Maneuvering target tracking of UAV based on MN-DDPG and transfer learning

Tracking maneuvering target in real time autonomously and accurately in an uncertain environment is one of the challenging missions for unmanned aerial vehicles(UAVs).In this paper,aiming to address the control problem of maneuvering target tracking and obstacle avoidance,an online path planning approach for UAV is developed based on deep reinforcement learning.Through end-to-end learning powered by neural networks,the proposed approach can achieve the perception of the environment and continuous motion output control.This proposed approach includes:(1)A deep deterministic policy gradient(DDPG)-based control framework to provide learning and autonomous decision-making capability for UAVs;(2)An improved method named MN-DDPG for introducing a type of mixed noises to assist UAV with exploring stochastic strategies for online optimal planning;and(3)An algorithm of taskdecomposition and pre-training for efficient transfer learning to improve the generalization capability of UAV’s control model built based on MN-DDPG.The experimental simulation results have verified that the proposed approach can achieve good self-adaptive adjustment of UAV’s flight attitude in the tasks of maneuvering target tracking with a significant improvement in generalization capability and training efficiency of UAV tracking controller in uncertain environments.

An impact angle constraint integral sliding mode guidance law for maneuvering targets interception

An integral sliding mode guidance law(ISMGL)combined with the advantages of the integral sliding mode control(SMC)method is designed to address maneuvering target interception problems with impact angle constraints.The relative motion equation of the missile and the target considering the impact angle constraint is established in the longitudinal plane,and an integral sliding mode surface is constructed.The proposed guidance law resolves the existence of a steady-state error problem in the traditional SMC.Such a guidance law ensures that the missile hits the target with an ideal impact angle in finite time and the missile is kept highly robust throughout the interception process.By adopting the dynamic surface control method,the ISMGL is designed considering the impact angle constraints and the autopilot dynamic characteristics.According to the Lyapunov stability theorem,all states of the closed-loop system are finally proven to be uniformly bounded.Simulation results are compared with the general sliding mode guidance law and the trajectory shaping guidance law,and the findings verify the effectiveness and superiority of the ISMGL.

Sensor scheduling for ground maneuvering target tracking in presence of detection blind zone

Continuous and stable tracking of the ground maneuvering target is a challenging problem due to the complex terrain and high clutter. A collaborative tracking method of the multisensor network is presented for the ground maneuvering target in the presence of the detection blind zone(DBZ). First, the sensor scheduling process is modeled within the partially observable Markov decision process(POMDP) framework. To evaluate the target tracking accuracy of the sensor, the Fisher information is applied to constructing the reward function. The key of the proposed scheduling method is forecasting and early decisionmaking. Thus, an approximate method based on unscented sampling is presented to estimate the target state and the multi-step scheduling reward over the prediction time horizon. Moreover, the problem is converted into a nonlinear optimization problem, and a fast search algorithm is given to solve the sensor scheduling scheme quickly. Simulation results demonstrate the proposed nonmyopic scheduling method(Non-MSM) has a better target tracking accuracy compared with traditional methods.

ISAR autofocus imaging algorithm for maneuvering targets based on deep learning and keystone transform

The issue of small-angle maneuvering targets inverse synthetic aperture radar(ISAR)imaging has been successfully addressed by popular motion compensation algorithms.However,when the target’s rotational velocity is sufficiently high during the dwell time of the radar,such compensation algorithms cannot obtain a high quality image.This paper proposes an ISAR imaging algorithm based on keystone transform and deep learning algorithm.The keystone transform is used to coarsely compensate for the target’s rotational motion and translational motion,and the deep learning algorithm is used to achieve a super-resolution image.The uniformly distributed point target data are used as the data set of the training u-net network.In addition,this method does not require estimating the motion parameters of the target,which simplifies the algorithm steps.Finally,several experiments are performed to demonstrate the effectiveness of the proposed algorithm.

A Fuzzy Adaptive Algorithm Based on“Current”Statistical Model for Maneuvering Target Tracking

The basic"current"statistical model and adaptive Kalman filter algorithm can not track a weakly maneuvering target precisely,though it has good estimate accuracy for strongly maneuvering target.In order to solve this problem,a novel nonlinear fuzzy membership function was presented to adjust the upper and lower limit of target acceleration adaptively,and then the validity of the new algorithm for feeblish maneuvering target was proved in theory.At last,the computer simulation experiments indicated that the new algorithm has a great advantage over the basic"current"statistical model and adaptive algorithm.

Maneuvering target state estimation based on separate model-ing of target trajectory shape and dynamic characteristics

The state estimation of a maneuvering target,of which the trajectory shape is independent on dynamic characteristics,is studied.The conventional motion models in Cartesian coordinates imply that the trajectory of a target is completely determined by its dynamic characteristics.However,this is not true in the applications of road-target,sea-route-target or flight route-target tracking,where target trajectory shape is uncoupled with target velocity properties.In this paper,a new estimation algorithm based on separate modeling of target trajectory shape and dynamic characteristics is proposed.The trajectory of a target over a sliding window is described by a linear function of the arc length.To determine the unknown target trajectory,an augmented system is derived by denoting the unknown coefficients of the function as states in mileage coordinates.At every estimation cycle except the first one,the interaction(mixing)stage of the proposed algorithm starts from the latest estimated base state and a recalculated parameter vector,which is determined by the least squares(LS).Numerical experiments are conducted to assess the performance of the proposed algorithm.Simulation results show that the proposed algorithm can achieve better performance than the conventional coupled model-based algorithms in the presence of target maneuvers.

Maneuvering target tracking algorithm based on CDKF in observation bootstrapping strategy

The selection and optimization of model filters affect the precision of motion pattern identification and state estimation in maneuvering target tracking directly.Aiming at improving performance of model filters,a novel maneuvering target tracking algorithm based on central difference Kalman filter in observation bootstrapping strategy is proposed.The framework of interactive multiple model(IMM) is used to realize identification of motion pattern,and a central difference Kalman filter(CDKF) is selected as the model filter of IMM.Considering the advantage of multi-sensor fusion method in improving the stability and reliability of observation information,the hardware cost of the observation system for multiple sensors is adopted,meanwhile,according to the data assimilation technique in Ensemble Kalman filter(En KF),a bootstrapping observation set is constructed by integrating the latest observation and the prior information of observation noise.On that basis,these bootstrapping observations are reasonably used to optimize the filtering performance of CDKF by means of weight fusion way.The object of new algorithm is to improve the tracking precision of observed target by the multi-sensor fusion method without increasing the number of physical sensors.The theoretical analysis and experimental results show the feasibility and efficiency of the proposed algorithm.

Reinforcement learning-based missile terminal guidance of maneuvering targets with decoys

In this paper,a missile terminal guidance law based on a new Deep Deterministic Policy Gradient(DDPG)algorithm is proposed to intercept a maneuvering target equipped with an infrared decoy.First,to deal with the issue that the missile cannot accurately distinguish the target from the decoy,the energy center method is employed to obtain the equivalent energy center(called virtual target)of the target and decoy,and the model for the missile and the virtual decoy is established.Then,an improved DDPG algorithm is proposed based on a trusted-search strategy,which significantly increases the train efficiency of the previous DDPG algorithm.Furthermore,combining the established model,the network obtained by the improved DDPG algorithm and the reward function,an intelligent missile terminal guidance scheme is proposed.Specifically,a heuristic reward function is designed for training and learning in combat scenarios.Finally,the effectiveness and robustness of the proposed guidance law are verified by Monte Carlo tests,and the simulation results obtained by the proposed scheme and other methods are compared to further demonstrate its superior performance.

Impact time control guidance against maneuvering targets based on a nonlinear virtual relative model

Aiming at the problem of high-precision interception of air-maneuvering targets with impact time constraints,this paper proposes a novel guidance law based on a nonlinear virtual relative model in which the origin is attached to the target.In this way,the original maneuvering target is transformed into a stationary one.A polynomial function of the guidance command in the range domain with two unknown coefficients is introduced into the virtual model,one of the coefficients is determined to achieve the impact time constraint,and the other is determined to satisfy a newly defined virtual look angle constraint.For meeting the terminal constraints simultaneously,the guidance command can finally be obtained.The resulting solution is represented as a combination of proportional navigation guidance-like term which is aimed to meet the zero miss distance constraint,a bias term for impact time control by adjusting the length of the homing trajectory,and an additional term for target maneuvers.Numerous simulations demonstrate that the proposed law achieves an acceptable impact time error for various initial conditions against different types of maneuvering targets and shows more effective performance in comparison with those of other existing guidance laws.

WSN Mobile Target Tracking Based on Improved Snake-Extended Kalman Filtering Algorithm

A wireless sensor network mobile target tracking algorithm(ISO-EKF)based on improved snake optimization algorithm(ISO)is proposed to address the difficulty of estimating initial values when using extended Kalman filtering to solve the state of nonlinear mobile target tracking.First,the steps of extended Kalman filtering(EKF)are introduced.Second,the ISO is used to adjust the parameters of the EKF in real time to adapt to the current motion state of the mobile target.Finally,the effectiveness of the algorithm is demonstrated through filtering and tracking using the constant velocity circular motion model(CM).Under the specified conditions,the position and velocity mean square error curves are compared among the snake optimizer(SO)-EKF algorithm,EKF algorithm,and the proposed algorithm.The comparison shows that the proposed algorithm reduces the root mean square error of position by 52%and 41%compared to the SOEKF algorithm and EKF algorithm,respectively.

Three-dimensional cooperative guidance strategy and guidance law for intercepting highly maneuvering target

Cooperative interception of the target with strong maneuverability by multiple missiles with weak maneuverability in the three-dimensional nonlinear model is studied.Firstly,the three-dimensional nonlinear model of cooperative guidance is established.The three-dimensional reachable region is represented composed of lateral acceleration and longitudinal acceleration in the two-dimensional coordinate system.Secondly,the problem of the multiple missile’s reachable coverage area is transformed into the problem of cooperative coverage.A cooperative coverage strategy is proposed and an algorithm for quickly calculating the number of required missiles is designed.Then,the guidance law based on the cooperative coverage strategy is proposed,and it is proved that cooperative interception of the target can be achieved under the acceleration limit.Moreover,the relations among the number of missiles,the initial array position of terminal guidance and the coverage area of the target’s large maneuver are analyzed.The dynamic adjustment strategy of guidance parameters is proposed to reduce the guidance error.Finally,simulation results show that multiple missiles with low maneuverability can achieve effective interception of target with strong maneuverability through the proposed cooperative strategy and cooperative guidance method.

Multiple model efficient particle filter based track-before-detect for maneuvering weak targets

It is a tough problem to jointly detect and track a weak target, and it becomes even more challenging when the target is maneuvering. The above problem is formulated by using the Bayesian theory and a multiple model(MM) based filter is proposed. The filter presented uses the MM method to accommodate the multiple motions that a maneuvering target may travel under by adding a random variable representing the motion model to the target state. To strengthen the efficiency performance of the filter,the target existence variable is separated from the target state and the existence probability is calculated in a more efficient way. To examine the performance of the MM based approach, a typical track-before-detect(TBD) scenario with a maneuvering target is used for simulations. The simulation results indicate that the MM based filter proposed has a good performance in joint detecting and tracking of a weak and maneuvering target, and it is more efficient than the general MM method.

Three-dimensional time-varying sliding mode guidance law against maneuvering targets with terminal angle constraint

This paper deals with the problem of intercepting maneuvering targets with terminal angle constraints for missiles subjected to three-dimensional non-decoupling engagement geometry.To achieve the finite-time interception and satisfactory overload characteristics, a time varying sliding mode control methodology is developed based on a time base generator function. The main feature of the proposed guidance law guarantees the Line-of-Sight(LOS) angles to converge to small neighborhoods of the desired values at the interception time. First, a fractional power extended state observer is used to estimate the unknown target acceleration, which can significantly reduce the adaptive switching gain. The fractional power extended state observer enjoys the advantage of better noise tolerance. Then, a newly designed sliding mode surface is constructed by introducing a time base generator function and the time-varying sliding mode guidance law is developed based on this time-varying sliding surface. The proposed guidance law significantly reduces the overload magnitudes. Numerical simulations are carried out to verify the performance of the proposed guidance law.

Capturability of 3D RTPN guidance law against true-arbitrarily maneuvering target with maneuverability limitation

The capturability of the Three-Dimensional(3D)Realistic True Proportional Navigation(RTPN)guidance law is thoroughly analyzed.The true-arbitrarily maneuvering target is considered,which maneuvers along an arbitrary direction in 3D space with an arbitrary but upperbounded acceleration.The whole nonlinear relative kinematics between the interceptor and target is taken into account.First,the upper-bound of commanded acceleration of 3D RTPN is deduced,using a novel Lyapunov-like approach.Second,the reasonable selection range of navigation gain of3D RTPN is analyzed,when the maneuver limitation of interceptor is considered.After that,a more realistic definition of capture is adopted,i.e.,the relative range is smaller than an acceptable miss-distance while the approaching speed is larger than a required impact speed.Unlike previous researches which present Two-Dimensional(2D)capture regions,the inequality analysis technique is utilized to obtain the 3D capture region,where the three coordinates are the closing speed,transversal relative speed,and relative range.The obtained capture region could be taken as a sufficient-but-unnecessary condition of capture.The new theoretical findings are all given in explicit expressions and are more general than previous results.

Performance analysis of three-dimensional differential geometric guidance law against low-speed maneuvering targets

The performance of the three-dimensional differential geometric guidance law with proportional navigation formation against a target maneuvering arbitrarily with time-varying normal acceleration is thoroughly analyzed using the Lyapunov-like approach.The validation of this guidance law is firstly proved,and then the performance issues such as capturability,heading error control efficiency,line of sight rate convergence,and commanded acceleration requirement are analyzed,under the condition that the missile is initially flying toward the target with a speed advantage.It is proved that an intercept can occur and the line of sight rate and missile commanded acceleration can be limited in certain ranges,if the initial heading error is small and the navigation gain is sufficiently large.The nonlinear relative dynamics between the missile and the target is taken into full account,and the analysis process is simple and intuitive,due to the use of a convenient line of sight rotating coordinate system.Finally,the new theoretical findings are validated by numerical simulations.

Event-Triggered-Backstepping-Based Parallel Approaching Guidance Method for Maneuvering Target Interception

In order to achieve a straight ballistic trajectory of missile and reduce the update frequency of the missile normal acceleration for the interception of maneuvering target,a backstepping-based parallel approaching guidance method is designed with nonlinear disturbance observer(NDO)technique and event-triggered(ET)mechanism in this paper.In order to suppress the adverse e®ect of target maneuver,the NDO is designed to estimate the target maneuvering acceleration.Then,the NDO-based backstepping method is used to obtain the normal acceleration of missile and realize the parallel approaching guidance.In order to reduce the update frequency of missile normal acceleration,the ET mechanism is employed in the parallel approaching guidance method.If the missile trajectory is relatively straight,the normal acceleration of missile remains unchanged.On the contrary,if the missile trajectory is not straight,the normal acceleration of missile is updated to make the missile trajectory straight.In this way,the ET-based parallel approaching guidance can be obtained.Furthermore,a determined method for the initial missile°ight-path angle is proposed to keep the normal acceleration of missile at zero in the initial stage of interception.Besides,Lyapunov stability analysis method is used to prove that all signals in the closed-loop guidance system are uniformly ultimately bounded.Finally,simulation results show the e®ectiveness of the proposed guidance method.

Modified rolling guidance law for single moving mass controlled reentry vehicle against maneuvering target with impact angle constraints

This paper deals with the problem of guidance law design for the single moving mass controlled reentry vehicle when impact angle constraints and maneuvering target are taken into consideration.More specifically,a modified rolling guidance law is proposed with the interactive virtual target and the landing point prediction strategy.First,considering the fact that the roll channel can be controlled directly,the relative motion between the single moving mass controlled reentry vehicle and the target is described by the error angle between the relative velocity and the line-ofsight.Second,a nonlinear error angle command is given to reduce the rotation rate.To satisfy impact angle constraints,an interactive virtual target is presented and the‘‘S”formed velocity of the virtual target is given to abate the error angle tracking difficulty at the final stage of the reentry phase.Then,the landing point prediction strategy is employed and the motion variation trend is also taken into consideration.As the maneuvering target is replaced with the predicted landing point,the error angle tracking difficulty caused by the target velocity decreases,which is helpful to meet impact angle constraints and improve guidance accuracy at the same time.Finally,the finite-time rolling guidance law is proposed and proved via Lyapunov stability theorem.Compared with the existing method,lower-speed rotation,smaller missing distance and less impact angle errors are obtained,which can be demonstrated by numerical simulations.

Efficient coherent detection of maneuvering targets based on location rotation transform and non-uniform fast Fourier transform

Long-term coherent integration can remarkably improve the ability of detection and motion parameter estimation of radar for maneuvering targets.However,the linear range migration,quadratic range migration(QRM),and Doppler frequency migration within the coherent processing interval seriously degrade the detection and estimation performance.Therefore,an efficient and noise-resistant coherent integration method based on location rotation transform(LRT)and non-uniform fast Fourier transform(NuFFT)is proposed.QRM is corrected by the second-order keystone transform.Using the relationship between the rotation angle and Doppler frequency,a novel phase compensation function is constructed.Motion parameters can be rapidly estimated by LRT and NuFFT.Compared with several representative algorithms,the proposed method achieves a nearly ideal detection performance with low computational cost.Finally,experiments based on measured radar data are conducted to verify the proposed algorithm.

Consistent Extended Kalman Filter Design for Maneuvering Target Tracking and Its Application on Hand Position Tracking

This paper propees the consistent extended Kalman flter(CEKF)for the maneuvering target tracking(MTT)with nonlinear uncertain dynamics,and applies it on hand poition tracking.The general modlel of the MTT system i presented with unmodleled dynamics in terms of nonlinear unknown function of states.The CEKF is propoeed to ensure that the bounds of the estimation error's covariance matrix are av ailable through the flter algorithm.As a result,the creponding accuracy of the flter approach can be achieved online.Furthermore,a CEKF-baaed MTT algorithm is constructed via the tumning aw of the critical parameter matrix QE Finally,the efectiveness of CEKF i verified by MTT numerical simulations and hand tacking expeiments under dilferent maneuvens.Specifcally,two indices are employed to compare the CEKF with extended Kalman filter(EKF):the mean square errors(MSEa)and the bounded percentage,ie the percentage of the rang w bere the estimation error is encboed by the bound calculated by algorithms.All MSEs of CEKF are smaller than thoee of EKF,where the worst MSEa of CEKF and EKF are0.14 and 418 in the simulation,a8 well 80.11 and 059 in the expeiments,respectively;all bounded percentages of CEKF are larger than thoee of EKF,where the wonst average bounded percentages of CEKF and EKF ame 87.86%and 14.58%,8 well as 97.41%and 41.79%in the experiments,reapectively.

Design of integral sliding mode guidance law based on disturbance observer

With the increasing precision of guidance,the impact of autopilot dynamic characteristics and target maneuvering abilities on precision guidance is becoming more and more significant.In order to reduce or even eliminate the autopilot dynamic operation and the target maneuvering influence,this paper suggests a guidance system model involving a novel integral sliding mode guidance law(ISMGL).The method utilizes the dynamic characteristics and the impact angle,combined with a sliding mode surface scheme that includes the desired line-ofsight angle,line-of-sight angular rate,and second-order differential of the angular line-of-sight.At the same time,the evaluation scenario considere the target maneuvering in the system as the external disturbance,and the non-homogeneous disturbance observer estimate the target maneuvering as a compensation of the guidance command.The proposed system’s stability is proven based on the Lyapunov stability criterion.The simulations reveale that ISMGL effectively intercepted large maneuvering targets and present a smaller miss-distance compared with traditional linear sliding mode guidance laws and trajectory shaping guidance laws.Furthermore,ISMGL has a more accurate impact angle and fast convergence speed.