Multiple unmanned aerial vehicles(UAVs)cooperative operation is the main form for UAVs fighting in battlefield,and multi-UAV mission rendezvous is the premise of cooperative reconnaissance and attack missions.We propo...Multiple unmanned aerial vehicles(UAVs)cooperative operation is the main form for UAVs fighting in battlefield,and multi-UAV mission rendezvous is the premise of cooperative reconnaissance and attack missions.We propose a rendezvous control strategy,which divides the rendezvous process into two parts:The loose formation rendezvous and the close formation rendezvous.In the first stage,UAVs are supposed to reach the specific target locations simultaneously and form a loose formation.A distributed control strategy based on first-order consensus algorithm is presented to achieve this goal.Then the second stage is designed based on the second-order consensus algorithm to complete the transition from the loose formation to the close formation.This process needs the speeds and heading angles of UAVs to reach an agreement.Besides,control algorithms with a virtual leader are proposed,by which the formation states can reach a specific value.Finally,simulation results show that the control algorithms are capable of realizing the mission rendezvous of multi-UAV and the consistence of UAVs′final states,which verify the effectiveness and feasibility of the designed control strategy.展开更多
A decision-making problem of missile-target assignment with a novel particle swarm optimization algorithm is proposed when it comes to a multiple target collaborative combat situation.The threat function is establishe...A decision-making problem of missile-target assignment with a novel particle swarm optimization algorithm is proposed when it comes to a multiple target collaborative combat situation.The threat function is established to describe air combat situation.Optimization function is used to find an optimal missile-target assignment.An improved particle swarm optimization algorithm is utilized to figure out the optimization function with less parameters,which is based on the adaptive random learning approach.According to the coordinated attack tactics,there are some adjustments to the assignment.Simulation example results show that it is an effective algorithm to handle with the decision-making problem of the missile-target assignment(MTA)in air combat.展开更多
A novel multi-observer passive localization algorithm based on the weighted restricted total least square （WRTLS） is proposed to solve the bearings-only localization problem in the presence of observer position erro...A novel multi-observer passive localization algorithm based on the weighted restricted total least square （WRTLS） is proposed to solve the bearings-only localization problem in the presence of observer position errors. Firstly, the unknown matrix perturbation information is utilized to form the WRTLS problem. Then, the corresponding constrained optimization problem is transformed into an unconstrained one, which is a generalized Rayleigh quotient minimization problem. Thus, the solution can be got through the generalized eigenvalue decomposition and requires no initial state guess process. Simulation results indicate that the proposed algorithm can approach the Cramer-Rao lower bound （CRLB）, and the localization solution is asymptotically unbiased.展开更多
This paper investigates the jamming sensing performance of the simultaneous transmit and receive based cognitive anti-jamming(SCAJ) receiver impaired by phase noise in local oscillators(LO) over fading channels. First...This paper investigates the jamming sensing performance of the simultaneous transmit and receive based cognitive anti-jamming(SCAJ) receiver impaired by phase noise in local oscillators(LO) over fading channels. Firstly, energy detection(ED)based on the jamming to noise ratio(JNR) of the high frequency bands SCAJ receiver with phase noise under different channels is analyzed. Then, the probabilities of jamming detection and false alarm in closed-form for the SCAJ receiver are derived. Finally,the modified Bayesian Cramer-Rao bound(BCRB) of jamming sensing for the SCAJ receiver is presented. Simulation results show that the performance degradation of the SCAJ system due to phase noise is more severe than that due to the channel fading in the circumstances where the signal bandwidth(BW) is kept a constant. Moreover, the signal BW has an effect on the phase noise in LO, and the jamming detection probability of the wideband SCAJ receiver with lower phase noise outperforms that of the narrowband receiver using the same center frequency. Furthermore,an accurate phase noise estimation and compensation scheme can improve the jamming detection capability of the SCAJ receiver in high frequency bands and approach to the upper bound.展开更多
The stability of quantized innovations Kalman filtering (QIKF) is analyzed. In the analysis, the correlation between quantization errors and measurement noises is considered. By taking the quantization errors as a ran...The stability of quantized innovations Kalman filtering (QIKF) is analyzed. In the analysis, the correlation between quantization errors and measurement noises is considered. By taking the quantization errors as a random perturbation in the observation system, the QIKF for the original system is equivalent to a Kalman-like filtering for the equivalent state-observation system. Thus, the estimate error covariance matrix of QIKF can be more exactly analyzed. The boundedness of the estimate error covariance matrix of QIKF is obtained under some weak conditions. The design of the number of quantized levels is discussed to guarantee the stability of QIKF. To overcome the instability and divergence of QIKF when the number of quantization levels is small, we propose a Kalman filter using scaling quantized innovations. Numerical simulations show the validity of the theorems and algorithms.展开更多
Image restoration is an important part of various applications, such as computer vision, robotics and remote sensing. However, recovering the underlying structures of the latent image contained in multi-image is a cha...Image restoration is an important part of various applications, such as computer vision, robotics and remote sensing. However, recovering the underlying structures of the latent image contained in multi-image is a challenging problem because of the need to develop robust and fast algorithms. In this paper, a novel problem formulation for multi-image restoration problem is proposed. This novel formulation is composed of multi-data fidelity terms and a composite regularizer. The proposed regularizer consists of total generalized variation(TGV)and lp-norm. This multi-regularization method can simultaneously exploit the consistence of image pixels and promote the sparsity of natural signals. To deal with the resulting problem, we derive and implement the solution using alternating direction method of multipliers(ADMM). The effectiveness of our method is illustrated through extensive experiments on multi-image denoising and inpainting. Numerical results show that the proposed method is more efficient than competing algorithms, achieving better restoration performance.展开更多
In order to solve the bearings-only passive localization problem in the presence of erroneous observer position, a novel algorithm based on double side matrix-restricted total least squares （DSMRTLS） is proposed. Fi...In order to solve the bearings-only passive localization problem in the presence of erroneous observer position, a novel algorithm based on double side matrix-restricted total least squares （DSMRTLS） is proposed. First, the aforementioned passive localization problem is transferred to the DSMRTLS problem by deriving a multiplicative structure for both the observation matrix and the observation vector. Second, the corresponding optimization problem of the DSMRTLS problem without constraint is derived, which can be approximated as the generalized Rayleigh quotient minimization problem. Then, the localization solution which is globally optimal and asymptotically unbiased can be got by generalized eigenvalue decomposition. Simulation results verify the rationality of the approximation and the good performance of the proposed algorithm compared with several typical algorithms.展开更多
基金jointly granted by the Science and Technology on Avionics Integration Laboratorythe Aeronautical Science Foundation(2016ZC15008)
文摘Multiple unmanned aerial vehicles(UAVs)cooperative operation is the main form for UAVs fighting in battlefield,and multi-UAV mission rendezvous is the premise of cooperative reconnaissance and attack missions.We propose a rendezvous control strategy,which divides the rendezvous process into two parts:The loose formation rendezvous and the close formation rendezvous.In the first stage,UAVs are supposed to reach the specific target locations simultaneously and form a loose formation.A distributed control strategy based on first-order consensus algorithm is presented to achieve this goal.Then the second stage is designed based on the second-order consensus algorithm to complete the transition from the loose formation to the close formation.This process needs the speeds and heading angles of UAVs to reach an agreement.Besides,control algorithms with a virtual leader are proposed,by which the formation states can reach a specific value.Finally,simulation results show that the control algorithms are capable of realizing the mission rendezvous of multi-UAV and the consistence of UAVs′final states,which verify the effectiveness and feasibility of the designed control strategy.
基金jointly granted by the Science and Technology on Avionics Integration Laboratory and the Aeronautical Science Foundation of China (No. 2016ZC15008)
文摘A decision-making problem of missile-target assignment with a novel particle swarm optimization algorithm is proposed when it comes to a multiple target collaborative combat situation.The threat function is established to describe air combat situation.Optimization function is used to find an optimal missile-target assignment.An improved particle swarm optimization algorithm is utilized to figure out the optimization function with less parameters,which is based on the adaptive random learning approach.According to the coordinated attack tactics,there are some adjustments to the assignment.Simulation example results show that it is an effective algorithm to handle with the decision-making problem of the missile-target assignment(MTA)in air combat.
基金supported by the Aeronautical Science Foundation of China (20105584004)the Science and Technology on Avionics Integration Laboratory
文摘A novel multi-observer passive localization algorithm based on the weighted restricted total least square （WRTLS） is proposed to solve the bearings-only localization problem in the presence of observer position errors. Firstly, the unknown matrix perturbation information is utilized to form the WRTLS problem. Then, the corresponding constrained optimization problem is transformed into an unconstrained one, which is a generalized Rayleigh quotient minimization problem. Thus, the solution can be got through the generalized eigenvalue decomposition and requires no initial state guess process. Simulation results indicate that the proposed algorithm can approach the Cramer-Rao lower bound （CRLB）, and the localization solution is asymptotically unbiased.
基金supported by the Program of the Aeronautical Science Foundation of China(2013ZC15003)
文摘This paper investigates the jamming sensing performance of the simultaneous transmit and receive based cognitive anti-jamming(SCAJ) receiver impaired by phase noise in local oscillators(LO) over fading channels. Firstly, energy detection(ED)based on the jamming to noise ratio(JNR) of the high frequency bands SCAJ receiver with phase noise under different channels is analyzed. Then, the probabilities of jamming detection and false alarm in closed-form for the SCAJ receiver are derived. Finally,the modified Bayesian Cramer-Rao bound(BCRB) of jamming sensing for the SCAJ receiver is presented. Simulation results show that the performance degradation of the SCAJ system due to phase noise is more severe than that due to the channel fading in the circumstances where the signal bandwidth(BW) is kept a constant. Moreover, the signal BW has an effect on the phase noise in LO, and the jamming detection probability of the wideband SCAJ receiver with lower phase noise outperforms that of the narrowband receiver using the same center frequency. Furthermore,an accurate phase noise estimation and compensation scheme can improve the jamming detection capability of the SCAJ receiver in high frequency bands and approach to the upper bound.
基金supported by the National Natural Science Foundation of China (Nos. 61175008, 60935001, and 60874104)the National Basic Research Program (973) of China (Nos. 2009CB824900 and 2010CB734103)+1 种基金the Space Foundation of Supporting-Technology (No. 2011-HT-SHJD002)the Aeronautical Science Foundation of China (No. 20105557007)
文摘The stability of quantized innovations Kalman filtering (QIKF) is analyzed. In the analysis, the correlation between quantization errors and measurement noises is considered. By taking the quantization errors as a random perturbation in the observation system, the QIKF for the original system is equivalent to a Kalman-like filtering for the equivalent state-observation system. Thus, the estimate error covariance matrix of QIKF can be more exactly analyzed. The boundedness of the estimate error covariance matrix of QIKF is obtained under some weak conditions. The design of the number of quantized levels is discussed to guarantee the stability of QIKF. To overcome the instability and divergence of QIKF when the number of quantization levels is small, we propose a Kalman filter using scaling quantized innovations. Numerical simulations show the validity of the theorems and algorithms.
基金the National Natural Science Foundation of China(Nos.61690210,61690212,61673262and 61603249)the Key Project of Science and Technology Commission of Shanghai Municipality(No.16JC1401100)
文摘Image restoration is an important part of various applications, such as computer vision, robotics and remote sensing. However, recovering the underlying structures of the latent image contained in multi-image is a challenging problem because of the need to develop robust and fast algorithms. In this paper, a novel problem formulation for multi-image restoration problem is proposed. This novel formulation is composed of multi-data fidelity terms and a composite regularizer. The proposed regularizer consists of total generalized variation(TGV)and lp-norm. This multi-regularization method can simultaneously exploit the consistence of image pixels and promote the sparsity of natural signals. To deal with the resulting problem, we derive and implement the solution using alternating direction method of multipliers(ADMM). The effectiveness of our method is illustrated through extensive experiments on multi-image denoising and inpainting. Numerical results show that the proposed method is more efficient than competing algorithms, achieving better restoration performance.
基金co-supported by Science and Technology on Avionics Integration Laboratory and the Aeronautical Science Foundation of China(No.20105584004)
文摘In order to solve the bearings-only passive localization problem in the presence of erroneous observer position, a novel algorithm based on double side matrix-restricted total least squares （DSMRTLS） is proposed. First, the aforementioned passive localization problem is transferred to the DSMRTLS problem by deriving a multiplicative structure for both the observation matrix and the observation vector. Second, the corresponding optimization problem of the DSMRTLS problem without constraint is derived, which can be approximated as the generalized Rayleigh quotient minimization problem. Then, the localization solution which is globally optimal and asymptotically unbiased can be got by generalized eigenvalue decomposition. Simulation results verify the rationality of the approximation and the good performance of the proposed algorithm compared with several typical algorithms.
