Boost-Phase ballistic missile trajectory estimation with ground based radar

A conditional boost-phase trajectory estimation method based on ballistic missile （BM） information database and classification is developed to estimate and predict boos-phase BM trajectory. The main uncertain factors to describe BM dynamics equation are reduced to the control law of trajectory pitch angle in boost-phase. After the BM mass at the beginning of estimation, the BM attack angle and the modification of engine thrust denoting BM acceleration are modeled reasonably, the boost-phase BM trajectory estimation with ground based radar is well realized. The validity of this estimation method is testified by computer simulation with a typical example.

QPSO-based algorithm of CSO joint infrared super-resolution and trajectory estimation

The midcourse ballistic closely spaced objects（CSO） create blur pixel-cluster on the space-based infrared focal plane,making the super-resolution of CSO quite necessary.A novel algorithm of CSO joint super-resolution and trajectory estimation is presented.The algorithm combines the focal plane CSO dynamics and radiation models,proposes a novel least square objective function from the space and time information,where CSO radiant intensity is excluded and initial dynamics（position and velocity） are chosen as the model parameters.Subsequently,the quantum-behaved particle swarm optimization（QPSO） is adopted to optimize the objective function to estimate model parameters,and then CSO focal plane trajectories and radiant intensities are computed.Meanwhile,the estimated CSO focal plane trajectories from multiple space-based infrared focal planes are associated and filtered to estimate the CSO stereo ballistic trajectories.Finally,the performance（CSO estimation precision of the focal plane coordinates,radiant intensities,and stereo ballistic trajectories,together with the computation load） of the algorithm is tested,and the results show that the algorithm is effective and feasible.

A novel framework to intercept GPS-denied,bomb-carrying,nonmilitary,kamikaze drones:Towards protecting critical infrastructures

Protection of urban critical infrastructures(CIs)from GPS-denied,bomb-carrying kamikaze drones(G-BKDs)is very challenging.Previous approaches based on drone jamming,spoofing,communication interruption and hijacking cannot be applied in the case under examination,since G-B-KDs are uncontrolled.On the other hand,drone capturing schemes and electromagnetic pulse(EMP)weapons seem to be effective.However,again,existing approaches present various limitations,while most of them do not examine the case of G-B-KDs.This paper,focuses on the aforementioned under-researched field,where the G-B-KD is confronted by two defensive drones.The first neutralizes and captures the kamikaze drone,while the second captures the bomb.Both defensive drones are equipped with a net-gun and an innovative algorithm,which,among others,estimates the locations of interception,using a real-world trajectory model.Additionally,one of the defensive drones is also equipped with an EMP weapon to damage the electronics equipment of the kamikaze drone and reduce the capturing time and the overall risk.Extensive simulated experiments and comparisons to state-of-art methods,reveal the advantages and limitations of the proposed approach.More specifically,compared to state-of-art,the proposed approach improves:(a)time to neutralize the target by at least 6.89%,(b)maximum number of missions by at least 1.27%and(c)total cost by at least 5.15%.

Anisotropy safety potential field model under intelligent and connected vehicle environment and its application in car-following modeling

Potential field theory,as a theory that can also be applied to vehicle control,is an emerging risk quantification approach to accommodate the connected and self-driving vehicle environment.Vehicles have different risk impact effects on other road participants in each direction under the influence of road rules.This variability exhibited by vehicles in each direction is not considered in the previous potential field model.Therefore,this paper proposed a potential field model that takes the anisotropy of vehicle impact into account:(1)introducing equivalent distances to separate the potential field area in the different directions before and after the vehicle;(2)introducing co-virtual forces to characterize the effect of the side-by-side travel phenomenon on vehicle car-following travel;(3)introducing target forces and lane resistance,which regress the control of desired speed to control the acceptable risk of drivers.The Next Generation Simulation(NGSIM)dataset is used in this study to create the model's initial parameter values based on the artificial swarm algorithm.The simulation findings indicate that when the vehicle is given the capacity to perceive the surrounding traffic environment,the suggested the anisotropic safety potential field model(ASPFM)performs better in terms of driving safety.

An Improved Underwater Confrontation Simulation Method of Naval Amphibious Operational Training System

This paper described an improved underwater confrontation simulation method of naval amphibious operational training system. The initial position of submarine forces on the enemy is generated automatically, and the attacking distance model of torpedoes is established based on the kinematics theory, which is more flexible and reasonable to judge the launch condition compared to traditional method. The two kinds of confrontation behavior models on the enemy submarine are created to depict its tactical action from the defensive to the offensive as well as the contrary, ensuring that operational style is simulated more comprehensively and properly. The existing motion trajectory estimation and collision detection algorithms on operational platforms are also improved to reduce the iteration error and further enhance the detection accuracy of target hit.