125-014)the National Natural Science Foundation of China(Grant No.61273334)State Key Laboratory of Robotics Foundation(Grant No.2017-Z05)
文摘A novel efficient track initiation method is proposed for the harsh underwater target tracking environment(heavy clutter and large measurement errors): track splitting, evaluating, pruning and merging method(TSEPM). Track initiation demands that the method should determine the existence and initial state of a target quickly and correctly.Heavy clutter and large measurement errors certainly pose additional difficulties and challenges, which deteriorate and complicate the track initiation in the harsh underwater target tracking environment. There are three primary shortcomings for the current track initiation methods to initialize a target:(a) they cannot eliminate the turbulences of clutter effectively;(b) there may be a high false alarm probability and low detection probability of a track;(c) they cannot estimate the initial state for a new confirmed track correctly. Based on the multiple hypotheses tracking principle and modified logic-based track initiation method, in order to increase the detection probability of a track,track splitting creates a large number of tracks which include the true track originated from the target. And in order to decrease the false alarm probability, based on the evaluation mechanism, track pruning and track merging are proposed to reduce the false tracks. TSEPM method can deal with the track initiation problems derived from heavy clutter and large measurement errors, determine the target’s existence and estimate its initial state with the least squares method. What’s more, our method is fully automatic and does not require any kind manual input for initializing and tuning any parameter. Simulation results indicate that our new method improves significantly the performance of the track initiation in the harsh underwater target tracking environment.
基金supported by the National Natural Science Foundation of China(62171447)。
文摘In this paper,a comprehensive overview of radar detection methods for low-altitude targets in maritime environments is presented,focusing on the challenges posed by sea clutter and multipath scattering.The performance of the radar detection methods under sea clutter,multipath,and combined conditions is categorized and summarized,and future research directions are outlined to enhance radar detection performance for low-altitude targets in maritime environments.
基金supported by the National Natural Science Foundation of China (61102166)the Scientific Research Foundation of Naval Aeronautical and Astronautical University for Young Scholars (HY2012)
文摘Based on the target scatterer density, the range-spread target detection of high-resolution radar is addressed in additive non-Gaussian clutter, which is modeled as a spherically invariant random vector. Firstly, for sparse scatterer density, the detection of target scatterer in each range cell is derived, and then an M/K detector is proposed to detect the whole range-spread target. Se- condly, an integrating detector is devised to detect a range-spread target with dense scatterer density. Finally, to make the best of the advantages of M/K detector and integrating detector, a robust detector based on scatterer density （DBSD） is designed, which can reduce the probable collapsing loss or quantization error ef- fectively. Moreover, the density decision factor of DBSD is also determined. The formula of the false alarm probability is derived for DBSD. It is proved that the DBSD ensures a constant false alarm rate property. Furthermore, the computational results indi- cate that the DBSD is robust to different clutter one-lag correlations and target scatterer densities. It is also shown that the DBSD out- performs the existing scatterer-density-dependent detector.
基金supported by the National Natural Science Foundation of China(61703228)
文摘With the increment of the number of Gaussian components, the computation cost increases in the Gaussian mixture probability hypothesis density(GM-PHD) filter. Based on the theory of Chen et al, we propose an improved pruning algorithm for the GM-PHD filter, which utilizes not only the Gaussian components’ means and covariance, but their weights as a new criterion to improve the estimate accuracy of the conventional pruning algorithm for tracking very closely proximity targets. Moreover, it solves the end-less while-loop problem without the need of a second merging step. Simulation results show that this improved algorithm is easier to implement and more robust than the formal ones.
文摘Airborne Distributed Coherent Aperture Radar(ADCAR)is one of the most promising next-generation radars to significantly improve target detection and discrimination abilities.However,time and phase synchronization among unit radars should be done before an ADCAR is intended to cohere on a potential target.To address this problem,a time and phase synchronization technique using clutter observations is proposed in this paper.Clutter returns from different azimuths and elevations on the surface of the earth are employed to calibrate system uncertainties.Two stages are mainly considered:a scene registration among range-Doppler units from different transmit/receive pairs is performed to enhance the clutter coherence in the first stage,followed by a joint estimation of those synchronization errors in the second stage.To relieve the computational burden,a novel Separable and Sequential Estimation(SSE)method is provided to separate the unknowns at the sacrifice of a range-Doppler unit.Moreover,performance analyses including the clutter coherence ability,estimation lower bound,and signal coherence loss are also performed.Finally,simulation results indicate that ADCAR time and phase synchronization is realized by using our methods.
基金Project supported by the National Natural Science Foundation of China (Grant No. 41105013)the National Natural Science Foundation of Jiangsu Province,China (Grant No. BK2011122)+1 种基金the Open Issue Foundation of Key Laboratory of Meteorological Disaster of Ministry of Education,China (Grant No. KLME1109)the City Meteorological Scientific Research Fund,China (Grant No. IUMKY&UMRF201111)
文摘The estimation of lower atmospheric refractivity from radar sea clutter（RFC） is a complicated nonlinear optimization problem.This paper deals with the RFC problem in a Bayesian framework.It uses the unbiased Markov Chain Monte Carlo（MCMC） sampling technique,which can provide accurate posterior probability distributions of the estimated refractivity parameters by using an electromagnetic split-step fast Fourier transform terrain parabolic equation propagation model within a Bayesian inversion framework.In contrast to the global optimization algorithm,the Bayesian-MCMC can obtain not only the approximate solutions,but also the probability distributions of the solutions,that is,uncertainty analyses of solutions.The Bayesian-MCMC algorithm is implemented on the simulation radar sea-clutter data and the real radar seaclutter data.Reference data are assumed to be simulation data and refractivity profiles are obtained using a helicopter.The inversion algorithm is assessed（i） by comparing the estimated refractivity profiles from the assumed simulation and the helicopter sounding data;（ii） the one-dimensional（1D） and two-dimensional（2D） posterior probability distribution of solutions.
