Design methodology of a mini-missile considering flight performance and guidance precision

The design of mini-missiles(MMs)presents several novel challenges.The stringent mission requirement to reach a target with a certain precision imposes a high guidance precision.The miniaturization of the size of MMs makes the design of the guidance,navigation,and control(GNC)have a larger-thanbefore impact on the main-body design(shape,motor,and layout design)and its design objective,i.e.,flight performance.Pursuing a trade-off between flight performance and guidance precision,all the relevant interactions have to be accounted for in the design of the main body and the GNC system.Herein,a multi-objective and multidisciplinary design optimization(MDO)is proposed.Disciplines pertinent to motor,aerodynamics,layout,trajectory,flight dynamics,control,and guidance are included in the proposed MDO framework.The optimization problem seeks to maximize the range and minimize the guidance error.The problem is solved by using the nondominated sorting genetic algorithm II.An optimum design that balances a longer range with a smaller guidance error is obtained.Finally,lessons learned about the design of the MM and insights into the trade-off between flight performance and guidance precision are given by comparing the optimum design to a design provided by the traditional approach.

Recorded recurrent deep reinforcement learning guidance laws for intercepting endoatmospheric maneuvering missiles

This work proposes a recorded recurrent twin delayed deep deterministic(RRTD3)policy gradient algorithm to solve the challenge of constructing guidance laws for intercepting endoatmospheric maneuvering missiles with uncertainties and observation noise.The attack-defense engagement scenario is modeled as a partially observable Markov decision process(POMDP).Given the benefits of recurrent neural networks(RNNs)in processing sequence information,an RNN layer is incorporated into the agent’s policy network to alleviate the bottleneck of traditional deep reinforcement learning methods while dealing with POMDPs.The measurements from the interceptor’s seeker during each guidance cycle are combined into one sequence as the input to the policy network since the detection frequency of an interceptor is usually higher than its guidance frequency.During training,the hidden states of the RNN layer in the policy network are recorded to overcome the partially observable problem that this RNN layer causes inside the agent.The training curves show that the proposed RRTD3 successfully enhances data efficiency,training speed,and training stability.The test results confirm the advantages of the RRTD3-based guidance laws over some conventional guidance laws.

Trajectory tracking guidance of interceptor via prescribed performance integral sliding mode with neural network disturbance observer

This paper investigates interception missiles’trajectory tracking guidance problem under wind field and external disturbances in the boost phase.Indeed,the velocity control in such trajectory tracking guidance systems of missiles is challenging.As our contribution,the velocity control channel is designed to deal with the intractable velocity problem and improve tracking accuracy.The global prescribed performance function,which guarantees the tracking error within the set range and the global convergence of the tracking guidance system,is first proposed based on the traditional PPF.Then,a tracking guidance strategy is derived using the integral sliding mode control techniques to make the sliding manifold and tracking errors converge to zero and avoid singularities.Meanwhile,an improved switching control law is introduced into the designed tracking guidance algorithm to deal with the chattering problem.A back propagation neural network(BPNN)extended state observer(BPNNESO)is employed in the inner loop to identify disturbances.The obtained results indicate that the proposed tracking guidance approach achieves the trajectory tracking guidance objective without and with disturbances and outperforms the existing tracking guidance schemes with the lowest tracking errors,convergence times,and overshoots.

Command filtered integrated estimation guidance and control for strapdown missiles with circular field of view

In this paper,an integrated estimation guidance and control(IEGC)system is designed based on the command filtered backstepping approach for circular field-of-view(FOV)strapdown missiles.The threedimensional integrated estimation guidance and control nonlinear model with limited actuator deflection angle is established considering the seeker's FOV constraint.The boundary time-varying integral barrier Lyapunov function(IBLF)is employed in backstepping design to constrain the body line-of-sight(BLOS)in IEGC system to fit a circular FOV.Then,the nonlinear adaptive controller is designed to estimate the changing aerodynamic parameters.The generalized extended state observer(GESO)is designed to estimate the acceleration of the maneuvering targets and the unmatched time-varying disturbances for improving tracking accuracy.Furthermore,the command filters are used to solve the"differential expansion"problem during the backstepping design.The Lyapunov theory is used to prove the stability of the overall closed-loop IEGC system.Finally,the simulation results validate the integrated system's effectiveness,achieving high accuracy strikes against maneuvering targets.

Six-Dimensional Guidance: The Strategies of Thinking Quality Cultivation in Senior High School English Discourse Learning

Taking the discourse learning of the new senior high school English textbook published by the People’s Education Press as an example,combined with the“six-dimensional guidance”deep reading strategy,and through the six-skill training strategies of“memory skill training,understanding skill training,application skill training,analytical skill training,evaluation skill training,creative skill training,”this paper aims to cultivate students’thinking profundity,logic,flexibility,sensitivity,criticality,and originality.It also promotes the real implementation of senior high school English deep reading that points to the cultivation of thinking quality in classroom teaching,and realizes the transformation from“conventional reading”to“deep reading”that reflects the core literacy of the discipline.

Exploration and Research on Employment Guidance System in Universities from the Perspective of Artificial Intelligence

In the context of the era of continuous development of artificial intelligence, the labor value of university students is impacted by technological substitution. Simultaneously, university students are also required to constantly update their skills. All of the above will be the challenge of university students’ employment prospects. However, artificial intelligence will also bring new opportunities, which will stimulate the innovation ability of university students and bring new directions for employment. In order to better cope with the possible impact of artificial intelligence, universities should incorporate employment guidance services into the “three-wide education” system. To achieve this, universities need to take the following measures: developing the dynamic monitoring system of university employment based on big data, constructing the employment guidance curriculum system of university students throughout the whole process, updating the mode of diversified employment guidance service as well as establishing a team of employment guidance teachers keeping pace with the times. These measures aim to better adapt to the job market demands in the context of artificial intelligence, guide students to actively respond to the possible impact of artificial intelligence technology, cultivate their core competencies and qualities that are less likely to be replaced by artificial intelligence, and promote the high-quality employment of university students.

IoV and Blockchain-Enabled Driving Guidance Strategy in Complex Traffic Environment

Diversified traffic participants and complex traffic environment(e.g.,roadblocks or road damage exist)challenge the decision-making accuracy of a single connected and autonomous vehicle(CAV)due to its limited sensing and computing capabilities.Using Internet of Vehicles(IoV)to share driving rules between CAVs can break limitations of a single CAV,but at the same time may cause privacy and safety issues.To tackle this problem,this paper proposes to combine IoV and blockchain technologies to form an efficient and accurate autonomous guidance strategy.Specifically,we first use reinforcement learning for driving decision learning,and give the corresponding driving rule extraction method.Then,an architecture combining IoV and blockchain is designed to ensure secure driving rule sharing.Finally,the shared rules will form an effective autonomous driving guidance strategy through driving rules selection and action selection.Extensive simulation proves that the proposed strategy performs well in complex traffic environment,mainly in terms of accuracy,safety,and robustness.

Identification of a Printed Anti-Counterfeiting Code Based on Feature Guidance Double Pool Attention Networks

The authenticity identification of anti-counterfeiting codes based on mobile phone platforms is affected by lighting environment,photographing habits,camera resolution and other factors,resulting in poor collection quality of anti-counterfeiting codes and weak differentiation of anti-counterfeiting codes for high-quality counterfeits.Developing an anticounterfeiting code authentication algorithm based on mobile phones is of great commercial value.Although the existing algorithms developed based on special equipment can effectively identify forged anti-counterfeiting codes,the anti-counterfeiting code identification scheme based on mobile phones is still in its infancy.To address the small differences in texture features,low response speed and excessively large deep learning models used in mobile phone anti-counterfeiting and identification scenarios,we propose a feature-guided double pool attention network(FG-DPANet)to solve the reprinting forgery problem of printing anti-counterfeiting codes.To address the slight differences in texture features in high-quality reprinted anti-counterfeiting codes,we propose a feature guidance algorithm that creatively combines the texture features and the inherent noise feature of the scanner and printer introduced in the reprinting process to identify anti-counterfeiting code authenticity.The introduction of noise features effectively makes up for the small texture difference of high-quality anti-counterfeiting codes.The double pool attention network(DPANet)is a lightweight double pool attention residual network.Under the condition of ensuring detection accuracy,DPANet can simplify the network structure as much as possible,improve the network reasoning speed,and run better on mobile devices with low computing power.We conducted a series of experiments to evaluate the FG-DPANet proposed in this paper.Experimental results show that the proposed FG-DPANet can resist highquality and small-size anti-counterfeiting code reprint forgery.By comparing with the existing algorithm based on texture,it is shown that the proposed method has a higher authentication accuracy.Last but not least,the proposed scheme has been evaluated in the anti-counterfeiting code blurring scene,and the results show that our proposed method can well resist slight blurring of anti-counterfeiting images.

Impact point prediction guidance of ballistic missile in high maneuver penetration condition

An impact point prediction(IPP) guidance based on supervised learning is proposed to address the problem of precise guidance for the ballistic missile in high maneuver penetration condition.An accurate ballistic trajectory model is applied to generate training samples,and ablation experiments are conducted to determine the mapping relationship between the flight state and the impact point.At the same time,the impact point coordinates are decoupled to improve the prediction accuracy,and the sigmoid activation function is improved to ameliorate the prediction efficiency.Therefore,an IPP neural network model,which solves the contradiction between the accuracy and the speed of the IPP,is established.In view of the performance deviation of the divert control system,the mapping relationship between the guidance parameters and the impact deviation is analysed based on the variational principle.In addition,a fast iterative model of guidance parameters is designed for reference to the Newton iteration method,which solves the nonlinear strong coupling problem of the guidance parameter solution.Monte Carlo simulation results show that the prediction accuracy of the impact point is high,with a 3 σ prediction error of 4.5 m,and the guidance method is robust,with a 3 σ error of 7.5 m.On the STM32F407 singlechip microcomputer,a single IPP takes about 2.374 ms,and a single guidance solution takes about9.936 ms,which has a good real-time performance and a certain engineering application value.

An Investigation Into the Needs and Challenges of County-Level Family Education Guidance Services and Corresponding Improvement Measures

The delivery of targeted family education guidance services is essential for establishing a three-in-one education model that encompasses families,schools,and communities.It is also the key to creating a favorable educational environment that promotes the comprehensive and healthy development of individual students.To gain a comprehensive understanding of family education characteristics and trends in Chinese counties,accurately tap into the educational needs of parents,and effectively identify strengths and weaknesses in family education guidance services,this paper employed a quantitative research method based on a questionnaire survey and interview data from J district of C city after years of continuous monitoring of the quality of family education in the area,aiming to explore these issues and put forward several suggestions for improvement.The results indicate that the family learning environment and atmosphere in the district are generally favorable,while parental educational competence requires further improvement.Parents express a strong desire for interactive,systematic,and fragmented family education guidance from schools.Most parents acknowledge the significance of receiving guidance on family education,yet they are disinclined to actively engage in learning-related activities.While the operational mechanisms of county-level family education guidance services have been continuously improved,there is a need for greater overall coordination.Furthermore,the potential of school-led family education guidance services has yet to be fully tapped,and the scientific and professional standards of such guidance need to be further enhanced.Based on the aforementioned findings,we propose recommendations for improvement.Using J district’s effective improvement practices in management,curriculum,and teams as an example,we intend to explore practical ways to promote county-level family education guidance services and provide a valuable reference for the establishment of a comprehensive and effective system to improve such services.

Bee Colony Optimization Algorithm for Routing and Wavelength Assignment Based on Directional Guidance in Satellite Optical Networks

With the development of satellite communication,in order to solve the problems of shortage of on-board resources and refinement of delay requirements to improve the communication performance of satellite optical networks,this paper proposes a bee colony optimization algorithm for routing and wavelength assignment based on directional guidance(DBCO-RWA)in satellite optical networks.In D-BCORWA,directional guidance based on relative position and link load is defined,and then the link cost function in the path search stage is established based on the directional guidance factor.Finally,feasible solutions are expanded in the global optimization stage.The wavelength utilization,communication success probability,blocking rate,communication hops and convergence characteristic are simulated.The results show that the performance of the proposed algorithm is improved compared with existing algorithms.

Cooperative trajectory optimization of UAVs in approaching stage using feedback guidance methods

This paper mainly studies the problem of using UAVs to provide accurate remote target indication for hypersonic projectiles.Based on the optimal trajectory trends and feedback guidance methods,a new cooperative control algorithm is proposed to optimize trajectories of multi-UAVs for target tracking in approaching stage.Based on UAV kinematics and sensor performance models,optimal trajectory trends of UAVs are analyzed theoretically.Then,feedback guidance methods are proposed under the optimal observation trends of UAVs in the approaching target stage,producing trajectories with far less computational complexity and performance very close to the best-known trajectories.Next,the sufficient condition for the UAV to form the optimal observation configuration by the feedback guidance method is presented,which guarantees that the proposed method can optimize the observation trajectory of the UAV in approaching stage.Finally,the feedback guidance method is numerically simulated.Simulation results demonstrate that the estimation performance of the feedback guidance method is superior to the Lyapunov guidance vector field(LGVF)method and verify the effectiveness of the proposed method.Additionally,compared with the receding horizon optimization(RHO)method,the proposed method has the same optimization ability as the RHO method and better real-time performance.

Shanghai mapped out the guidance to“Cosmetics Samples”for the first time

On April 7th,2023,the supervisory department of Xuhui district published the first Guidance to“Cosmetics Samples”for the First Time(Trial).It unified the management requirement regarding cosmetics samples,guided managers to develop responsibility awareness and prevent and advert risks beforehand.Besides,it identified the definition of“cosmetics samples”.

Hybrid gradient vector fields for path-following guidance

Guidance path-planning and following are two core technologies used for controlling un-manned aerial vehicles(UAVs)in both military and civilian applications.However,only a few approaches treat both the technologies simultaneously.In this study,an innovative hybrid gradient vector fields for path-following guidance(HGVFs-PFG)algorithm is proposed to control fixed-wing UAVs to follow a generated guidance path and oriented target curves in three-dimensional space,which can be any combination of straight lines,arcs,and helixes as motion primitives.The algorithm aids the creation of vector fields(VFs)for these motion primitives as well as the design of an effective switching strategy to ensure that only one VF is activated at any time to ensure that the complex paths are followed completely.The strategies designed in earlier studies have flaws that prevent the UAV from following arcs that make its turning angle too large.The proposed switching strategy solves this problem by introducing the concept of the virtual way-points.Finally,the performance of the HGVFs-PFG algorithm is verified using a reducedorder autopilot and four representative simulation scenarios.The simulation considers the constraints of the aircraft,and its results indicate that the algorithm performs well in following both lateral and longitudinal control,particularly for curved paths.In general,the proposed technical method is practical and competitive.

Extended optimal guidance law with impact angle and acceleration constriants

The extended optima straints of miss distance and Schwartz inequality. To reduce guidance law with terminal conmpact angle is derived by the terminal acceleration and eliminate gravity disturbance absolutely, the object function, which designs the weight of control command to be the power function of time-to-go＇s reciprocal, is given. And the gravity is considered when building the state equation. Based on the parsing express of the guidance command change with varying time and adjoint system analysis method, the command characteristics and the non-dimensional miss distance of the guidance law are analyzed, a design principle of guidance order coefficients is discussed. Finally, based on the requirement of engineering, the method to calculate the guidance condition and maximal required acceleration of the guidance law is given. The simulation demonstrates that not only the guidance law can satisfy the terminal position and impact angle constraints, but also the terminal acceleration can be converged toward zero, which will support a good situation for the terminal angle of attacking control.

Variable structure guidance law for attacking surface maneuver targets

The characteristics of surface maneuver targets are analyzed and a 3-D relative motion model for missiles and targets is established. A variable structure guidance law is designed considering the characteristics of targets. In the guidance law, the distance between missiles and targets as well as the missile-target relative velocity are all substituted by estimation values. The estimation errors, the target＇s velocity, and the maneuver acceleration are all treated as bounded disturbance. The guidance law proposed can be implemented conveniently in engineering with little target information. The performance of the guidance system is analyzed theoretically and the numerical simulation result shows the effectiveness of the guidance law.

Integrated Entry Guidance for Reusable Launch Vehicle

A method for the implementation of integrated three-degree-of-freedom constrained entry guidance for reusable launch vehicle is presented. Given any feasible entry conditions, terminal area energy management interface conditions, and the reference trajectory generated onboard then, the method can generate a longitudinal guidance profile rapidly, featuring linear quadratic regular method and a proportional-integral-derivative tracking law with time-varying gains, which satisfies all the entry corridor constraints and meets the requirements with high precision. Afterwards, by utilizing special features of crossrange parameter, establishing bank-reversal corridor, and determining bank-reversals according to dynamically adjusted method, the algorithm enables the lateral entry guidance system to fly a wide range of missions and provides reliable and good performance in the presence of significant aerodynamic modeling uncertainty. Fast trajectory guidance profiles and simulations with a reusable launch vehicle model for various missions and aerodynamic uncertainties are presented to demonstrate the capacity and reliability of this method.

Classic axon guidance molecules control correct nerve bridge tissue formation and precise axon regeneration

The peripheral nervous system has an astonishing ability to regenerate following a compression or crush injury;however,the potential for full repair following a transection injury is much less.Currently,the major clinical challenge for peripheral nerve repair come from long gaps between the proximal and distal nerve stumps,which prevent regenerating axons reaching the distal nerve.Precise axon targeting during nervous system development is controlled by families of axon guidance molecules including Netrins,Slits,Ephrins and Semaphorins.Several recent studies have indicated key roles of Netrin1,Slit3 and EphrinB2 signalling in controlling the formation of new nerve bridge tissue and precise axon regeneration after peripheral nerve transection injury.Inside the nerve bridge,nerve fibroblasts express EphrinB2 while migrating Schwann cells express the receptor EphB2.EphrinB2/EphB2 signalling between nerve fibroblasts and migrating Schwann cells is required for Sox2 upregulation in Schwann cells and the formation of Schwann cell cords within the nerve bridge to allow directional axon growth to the distal nerve stump.Macrophages in the outermost layer of the nerve bridge express Slit3 while migrating Schwann cells and regenerating axons express the receptor Robo1;within Schwann cells,Robo1 expression is also Sox2-dependent.Slit3/Robo1 signalling is required to keep migrating Schwann cells and regenerating axons inside the nerve bridge.In addition to the Slit3/Robo1 signalling system,migrating Schwann cells also express Netrin1 and regenerating axons express the DCC receptor.It appears that migrating Schwann cells could also use Netrin1 as a guidance cue to direct regenerating axons across the peripheral nerve gap.Engineered neural tissues have been suggested as promising alternatives for the repair of large peripheral nerve gaps.Therefore,understanding the function of classic axon guidance molecules in nerve bridge formation and their roles in axon regeneration could be highly beneficial in developing engineered neural tissue for more effective peripheral nerve repair.

Ultrasound guidance for transforaminal percutaneous endoscopic lumbar discectomy may prevent radiation exposure: A case report

BACKGROUND Percutaneous endoscopic lumbar discectomy(PELD)has become a mature and mainstream minimally invasive surgical technique for treating lumbar disc herniation(LDH).Repeated fluoroscopy,with more than 30 shots on average,is inevitable to ensure its accuracy and safety.However,exposure to X-rays may pose a threat to human health.We herein report a case of ultrasound(US)-assisted PELD in two levels of LDH to explore a new possibility that can reduce the radiation dose during puncture and cannulation in PELD.CASE SUMMARY A 38-year-old man with low back pain and left leg pain for more than 7 years came to our clinic,his symptoms had aggravated for 1 month,and he was diagnosed with L3-4 and L4-5 disc herniations.He received US-guided PELD with good results:His straight leg elevation increased from 40 to 90 degrees after PELD,and his visual analog scale(VAS)and Oswestry Disability Index scores both significantly decreased immediately and 6 mo after PELD.With the guidance of US,he received only two shots of fluoroscopy(fluoroscopic time:4.4 s;radiation dose:3.98 mGy).To our knowledge,this is the first case of US-guided puncture and cannulation of PELD for LDH at two levels.CONCLUSION US could be used to guide PELD and has the potential to largely reduce radiation than traditional X-ray guidance.