Based on a joint time-frequency two dimensional processing, this paper proposes a method for the detection and imaging of moving targets SAR by using Wigner-Ville Distribution (WVD). It is a parameter estimation metho...Based on a joint time-frequency two dimensional processing, this paper proposes a method for the detection and imaging of moving targets SAR by using Wigner-Ville Distribution (WVD). It is a parameter estimation method to generate a high resolution image. The problem of WVD in dealing with multi-point targets and extended targets are also discussed. The computer simulation results illustrate its availability.展开更多
In this paper, the shortages of Wigner-Ville Distribution(WVD) double-linearity in extracting the Doppler parameters of moving-targets are discussed, especially in multi-point moving-target imaging processing based on...In this paper, the shortages of Wigner-Ville Distribution(WVD) double-linearity in extracting the Doppler parameters of moving-targets are discussed, especially in multi-point moving-target imaging processing based on the spectrum characteristics of moving-target echo signals in Synthetic Aperture Radar (SAR) imaging processing and the properties of WVD. Combined with the characteristics of Continuous Wavelet Transform (CWT), the responsibility and advantages of CWT in multi-point moving-target Doppler parameter extraction are analyzed. Finally a kind of multi-point moving-target Doppler parameter extracting algorithm based on CWT are developed, and the computer stimulating results demonstrate the correctness of the algorithm.展开更多
We present a soliton resonance method for moving target detection which is based on the use of inhomogeneous Korteweg-de Vries equation. Zero initial and absorbing boundary conditions are used to obtain the solution o...We present a soliton resonance method for moving target detection which is based on the use of inhomogeneous Korteweg-de Vries equation. Zero initial and absorbing boundary conditions are used to obtain the solution of the equation. The solution will be soliton-like if its right part contains the information about the moving target. The induced soliton will grow in time and the soliton propagation will reflect the kinematic properties of the target. Such soliton-like solution is immune to different types of noise present in the data set, and the method allows to significantly amplify the simulated target signal. Both, general formalism and computer simulations justifying the soliton resonance method capabilities are presented. Simulations are performed for 1D and 2D target movement.展开更多
The development of an efficient moving target detection algorithm in IR-image sequence is considered one of the most critical research fields in modern IRST (Infrared Search and Track) systems, especially when dealing...The development of an efficient moving target detection algorithm in IR-image sequence is considered one of the most critical research fields in modern IRST (Infrared Search and Track) systems, especially when dealing with moving dim point targets. In this paper we propose a new approach in processing of the Infrared image sequence for moving dim point targets detection built on the transformation of the IR-image sequence into 4-vectors for each frame in the sequence. The results of testing the proposed approach on a set of frames having a simple single pixel target performing a different motion patterns show the validity of the approach for detecting the motion, with simplicity in calculation and low time consumption.展开更多
The existing research results show that a fixed single station must conduct three consecutive frequency shift measurements and obtain the target’s moving speed by constructing two frequency difference equations. This...The existing research results show that a fixed single station must conduct three consecutive frequency shift measurements and obtain the target’s moving speed by constructing two frequency difference equations. This article proposes a new method that requires only two consecutive measurements. While using the azimuth measurement to obtain the angular difference between two radial distances, it also conducts two consecutive Doppler frequency shift measurements at the same target azimuth. On the basis of this measurement, a frequency difference equation is first constructed and solved jointly with the Doppler frequency shift equation. By eliminating the velocity variable and using the measured angular difference to obtain the target’s lead angle, the target’s velocity can be solved by using the Doppler frequency shift equation again. The new method avoids the condition that the target must move equidistantly, which not only provides an achievable method for engineering applications but also lays a good foundation for further exploring the use of steady-state signals to achieve passive positioning.展开更多
Global Navigation Satellite System(GNSS)-based passive radar(GBPR)has been widely used in remote sensing applications.However,for moving target detection(MTD),the quadratic phase error(QPE)introduced by the non-cooper...Global Navigation Satellite System(GNSS)-based passive radar(GBPR)has been widely used in remote sensing applications.However,for moving target detection(MTD),the quadratic phase error(QPE)introduced by the non-cooperative target motion is usually difficult to be compensated,as the low power level of the GBPR echo signal renders the estimation of the Doppler rate less effective.Consequently,the moving target in GBPR image is usually defocused,which aggravates the difficulty of target detection even further.In this paper,a spawning particle filter(SPF)is proposed for defocused MTD.Firstly,the measurement model and the likelihood ratio function(LRF)of the defocused point-like target image are deduced.Then,a spawning particle set is generated for subsequent target detection,with reference to traditional particles in particle filter(PF)as their parent.After that,based on the PF estimator,the SPF algorithm and its sequential Monte Carlo(SMC)implementation are proposed with a novel amplitude estimation method to decrease the target state dimension.Finally,the effectiveness of the proposed SPF is demonstrated by numerical simulations and pre-liminary experimental results,showing that the target range and Doppler can be estimated accurately.展开更多
This paper studies the problem of using multiple unmanned air vehicles (UAVs) to search for moving targets with sensing capabilities. When multiple UAVs (multi-UAV) search for a number of moving targets in the mission...This paper studies the problem of using multiple unmanned air vehicles (UAVs) to search for moving targets with sensing capabilities. When multiple UAVs (multi-UAV) search for a number of moving targets in the mission area, the targets can intermittently obtain the position information of the UAVs from sensing devices, and take appropriate actions to increase the distance between themselves and the UAVs. Aiming at this problem, an environment model is established using the search map, and the updating method of the search map is extended by considering the sensing capabilities of the moving targets. A multi-UAV search path planning optimization model based on the model predictive control (MPC) method is constructed, and a hybrid particle swarm optimization algorithm with a crossover operator is designed to solve the model. Simulation results show that the proposed method can effectively improve the cooperative search efficiency and can find more targets per unit time compared with the coverage search method and the random search method.展开更多
Searching for maritime moving targets using satellites is an attracting but rather difficult problem due to the satellites' orbits and discontinuous visible time windows.From a long term cyclic view,a non-myopic m...Searching for maritime moving targets using satellites is an attracting but rather difficult problem due to the satellites' orbits and discontinuous visible time windows.From a long term cyclic view,a non-myopic method based on reinforcement learning(RL)for multi-pass multi-targets searching was proposed.It learnt system behaviors step by step from each observation which resulted in a dynamic progressive way.Then it decided and adjusted optimal actions in each observation opportunity.System states were indicated by expected information gain.Neural networks algorithm was used to approximate parameters of control policy.Simulation results show that our approach with sufficient training performs significantly better than other myopic approaches which make local optimal decisions for each individual observation opportunity.展开更多
AT-InSAR(Along Track Interferometric SAR) is a technique to detect slow-moving targets. However, the detection performance is greatly influenced by noise and clutter. In this paper, the influence of noise and clutter ...AT-InSAR(Along Track Interferometric SAR) is a technique to detect slow-moving targets. However, the detection performance is greatly influenced by noise and clutter. In this paper, the influence of noise and clutter on the detecting performance is analyzed. By simulating different background clutter and noise, the performances of the phase threshold and dual-threshold methods are discussed in detail, and then the adaptive-threshold method is proposed which can greatly improve the detection performance.展开更多
We prove some value-distribution results for a class of L-functions with rational moving targets. The class contains Selberg class, as well as the Riemann-zeta function.
The Synthetic Aperture Radar(SAR)raw data generator is required to the evaluation of focusing algorithms,moving target analysis,and hardware design.The time-domain SAR simulator can generate the accurate raw data but ...The Synthetic Aperture Radar(SAR)raw data generator is required to the evaluation of focusing algorithms,moving target analysis,and hardware design.The time-domain SAR simulator can generate the accurate raw data but it needs much time.The frequency-domain simulator not only increases the efficiency but also considers the trajectory deviations of the radar.In addition,the raw signal of the extended scene included static and moving targets can be generated by some frequency-domain simulators.However,the existing simulators concentrate on the raw signal simulation of the static extended scene and moving targets at uniform speed mostly.As for the issue,the two-dimensional signal spectrum of moving targets with constant acceleration can be derived accurately based on the geometric model of a side-looking SAR and reversion of series.And a frequency-domain algorithm for SAR echo signal simulation is presented based on the two-dimensional signal spectrum.The raw data generated with proposed method is verified by several simulation experiments.In addition to reveal the efficiency of the presented frequency-domain SAR scene simulator,the computational complexity of the proposed method is compared with the time-domain approach using the complex multiplication.Numerical results demonstrate that the present method can reduce the computational time significantly without accuracy loss while simulating SAR raw data.展开更多
In this work we find a lower bound on the energy required for synchronizing moving sensor nodes in a Wireless Sensor Network (WSN) affected by large-scale fading, based on clock estimation techniques. The energy requi...In this work we find a lower bound on the energy required for synchronizing moving sensor nodes in a Wireless Sensor Network (WSN) affected by large-scale fading, based on clock estimation techniques. The energy required for synchronizing a WSN within a desired estimation error level is specified by both the transmit power and the required number of messages. In this paper we extend our previous work introducing nodes’ movement and the average message delay in the total energy, including a comprehensive analysis on how the distance between nodes impacts on the energy and synchronization quality trade-off under large-scale fading effects.展开更多
Based on pattern recognition theory and neural network technology, moving objects automatic detection and classification method integrating advanced wavelet analysis are discussed in detail. An algorithm of moving tar...Based on pattern recognition theory and neural network technology, moving objects automatic detection and classification method integrating advanced wavelet analysis are discussed in detail. An algorithm of moving targets pattern recognition on the combination of inter-frame difference and wavelet neural network is presented. The experimental results indicate that the designed BP wavelet network using this algorithm can recognize and classify moving targets rapidly and effectively.展开更多
Small tracking error correction for electro-optical systems is essential to improve the tracking precision of future mechanical and defense technology.Aerial threats,such as“low,slow,and small(LSS)”moving targets,po...Small tracking error correction for electro-optical systems is essential to improve the tracking precision of future mechanical and defense technology.Aerial threats,such as“low,slow,and small(LSS)”moving targets,pose increasing challenges to society.The core goal of this work is to address the issues,such as small tracking error correction and aiming control,of electro-optical detection systems by using mechatronics drive modeling,composite velocity–image stability control,and improved interpolation filter design.A tracking controller delay prediction method for moving targets is proposed based on the Euler transformation model of a two-axis,two-gimbal cantilever beam coaxial configuration.Small tracking error formation is analyzed in detail to reveal the scientific mechanism of composite control between the tracking controller’s feedback and the motor’s velocity–stability loop.An improved segmental interpolation filtering algorithm is established by combining line of sight(LOS)position correction and multivariable typical tracking fault diagnosis.Then,a platform with 2 degrees of freedom is used to test the system.An LSS moving target shooting object with a tracking distance of S=100 m,target board area of A=1 m^(2),and target linear velocity of v=5 m/s is simulated.Results show that the optimal method’s distribution probability of the tracking error in a circle with a radius of 1 mrad is 66.7%,and that of the traditional method is 41.6%.Compared with the LOS shooting accuracy of the traditional method,the LOS shooting accuracy of the optimized method is improved by 37.6%.展开更多
Conventional moving target detection focuses on algorithms to improve detection efficiency. These algorithms pay less attention to the image acquisition means, and usually solve specific problems. This often results i...Conventional moving target detection focuses on algorithms to improve detection efficiency. These algorithms pay less attention to the image acquisition means, and usually solve specific problems. This often results in poor flexibility and reus- ability. Insect compound eyes offer unique advantages for moving target detection and these advantages have attracted the attention of many researchers in recent years. In this paper we proposed a new system for moving target detection. We used the detection mechanism of insect compound eyes for the simulation of the characteristics of structure, control, and function. We discussed the design scheme of the system, the development of the bionic control circuit, and introduced the proposed mathe- matical model of bionic cqmpound eyes for data acquisition and object detection. After this the integrated system was described and discussed. Our paper presents a novel approach for moving target detection. This approach effectively tackles some of the well-known problems in the field of view, resolution, and real-time processing problems in moving target detection.展开更多
The method of moving target detection based on subimage cancellation for single-antenna airborne SAR is presented. First the subimage is obtained through frequency processing is pointed out. The imaging difference of ...The method of moving target detection based on subimage cancellation for single-antenna airborne SAR is presented. First the subimage is obtained through frequency processing is pointed out. The imaging difference of a stationary objects and moving object in the subimage based on the frequency division is analyzed from the fundamental principle. Then the developed method combines the shear averaging algorithm to focus on the moving target in the subimage, after the clutter suppression and the focusing position in each subimage is obtained. Next the observation model and the relative movement of the moving targets between the subimages estimate the moving targets. The theoretical analysis and simulation results demonstrate that the method is effective and can not only detect the moving targets, but also estimate their motion parameters precisely.展开更多
Under the conditions of strong sea clutter and complex moving targets,it is extremely difficult to detect moving targets in the maritime surface.This paper proposes a new algorithm named improved tunable Q-factor wave...Under the conditions of strong sea clutter and complex moving targets,it is extremely difficult to detect moving targets in the maritime surface.This paper proposes a new algorithm named improved tunable Q-factor wavelet transform(TQWT)for moving target detection.Firstly,this paper establishes a moving target model and sparsely compensates the Doppler migration of the moving target in the fractional Fourier transform(FRFT)domain.Then,TQWT is adopted to decompose the signal based on the discrimination between the sea clutter and the target’s oscillation characteristics,using the basis pursuit denoising(BPDN)algorithm to get the wavelet coefficients.Furthermore,an energy selection method based on the optimal distribution of sub-bands energy is proposed to sparse the coefficients and reconstruct the target.Finally,experiments on the Council for Scientific and Industrial Research(CSIR)dataset indicate the performance of the proposed method and provide the basis for subsequent target detection.展开更多
The Earth observation remote sensing images can display ground activities and status intuitively,which plays an important role in civil and military fields.However,the information obtained from the research only from ...The Earth observation remote sensing images can display ground activities and status intuitively,which plays an important role in civil and military fields.However,the information obtained from the research only from the perspective of images is limited,so in this paper we conduct research from the perspective of video.At present,the main problems faced when using a computer to identify remote sensing images are:They are difficult to build a fixed regular model of the target due to their weak moving regularity.Additionally,the number of pixels occupied by the target is not enough for accurate detection.However,the number of moving targets is large at the same time.In this case,the main targets cannot be recognized completely.This paper studies from the perspective of Gestalt vision,transforms the problem ofmoving target detection into the problem of salient region probability,and forms a Saliency map algorithm to extract moving targets.On this basis,a convolutional neural network with global information is constructed to identify and label the target.And the experimental results show that the algorithm can extract moving targets and realize moving target recognition under many complex conditions such as target’s long-term stay and small-amplitude movement.展开更多
文摘Based on a joint time-frequency two dimensional processing, this paper proposes a method for the detection and imaging of moving targets SAR by using Wigner-Ville Distribution (WVD). It is a parameter estimation method to generate a high resolution image. The problem of WVD in dealing with multi-point targets and extended targets are also discussed. The computer simulation results illustrate its availability.
文摘In this paper, the shortages of Wigner-Ville Distribution(WVD) double-linearity in extracting the Doppler parameters of moving-targets are discussed, especially in multi-point moving-target imaging processing based on the spectrum characteristics of moving-target echo signals in Synthetic Aperture Radar (SAR) imaging processing and the properties of WVD. Combined with the characteristics of Continuous Wavelet Transform (CWT), the responsibility and advantages of CWT in multi-point moving-target Doppler parameter extraction are analyzed. Finally a kind of multi-point moving-target Doppler parameter extracting algorithm based on CWT are developed, and the computer stimulating results demonstrate the correctness of the algorithm.
文摘We present a soliton resonance method for moving target detection which is based on the use of inhomogeneous Korteweg-de Vries equation. Zero initial and absorbing boundary conditions are used to obtain the solution of the equation. The solution will be soliton-like if its right part contains the information about the moving target. The induced soliton will grow in time and the soliton propagation will reflect the kinematic properties of the target. Such soliton-like solution is immune to different types of noise present in the data set, and the method allows to significantly amplify the simulated target signal. Both, general formalism and computer simulations justifying the soliton resonance method capabilities are presented. Simulations are performed for 1D and 2D target movement.
文摘The development of an efficient moving target detection algorithm in IR-image sequence is considered one of the most critical research fields in modern IRST (Infrared Search and Track) systems, especially when dealing with moving dim point targets. In this paper we propose a new approach in processing of the Infrared image sequence for moving dim point targets detection built on the transformation of the IR-image sequence into 4-vectors for each frame in the sequence. The results of testing the proposed approach on a set of frames having a simple single pixel target performing a different motion patterns show the validity of the approach for detecting the motion, with simplicity in calculation and low time consumption.
文摘The existing research results show that a fixed single station must conduct three consecutive frequency shift measurements and obtain the target’s moving speed by constructing two frequency difference equations. This article proposes a new method that requires only two consecutive measurements. While using the azimuth measurement to obtain the angular difference between two radial distances, it also conducts two consecutive Doppler frequency shift measurements at the same target azimuth. On the basis of this measurement, a frequency difference equation is first constructed and solved jointly with the Doppler frequency shift equation. By eliminating the velocity variable and using the measured angular difference to obtain the target’s lead angle, the target’s velocity can be solved by using the Doppler frequency shift equation again. The new method avoids the condition that the target must move equidistantly, which not only provides an achievable method for engineering applications but also lays a good foundation for further exploring the use of steady-state signals to achieve passive positioning.
基金supported by the National Natural Science Foundation of China(62101014)the National Key Laboratory of Science and Technology on Space Microwave(6142411203307).
文摘Global Navigation Satellite System(GNSS)-based passive radar(GBPR)has been widely used in remote sensing applications.However,for moving target detection(MTD),the quadratic phase error(QPE)introduced by the non-cooperative target motion is usually difficult to be compensated,as the low power level of the GBPR echo signal renders the estimation of the Doppler rate less effective.Consequently,the moving target in GBPR image is usually defocused,which aggravates the difficulty of target detection even further.In this paper,a spawning particle filter(SPF)is proposed for defocused MTD.Firstly,the measurement model and the likelihood ratio function(LRF)of the defocused point-like target image are deduced.Then,a spawning particle set is generated for subsequent target detection,with reference to traditional particles in particle filter(PF)as their parent.After that,based on the PF estimator,the SPF algorithm and its sequential Monte Carlo(SMC)implementation are proposed with a novel amplitude estimation method to decrease the target state dimension.Finally,the effectiveness of the proposed SPF is demonstrated by numerical simulations and pre-liminary experimental results,showing that the target range and Doppler can be estimated accurately.
基金supported by the National Natural Science Foundation of China(7140104871671059)the National Natural Science Funds of China for Innovative Research Groups(71521001)
文摘This paper studies the problem of using multiple unmanned air vehicles (UAVs) to search for moving targets with sensing capabilities. When multiple UAVs (multi-UAV) search for a number of moving targets in the mission area, the targets can intermittently obtain the position information of the UAVs from sensing devices, and take appropriate actions to increase the distance between themselves and the UAVs. Aiming at this problem, an environment model is established using the search map, and the updating method of the search map is extended by considering the sensing capabilities of the moving targets. A multi-UAV search path planning optimization model based on the model predictive control (MPC) method is constructed, and a hybrid particle swarm optimization algorithm with a crossover operator is designed to solve the model. Simulation results show that the proposed method can effectively improve the cooperative search efficiency and can find more targets per unit time compared with the coverage search method and the random search method.
基金Project supported by NSFC(10571135)Doctoral Program Foundation of the Ministry of Education of China(20050240771)Funds of the Science and Technology Committee of Shanghai(03JC14027)
文摘In this article, two uniqueness theorems of meromorphic mappings on moving targets with truncated multiplicities are proved.
基金National Natural Science Foundation of China(No.61203180)
文摘Searching for maritime moving targets using satellites is an attracting but rather difficult problem due to the satellites' orbits and discontinuous visible time windows.From a long term cyclic view,a non-myopic method based on reinforcement learning(RL)for multi-pass multi-targets searching was proposed.It learnt system behaviors step by step from each observation which resulted in a dynamic progressive way.Then it decided and adjusted optimal actions in each observation opportunity.System states were indicated by expected information gain.Neural networks algorithm was used to approximate parameters of control policy.Simulation results show that our approach with sufficient training performs significantly better than other myopic approaches which make local optimal decisions for each individual observation opportunity.
文摘AT-InSAR(Along Track Interferometric SAR) is a technique to detect slow-moving targets. However, the detection performance is greatly influenced by noise and clutter. In this paper, the influence of noise and clutter on the detecting performance is analyzed. By simulating different background clutter and noise, the performances of the phase threshold and dual-threshold methods are discussed in detail, and then the adaptive-threshold method is proposed which can greatly improve the detection performance.
文摘We prove some value-distribution results for a class of L-functions with rational moving targets. The class contains Selberg class, as well as the Riemann-zeta function.
基金The work was supported by the Natural Science Foundation of Shandong Province,China.(Grant No.ZR2017BF032)。
文摘The Synthetic Aperture Radar(SAR)raw data generator is required to the evaluation of focusing algorithms,moving target analysis,and hardware design.The time-domain SAR simulator can generate the accurate raw data but it needs much time.The frequency-domain simulator not only increases the efficiency but also considers the trajectory deviations of the radar.In addition,the raw signal of the extended scene included static and moving targets can be generated by some frequency-domain simulators.However,the existing simulators concentrate on the raw signal simulation of the static extended scene and moving targets at uniform speed mostly.As for the issue,the two-dimensional signal spectrum of moving targets with constant acceleration can be derived accurately based on the geometric model of a side-looking SAR and reversion of series.And a frequency-domain algorithm for SAR echo signal simulation is presented based on the two-dimensional signal spectrum.The raw data generated with proposed method is verified by several simulation experiments.In addition to reveal the efficiency of the presented frequency-domain SAR scene simulator,the computational complexity of the proposed method is compared with the time-domain approach using the complex multiplication.Numerical results demonstrate that the present method can reduce the computational time significantly without accuracy loss while simulating SAR raw data.
文摘In this work we find a lower bound on the energy required for synchronizing moving sensor nodes in a Wireless Sensor Network (WSN) affected by large-scale fading, based on clock estimation techniques. The energy required for synchronizing a WSN within a desired estimation error level is specified by both the transmit power and the required number of messages. In this paper we extend our previous work introducing nodes’ movement and the average message delay in the total energy, including a comprehensive analysis on how the distance between nodes impacts on the energy and synchronization quality trade-off under large-scale fading effects.
文摘Based on pattern recognition theory and neural network technology, moving objects automatic detection and classification method integrating advanced wavelet analysis are discussed in detail. An algorithm of moving targets pattern recognition on the combination of inter-frame difference and wavelet neural network is presented. The experimental results indicate that the designed BP wavelet network using this algorithm can recognize and classify moving targets rapidly and effectively.
基金funded by the National Natural Science Foundation of China(Grant No.U19A2072)the Provincial Department of Education Postgraduate Scientific Research Innovation Project of Hunan Province of China(Grant No.QL20210007)the Ministerial Level Postgraduate Funding Project of China(Grant No.JY2021A007).
文摘Small tracking error correction for electro-optical systems is essential to improve the tracking precision of future mechanical and defense technology.Aerial threats,such as“low,slow,and small(LSS)”moving targets,pose increasing challenges to society.The core goal of this work is to address the issues,such as small tracking error correction and aiming control,of electro-optical detection systems by using mechatronics drive modeling,composite velocity–image stability control,and improved interpolation filter design.A tracking controller delay prediction method for moving targets is proposed based on the Euler transformation model of a two-axis,two-gimbal cantilever beam coaxial configuration.Small tracking error formation is analyzed in detail to reveal the scientific mechanism of composite control between the tracking controller’s feedback and the motor’s velocity–stability loop.An improved segmental interpolation filtering algorithm is established by combining line of sight(LOS)position correction and multivariable typical tracking fault diagnosis.Then,a platform with 2 degrees of freedom is used to test the system.An LSS moving target shooting object with a tracking distance of S=100 m,target board area of A=1 m^(2),and target linear velocity of v=5 m/s is simulated.Results show that the optimal method’s distribution probability of the tracking error in a circle with a radius of 1 mrad is 66.7%,and that of the traditional method is 41.6%.Compared with the LOS shooting accuracy of the traditional method,the LOS shooting accuracy of the optimized method is improved by 37.6%.
基金The work presented in this paper is supported by the Scholarship for International Young Scientists of NSFC (National Natural Science Foundation of China) (1D: 41050110441).
文摘Conventional moving target detection focuses on algorithms to improve detection efficiency. These algorithms pay less attention to the image acquisition means, and usually solve specific problems. This often results in poor flexibility and reus- ability. Insect compound eyes offer unique advantages for moving target detection and these advantages have attracted the attention of many researchers in recent years. In this paper we proposed a new system for moving target detection. We used the detection mechanism of insect compound eyes for the simulation of the characteristics of structure, control, and function. We discussed the design scheme of the system, the development of the bionic control circuit, and introduced the proposed mathe- matical model of bionic cqmpound eyes for data acquisition and object detection. After this the integrated system was described and discussed. Our paper presents a novel approach for moving target detection. This approach effectively tackles some of the well-known problems in the field of view, resolution, and real-time processing problems in moving target detection.
文摘The method of moving target detection based on subimage cancellation for single-antenna airborne SAR is presented. First the subimage is obtained through frequency processing is pointed out. The imaging difference of a stationary objects and moving object in the subimage based on the frequency division is analyzed from the fundamental principle. Then the developed method combines the shear averaging algorithm to focus on the moving target in the subimage, after the clutter suppression and the focusing position in each subimage is obtained. Next the observation model and the relative movement of the moving targets between the subimages estimate the moving targets. The theoretical analysis and simulation results demonstrate that the method is effective and can not only detect the moving targets, but also estimate their motion parameters precisely.
基金the National Natural Science Foundation of China(U19B2031).
文摘Under the conditions of strong sea clutter and complex moving targets,it is extremely difficult to detect moving targets in the maritime surface.This paper proposes a new algorithm named improved tunable Q-factor wavelet transform(TQWT)for moving target detection.Firstly,this paper establishes a moving target model and sparsely compensates the Doppler migration of the moving target in the fractional Fourier transform(FRFT)domain.Then,TQWT is adopted to decompose the signal based on the discrimination between the sea clutter and the target’s oscillation characteristics,using the basis pursuit denoising(BPDN)algorithm to get the wavelet coefficients.Furthermore,an energy selection method based on the optimal distribution of sub-bands energy is proposed to sparse the coefficients and reconstruct the target.Finally,experiments on the Council for Scientific and Industrial Research(CSIR)dataset indicate the performance of the proposed method and provide the basis for subsequent target detection.
基金supported by Yulin Science and Technology Association Youth Talent Promotion Program(Grant No.20200212).
文摘The Earth observation remote sensing images can display ground activities and status intuitively,which plays an important role in civil and military fields.However,the information obtained from the research only from the perspective of images is limited,so in this paper we conduct research from the perspective of video.At present,the main problems faced when using a computer to identify remote sensing images are:They are difficult to build a fixed regular model of the target due to their weak moving regularity.Additionally,the number of pixels occupied by the target is not enough for accurate detection.However,the number of moving targets is large at the same time.In this case,the main targets cannot be recognized completely.This paper studies from the perspective of Gestalt vision,transforms the problem ofmoving target detection into the problem of salient region probability,and forms a Saliency map algorithm to extract moving targets.On this basis,a convolutional neural network with global information is constructed to identify and label the target.And the experimental results show that the algorithm can extract moving targets and realize moving target recognition under many complex conditions such as target’s long-term stay and small-amplitude movement.