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The authors address the problem of observability analysis and enhancement for missiles equipped with strapdown seekers, especially considering the line‐of‐sight angle‐only measurements and the constraints on impact angle and terminal acceleration. First, based on the generalised polynomial chaos expansion, a novel data‐driven observability analysis method is proposed to quantitatively analyse the observability of the radome aberration estimation system in real time, including the observability condition, the observability degree of each state and the effect of stochastic noises. The results show that under conventional proportional navigation guidance, the radome aberration estimation system is weakly observable with line‐of‐sight angle‐only measurements. To address this problem, a novel manoeuvre algorithm, the observability‐enhanced guidance law, is introduced to enhance the system observability within specified constraints, thereby improving the estimation performance. This guidance law incorporates a bias term to meet terminal constraints, and optimises the navigation gain using the proposed observability indices. Simulations are conducted to verify the performance of the proposed guidance law in conjunction with a target state estimator. [ABSTRACT FROM AUTHOR]

Signage functions as guidance and distribution assistance, directly affecting the operational efficiency of traffic in and around the comprehensive transportation hubs. Among the elements of signage, the visual guidance effect is the key factor affecting the information conveyance, which should be evaluated during the design and optimization process. This study conducted field investigations and developed panoramic videos for multiple transportation hubs in China and designed a survey accordingly. Human subjects were recruited to watch panoramic videos via virtual reality (VR) and respond to the surveys. The results show that the degree of visual attention of travelers significantly affects the evaluation results of guidance signage, with the influence being inversely proportional. Key factors affecting visual attention include accurate legibility, obstruction and defacement rates, informativeness, and whether signage is set up in a hierarchical manner. In unfamiliar environments, travelers focus on the overall context and closely observe the interaction between directional signs and their surroundings. The prominence and visibility of signage are influenced by interactions within the spatial environment. Notably, simple and clear signs are more likely to attract travelers' attention, and their directional information is more easily comprehended. Moreover, when the destination is clearly defined, visual attention significantly directs pedestrians' wayfinding behavior. [ABSTRACT FROM AUTHOR]

This paper proposes a novel path-following method for autonomous ships that optimizes overall performance by balancing course changes and convergence to the original route. The proposed method extends the line-of-sight (LOS) guidance law by dynamically adjusting key parameters based on the ship's cross-track error (XTE) and the distance of new course considering maneuvering characteristics. By incorporating these maneuvering characteristics, the method enables more precise adjustments during course changes, improving overall path-following performance. Simulation results showed that the proposed method outperformed three existing methods, including the traditional LOS guidance law, by minimizing overshoot and maintaining reasonable XTE during larger course changes. It achieved the lowest mean absolute cross-track error (MAE) while also significantly reducing the total time required to follow the path, highlighting its superior accuracy and efficiency in path following. These outcomes highlight the method's potential to enhance significantly the path-following capabilities of autonomous vessels, contributing to greater efficiency and accuracy in pre-determined route navigation. [ABSTRACT FROM AUTHOR]

For missile-borne platforms, traditional SAR technology consistently encounters two significant shortcomings: geometric distortion of 2D images and the inability to achieve forward-looking imaging. To address these issues, this paper explores the feasibility of using a maneuvering trajectory to enable forward-looking and three-dimensional imaging by analyzing the maneuvering characteristics of an actual missile-borne platform. Additionally, it derives the corresponding resolution characterization model, which lays a theoretical foundation for future applications. Building on this, the paper proposes a three-dimensional super-resolution imaging algorithm that combines axis rotation with compressed sensing. The axis rotation not only realizes the dimensionality reduction of data, but also can expand the observation scenario in the cross-track dimension. The proposed algorithm first focuses on the track-vertical plane to extract 2D position parameters. Then, a compressed sensing-based process is applied to extract reflection coefficients and super-resolution cross-track position parameters, thereby achieving precise 3D imaging reconstruction. Finally, numerical simulation results confirm the effectiveness and accuracy of the proposed algorithm. [ABSTRACT FROM AUTHOR]

In this paper, distributed three‐dimensional (3D) cooperative guidance laws are designed for leader–follower multiple missiles to achieve simultaneous attack at a specified time. The guidance laws are derived from the biased proportional navigation guidance (PNG) law. Two fixed‐time distributed algorithms with time‐varying coefficients are proposed to track the state of the leader under undirected and directed topologies, respectively. The upper bounds of convergence times for the tracking algorithms are obtained. The biased guidance terms of followers are designed to track the leader with the proposed algorithms and the biased guidance term of the leader is designed to achieve specified impact time. Then, an auxiliary function is included into the biased guidance terms to meet the field‐of‐view (FOV) constraints. The leading angles' properties and convergence times under the proposed guidance laws are further analyzed. Numerical simulations are given to verify the effectiveness of the proposed cooperative guidance laws. [ABSTRACT FROM AUTHOR]

Copyright of Przegląd Elektrotechniczny is the property of Przeglad Elektrotechniczny and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

To deal with the offense-defense confrontation problem of multi-missile cooperative intercepting a high-speed and large-maneuvering target, a differential game-based cooperative interception guidance law with collision avoidance is proposed, in which the offense-defense parties are the incoming target and the interceptors, respectively. Given that both offense-defense parties have uniformly decreasing speeds and first-order biproper dynamics, the relative motion models among the offense-defense parties are established, and the performance indices of the target and the interceptors are proposed. After that, the cooperative interception guidance law with collision avoidance is derived based on a differential game. The guidance law considers the effects of speed variations and rudder layouts on the motions of both offense-defense parties, ensuring excellent algorithmic real-time property and interception accuracy while introducing inter-missile collision avoidance constraints. In addition, the parameters of the target performance index are set according to the target acceleration information estimated by the interceptors. The simulation results verify the effectiveness of the guidance law designed in this paper, under various three-to-one scenarios, the interceptors could achieve collision-free interceptions with the interception accuracy of less than 5 m and the interception time difference of less than 0.1 s. [ABSTRACT FROM AUTHOR]

Aiming at the salvo-attack problem of multiple missiles, a distributed cooperative guidance law based on the event-triggered mechanism is proposed, which enables missiles with large differences in spatial location and velocity to achieve simultaneous attacks with only a few dozen information exchanges. It effectively reduces the generation of control commands and communication frequency, thereby reducing channel load and improving communication efficiency and reliability. Compared to traditional periodic sampling communication, the number of communications has been reduced by over 90 % . The guidance process is divided into two stages. The first stage is the cooperative guidance stage, where missiles achieve consensus of the time-to-go estimates through information exchange. In this stage, each missile is designed with an event-triggered function based on its own state error, and the missile only updates and transmits its information in the communication network when the error meets the set threshold, effectively reducing the occupancy rate of missile-borne resources during the cooperation process. The second stage is the independent guidance stage, where missiles can hit the target simultaneously while keeping the communication network silent. This is achieved by ensuring that the time-to-go estimates of missiles can represent the real time-to-go after achieving consensus. By the design of the two-stage guidance law and the replacement of the event-triggered function, the cooperative guidance system can be ensured to remain stable in scenarios where the leader missile is present and destroyed, and this excludes Zeno behavior. The stability of the cooperative guidance law is rigorously proved by algebraic graph theory, matrix theory, and the Lyapunov method. Finally, the numerical simulation results demonstrate the validity of the algorithm and the correctness of the stability analysis. [ABSTRACT FROM AUTHOR]

In this paper, targeting the problem that it is difficult to deal with the time-varying sideslip angle of an underactuated unmanned surface vehicle (USV), a line–of–sight (LOS) guidance law based on an improved extended state observer (ESO) is proposed. A reduced-order ESO is introduced into the identification of the sideslip angle caused by the environmental disturbance, which ensures a fast and accurate estimation of the sideslip angle. This enables the USV to follow the reference path with high precision, despite external disturbances from wind, waves, and currents. These unknown disturbances are modeled as drift, which the modified ESO-based LOS guidance law compensates for using the ESO. In the guidance subsystem incorporating the reduced-order state observer, the observer estimation and track errors are proved uniformly ultimately bounded. Simulation and experimental results are presented to validate the effectiveness of the proposed method. The simulation and comparison results demonstrate that the proposed ELOS guidance can help a USV track different types of paths quickly and smoothly. Additionally, the experimental results confirm the feasibility of the method. [ABSTRACT FROM AUTHOR]

Maritime transport plays a critical role in global logistics. Compared to road transport, the pace of research and development is much slower for maritime transport. It faces many major challenges, such as busy ports, long journeys, significant accidents, and greenhouse gas emissions. The problems have been exacerbated by recent regional conflicts and increasing international shipping demands. Maritime Autonomous Surface Ships (MASSs) are widely regarded as a promising solution to addressing maritime transport problems with improved safety and efficiency. With advanced sensing and path-planning technologies, MASSs can autonomously understand environments and navigate without human intervention. However, the complex traffic and water conditions and the corner cases are large barriers in the way of MASSs being practically deployed. In this paper, to address the above issues, we investigated the application of Large Language Models (LLMs), which have demonstrated strong generalization abilities. Given the substantial computational demands of LLMs, we propose a framework for LLM-assisted navigation in connected MASSs. In this framework, LLMs are deployed onshore or in remote clouds, to facilitate navigation and provide guidance services for MASSs. Additionally, certain large oceangoing vessels can deploy LLMs locally, to obtain real-time navigation recommendations. To the best of our knowledge, this is the first attempt to apply LLMs to assist with ship navigation. Specifically, MASSs transmit assistance requests to LLMs, which then process these requests and return assistance guidance. A crucial aspect, which has not been investigated in the literature, of this safety-critical LLM-assisted guidance system is the knowledge and safety performance of the LLMs, in regard to ship handling, navigation rules, and skills. To assess LLMs' knowledge of navigation rules and their qualifications for navigation assistance systems, we designed and conducted navigation theory tests for LLMs, which consisted of more than 1500 multiple-choice questions. These questions were similar to the official theory exams that are used to award the Officer Of the Watch (OOW) certificate based on the Standards of Training, Certification, and Watchkeeping (STCW) for Seafarers. A wide range of LLMs were tested, which included commercial ones from OpenAI and Baidu and an open-source one called ChatGLM, from Tsinghua. Our experimental results indicated that among all the tested LLMs, only GPT-4o passed the tests, with an accuracy of 86%. This suggests that, while the current LLMs possess significant potential in regard to navigation and guidance systems for connected MASSs, further improvements are needed. [ABSTRACT FROM AUTHOR]

In this article, we study the cooperative target‐fencing problem of multiple double‐integrator systems over a state‐dependent communication network. We propose a distributed control law to asymptotically fence a moving target while achieving both collision avoidance and connectivity preservation of the vehicles. In particular, a distributed observer is employed by each vehicle to estimate the position and the velocity of the target. Compared with the existing results, our approach can accommodate a larger class of target's trajectories. Furthermore, our control law is more practical since we do not require all vehicles to know the trajectory of the target. The effectiveness of our approach is illustrated by a numerical example. [ABSTRACT FROM AUTHOR]

This paper is concerned with the translational guidance of multirotor aerial vehicles with uncertain dynamics and equipped with short-range detection sensors in a scenario containing disturbances/uncertainties, multiple accelerated obstacles, and velocity constraints. To address this problem, we propose a robust guidance strategy based on the continuous control obstacles method. To handle disturbances and uncertainties, the proposed method tightens the position and velocity admissible sets according to the respective tracking errors. Moreover, a hybrid prescribed-time arbitrary-order differentiator is employed to robustly estimate the obstacles' velocities and accelerations within a prescribed time interval using measurements from a short-range sensor. As a result, the proposed method can fit into the available time for executing an avoidance maneuver upon the detection and tracking of obstacles. Then, we build a set of possible future positions for the obstacles according to their observed velocities and accelerations, and use this set to calculate a position command for the guided vehicle. The proposed method is experimentally evaluated using an augmented-reality setup composed of a Crazyflie quadcopter, motion capture cameras, and virtual obstacles. The results show that the proposed method is viable for real-time implementation and effective in providing collision avoidance and satisfying velocity constraints. [ABSTRACT FROM AUTHOR]

Copyright of Systems Engineering & Electronics is the property of Journal of Systems Engineering & Electronics Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Aiming at the interception constraint posed by defensive aircrafts against hypersonic morphing vehicles (HMVs) during the terminal guidance phase, this paper designed a guidance law with the finite-time convergence theory and control allocation methods based on the event-triggered theory, achieving evasion of the defensive aircraft and targeting objectives for a morphing vehicle in the terminal guidance phase. Firstly, this paper established the aircraft motion model; the relative motion relationships between HMV, defensive aircraft, and target; and the control equations for the guidance system. Secondly, a guidance law with finite-time convergence was designed, establishing a controller with the angle between the aircraft–target–defense aircraft triplet as the state variable and lift as the control variable. By ensuring the angle was non-zero, the aircraft maintained a certain relative distance from the defense aircraft, achieving evasion of interception. The delay characteristic of the aircraft's flight controller was considered, analyzing its delay stability and applying control compensation. Thirdly, a multi-model switching control allocation method based on an event-triggered mechanism was designed. Optimal attack and bank angles were determined based on acceleration control variables, considering different sweep angles. Finally, simulations were conducted to validate the effectiveness and robustness of the designed guidance laws. [ABSTRACT FROM AUTHOR]

Advanced computational methods are being applied to address traditional guidance problems, yet research is still ongoing regarding how to utilize them effectively and scientifically. A numerical root-finding method was proposed to determine the bias in biased proportional navigation to achieve the impact time control without time-to-go estimation. However, the root-finding algorithm in the original method might experience efficiency and convergence issues. This paper introduces an enhanced method based on neural networks, where the bias is directly output by the neural networks, significantly improving computational efficiency and addressing convergence issues. The novelty of this method lies in the development of a reasonable structure that appropriately integrates off-the-shelf machine learning techniques to effectively enhance the original iteration-based methods. In addition to demonstrating its effectiveness and performance of its own, two comparative scenarios are presented: (a) Evaluate the time consumption when both the proposed and the original methods operate at the same update frequency. (b) Compare the achievable update frequencies of both methods under the condition of equal real-world time usage. [ABSTRACT FROM AUTHOR]

This paper aims to analyze the stability of a special class of single-channel slow-rotating homing missiles using the Frank–Wall stability criterion. To achieve this, starting from the model of a slow-rolling missile with six degrees of freedom (6 DOFs) in the body frame, a 6-DOFs model in the Resal frame is obtained, which is used to linearize the coupled commanded motion. Based on the linearized model, we obtain the structural scheme of the commanded object and define the flight quality parameters. The obtained linear model has a complex representation (with real and imaginary parts) due to the coupling between longitudinal channels for the rolling missile. Then, the kinematic guidance equations, the seeker equations and the actuator relations using a switching function, specific to the slow-rolling single-channel missile, are defined. The guidance kinematic equations, the seeker equations and the actuator model are linearized in the Resal frame, and the structural diagram of the homing missile is constructed. Starting from this, the characteristic polynomial having complex coefficients is determined and then analyzed with the Frank–Wall stability criterion. Based on the analysis, a stability range is determined for the navigation constant (k) , and a minimum and possibly a maximum limit for the time to hit the target t g o is obtained. The stability range defined for the navigation constant in the linear model is finally validated in the nonlinear model in the body frame. [ABSTRACT FROM AUTHOR]

Previous control methods developed by our research team cannot satisfy the high accuracy requirements of unmanned surface vessel (USV) path-tracking during bathymetric mapping because of the excessive overshoot and slow convergence speed. For this reason, this study developed an adaptive fuzzy integral-derivative line-of-sight (AFIDLOS) method for USV path-tracking control. Integral and derivative terms were added to counteract the effect of the sideslip angle with which the USV could be quickly guided to converge to the planned path for bathymetric mapping. To obtain high accuracy of the look-ahead distance, a fuzzy control method was proposed. The proposed method was verified using simulations and outdoor experiments. The results demonstrate that the AFIDLOS method can reduce the overshoot by 79.85%, shorten the settling time by 55.32% in simulation experiments, reduce the average cross-track error by 10.91% and can ensure a 30% overlap of neighboring strips of bathymetric LiDAR outdoor mapping when compared with the traditional guidance law. [ABSTRACT FROM AUTHOR]

This paper proposes a trajectory-optimization problem for spacecraft close proximity to a noncooperative target, aiming at the generation of a six-degree-of-freedom (DOF) trajectory with the fuel-optimal objective value and considering multiple constraints on the control magnitude, line-of-sight, and glide-slope. The line-of-sight and glide-slope constraints are coupled between translational and rotational motions. The dual quaternion is an effective method for establishing the translationally and rotationally coupled model, because it can represent the translation and rotation in an integrated manner. Therefore, in this study, the trajectory-optimization problem of spacecraft close proximity coupled with position and attitude is established using dual quaternions. Next, the close-proximity trajectory-optimization problem is converted into a nonlinear programming problem, which can be solved efficiently using well-developed algorithms such as convex optimization. However, the zero-order hold used in the discrete method of convex optimization is an equidistant dispersion, which cannot guarantee the satisfaction of constraints between discrete points. Therefore the pseudospectral convex method is proposed using nonequidistant collocation points to mitigate the problem of constraint violation between discrete points and improve the accuracy and computational efficiency of the algorithm. The proposed algorithm can be applied to tasks such as rendezvous and docking with noncooperative targets and close proximity. Finally, the effectiveness of the proposed method was validated via numerical simulation, and the results were compared with those of the existing approach, GPOPS. The results indicate that the proposed algorithm is superior to GPOPS in computational efficiency and objective values. [ABSTRACT FROM AUTHOR]

A leading concern about single IRB (sIRB) review for multisite studies, as is now required by federal policies, is whether and how sIRBs consider local context in their review. While several types of local context considerations have been proposed, there is no shared agreement among those charged with the ethics oversight of human subjects research as to the goals and content of local context review, nor the types of research studies for which sIRB review might be inappropriate. Through a scoping review of published scholarship, public comments, and federal guidance documents, we identified five assumed goals for local context review: protecting the rights and welfare of local participants; ensuring compliance with applicable laws and policies; assessing feasibility; promoting the quality of research; and promoting procedural justice. While a variety of content was proposed to be relevant, it was largely grouped into four domains: population/participant‐level characteristics; investigator and research team characteristics; institution‐level characteristics; and state and local laws. Proposed characteristics for exclusion from sIRB requirements reflected both protection‐ and efficiency‐based concerns. These findings can inform ongoing efforts to assess the implications of policies mandating sIRB review, and when exceptions to those policies might be appropriate. [ABSTRACT FROM AUTHOR]

Autonomous navigation is currently subject to particular interest for naval and commercial vessels. In addition to the regulatory effort, several pieces of research tackled the development of new guidance laws, stable and robust control algorithms, methodologies to increase situational awareness, and collision avoidance algorithms. However, most of these systems blindly trust information from navigation sensors, which can malfunction or, even worse, have their data altered by cyber-attacks. This last scenario will be increasingly common shortly and represents a dangerous threat that future highly computerised ships must face. The proposed work shows an approach capable of hijacking a state-of-the-art collision avoidance algorithm route by feeding it with rogue data. The effects of such a cyber-attack are shown via an extensive simulation campaign, testing the methodology on three different COLREG scenarios: head-on, crossing, and overtaking. The study additionally highlights the susceptibility of forthcoming navigation systems to security breaches, which still needs to be addressed in the existing literature. According to the experimental findings, attackers can attract the autonomous ship guidance toward their objective at a mean distance of $ 133\,{\rm m} $ 133 m . Finally, suggestions on how to harden these systems against this family of attacks are provided in the conclusion. [ABSTRACT FROM AUTHOR]

To increase the hit efficiency and lethality of a flight vehicle, it is necessary to consider the vehicle's guidance law concerning both impact time and angle constraints. In this study, a novel and straightforward impact time and angle control guidance law that is independent of time-to-go and small angle approximations is proposed with two stages using a data-driven method and proportional navigation guidance. First, a proportional navigation guidance-based impact angle control guidance law is designed for the second stage. Second, from various initial conditions on the impact angle control guidance simulation with various initial conditions, the input and output datasets are obtained to build a mapping network. Using the neural network technique, a mapping network model that can output the ideal flight path angle in flight is constructed for impact time control in the first stage. The proposed impact time and angle control guidance law reduces to the proportional navigation guidance law when the flight path angle error converges to zero. The simulation results show that the proposed guidance law delivers excellent performance under various conditions (including cooperative attack) and features better acceleration performance and less control energy than does the comparative impact time and angle control guidance law. The results of this research are expected to supplement those exploring various paradigms to solve the impact time and angle control guidance problem, as concluded in the current literature. [ABSTRACT FROM AUTHOR]

This Review discusses the main results obtained in training end-to-end neural architectures for guidance and control of interplanetary transfers, planetary landings, and close-proximity operations, highlighting the successful learning of optimality principles by the underlying neural models. Spacecraft and drones aimed at exploring our solar system are designed to operate in conditions where the smart use of onboard resources is vital to the success or failure of the mission. Sensorimotor actions are thus often derived from high-level, quantifiable, optimality principles assigned to each task, using consolidated tools in optimal control theory. The planned actions are derived on the ground and transferred on board, where controllers have the task of tracking the uploaded guidance profile. Here, we review recent trends based on the use of end-to-end networks, called guidance and control networks (G&CNets), which allow spacecraft to depart from such an architecture and to embrace the onboard computation of optimal actions. In this way, the sensor information is transformed in real time into optimal plans, thus increasing mission autonomy and robustness. We then analyze drone racing as an ideal gym environment to test these architectures on real robotic platforms and thus increase confidence in their use in future space exploration missions. Drone racing not only shares with spacecraft missions both limited onboard computational capabilities and similar control structures induced from the optimality principle sought but also entails different levels of uncertainties and unmodeled effects and a very different dynamical timescale. [ABSTRACT FROM AUTHOR]

With the advancement of technology in both combat and defensive situations, the requirement of the use of autonomous vehicles which carry payload is increasing. For the different types of targets, missiles are used. The missile guidance system calculates the miss distance and the trajectory dynamics through automated system. Using image processing, multiple types of target can be identifies. The use of image processing in the guiding system to differentiate between the objects may provide the contemporary error correction in the flight path. In this paper, multiple approaches are used for target identification, tracking and control of trajectory dynamics. The approach identifies two targets, a massive missile truck and an airplane. The algorithm successfully identifies target despite colour variances and almost equivalent structural arrangements. Further trajectory estimation of target is done through constant velocity and constant turn models. When utilising motion estimates and detection, real-world success depends on the ability to recognise visual targets. The Type 1 system's main objective is flight path management using the yaw, pitch, and roll axes. A common atmospheric model and a set of equations are used by the missile autopilot system to describe the aircraft. In MATLAB Simulink, a simulated missile attack travelling at 328 m/s is modelled and simulated. In the model, the missile and its intended target came together at 3.5 s. [ABSTRACT FROM AUTHOR]

Minor bodies exhibit considerable variability in shape and surface morphology, posing challenges for spacecraft operations, which are further compounded by highly non-linear dynamics and limited communication windows with Earth. Additionally, uncertainties persist in the shape and surface morphology of minor bodies due to errors in ground-based estimation techniques. The growing need for autonomy underscores the importance of robust image processing and visual-based navigation methods. To address this demand, it is essential to conduct tests on a variety of body shapes and with different surface morphological features. This work introduces the procedural Minor bOdy geNErator Tool (MONET), implemented using an open-source 3D computer graphics software. The starting point of MONET is the three-dimensional mesh of a generic minor body, which is procedurally modified by introducing craters, boulders, and surface roughness, resulting in a photorealistic model. MONET offers the flexibility to generate a diverse range of shapes and surface morphological features, aiding in the recreation of various minor bodies. Users can fine-tune relevant parameters to create the desired conditions based on the specific application requirements. The tool offers the capability to generate two default families of models: rubble-pile, characterized by numerous different-sized boulders, and comet-like, reflecting the typical morphology of comets. MONET serves as a valuable resource for researchers and engineers involved in minor body exploration missions and related projects, providing insights into the adaptability and effectiveness of guidance and navigation techniques across a wide range of morphological scenarios. [ABSTRACT FROM AUTHOR]

In recent years, space research has shifted heavily its focus towards enhanced autonomy on-board spacecrafts for on-orbit servicing activities (OOS). OOS and proximity operations include a variety of activities: the focal point of this work is the autonomous guidance of a chaser spacecraft for the shape reconstruction of an artificial uncooperative object. Adaptive guidance depends on the ability of the system to build a map of the uncertain environment, figuring out its location inside of it and accordingly determining the control law. Thus, autonomous navigation is framed as an active Simultaneous Localization and Mapping (SLAM) problem and modeled as a Partially Observable Markov Decision Process (POMDP). A state-of-the-art Deep Reinforcement Learning (DRL) method, Proximal Policy Optimization (PPO), is investigated to develop an agent capable of cleverly planning the shape reconstruction of the target. Starting from previous research on the topic, this work develops further proposing a continuous action space, such that the agent is no more forced to choose between a predefined set of possible discrete actions, fixed both in magnitude and direction. In this way any combination of the three-dimensional thrust vector components is available. The chaser spacecraft is a small satellite mounting an electric propulsion engine defining the action space range, in linearized eccentric relative motion with the selected uncooperative object. Through a rendered triangular mesh, the agent capabilities of geometry reconstruction and mapping are evaluated, considering the number of quality pictures made for each face. Extensive training tests are performed with random initial conditions to verify the generalizing capability of the DRL agent. The results are then validated in a comprehensive testing campaign, whose primary focus is the introduction of noisy measurements coming from navigation, affecting pose estimation. The sensitivity of the proposed method to this condition is analyzed and the efficiency of a retraining procedure is examined. The applicability of DRL methods and neural networks to support autonomous guidance in a close proximity scenario is corroborated and the technique employed is vastly tested and verified. [ABSTRACT FROM AUTHOR]

In order to achieve the precise attack of multiple underwater intelligent vehicles (UIVs) on the same target ship at a fixed impact time, and to improve the penetration capability of the UIVs themselves, this study investigated the guidance law for the time-cooperative guidance of UIVs with maneuvering evasion. The evasive maneuver of the UIV increases the line-of-sight angle between the UIV and the target, which decreases the guidance precision of the UIV. A segmented control strategy is proposed to solve the problem of decreasing guidance precision caused by evading maneuvers, which is also the main contribution of this paper. This control strategy is dividing the guidance trajectory into two segments. The first segment allows for intelligent underwater vehicles to make evasion maneuvers and penetrate the defense, while the second segment controls the terminal time and achieves precision strike. Different desired target-vehicle distances are designed for each segment, unifying the impact time control issue and evasion maneuver problem into the pursuit of desired target-vehicle distances. Finally, based on feedback linearization control theory, a time-cooperative guidance law with evasion maneuver capability is proposed. Simulation results validate the effectiveness of the proposed method in attacking-moving targets. [ABSTRACT FROM AUTHOR]

This paper identifies and classifies the essential constraints that must be addressed to allow U-space traffic autonomous guidance. Based on an extensive analysis of the state of the art in robotic guidance, physics of flight, flight safety, communication and navigation, uncrewed aircraft missions, artificial intelligence (AI), social expectations in Europe on drones, etc., we analyzed the existing constraints and the information needs that are of essential importance to address the identified constraints. We compared the identified information needs with the last edition of the U-space Concept of Operations and identified critical gaps between the needs and proposed services. A high-level methodology to identify, measure, and close the gaps is proposed. [ABSTRACT FROM AUTHOR]

Introduction: As science and technology develop, automobiles are moving toward intelligence and electrification and need better braking systems. Methods: To improve the braking system’s response speed and braking effect, a longitudinal dynamics control system for automobiles based on the electronic mechanical braking system was proposed, and the electronic mechanical braking system was improved through automatic disturbance rejection control. Results: The experimental results show that the time required for achieving the target clamping force in the electronic mechanical braking system using selfdisturbance rejection control and proportional integral differential control is only 0.01 s, but there is an issue of excessive control in the proportional integral differential system between 0.12 s and 0.2 s, while the self-disturbance rejection controller does not have this problem. Meanwhile, regardless of the interference applied, the electronic mechanical braking system with automatic disturbance rejection control can ensure that the clamping force does not fluctuate. In the joint simulation experiment, the expected acceleration and actual acceleration can remain consistent, and if the expected braking force is 9000 N, then the actual braking force of the electronic mechanical brake (EMB) is also 9000 N. Discussion: The above results indicate that the vehicle longitudinal dynamics control system using the electronic mechanical braking system not only responds fast but also has a good braking effect, avoiding the problem of excessive control and improving the driving experience. [ABSTRACT FROM AUTHOR]

Mixed reality navigation (MRN) technology is emerging as an increasingly significant and interesting topic in neurosurgery. MRN enables neurosurgeons to "see through" the head with an interactive, hybrid visualization environment that merges virtual- and physical-world elements. Offering immersive, intuitive, and reliable guidance for preoperative and intraoperative intervention of intracranial lesions, MRN showcases its potential as an economically efficient and user-friendly alternative to standard neuronavigation systems. However, the clinical research and development of MRN systems present challenges: recruiting a sufficient number of patients within a limited timeframe is difficult, and acquiring low-cost, commercially available, medically significant head phantoms is equally challenging. To accelerate the development of novel MRN systems and surmount these obstacles, the study presents a dataset designed for MRN system development and testing in neurosurgery. It includes CT and MRI data from 19 patients with intracranial lesions and derived 3D models of anatomical structures and validation references. The models are available in Wavefront object (OBJ) and Stereolithography (STL) formats, supporting the creation and assessment of neurosurgical MRN applications. Subject terms: Mixed reality, Navigation, Neurosurgery, Intracranial lesion, Computed tomography, Magnetic resonance imaging [ABSTRACT FROM AUTHOR]

Online Virtual Museums (OVM) serve as vital conduits for the global propagation of cultural heritage but grapple with the challenge of user disorientation due to the absence of physical references. Leveraging the successful paradigm of game-based virtual navigation, this study investigates the potential integration of game mini-map navigation design elements into OVM to enhance spatial cognition. Through empirical investigation, a conceptual model was developed to probe the role of core mini-map design elements (interactivity, visual guidance, and information content) in augmenting spatial cognition. Results indicate that optimizing these elements significantly enhances user immersion and presence, thereby improving spatial cognition. Specifically, information content and visual guidance exerted stronger effects on immersion and presence, respectively. This research contributes a novel perspective on incorporating game design strategies into non-game virtual experiences, offering practical guidance for enhancing navigation in OVM and similar virtual environments. This bridges the gap between virtual museum navigation and game design, propelling the evolution of more dynamic, interactive, and user-centric virtual environments, thus fostering the preservation and dissemination of digital cultural heritage. [ABSTRACT FROM AUTHOR]

Although the probability of a rollover accident is lower than that of other forms of collision, rollover is a serious accident that can break the symmetry of the vehicle and cause serious loss of life and property. There are many factors affecting rollovers, such as the environment, the vehicle, and the driving control. A coach comprises a complex dynamic system; as such, the accuracy and rationality of the used mathematical model are decisive in the study of coach rollover warning and control. By analogy with the modeling method of an automobile collision accident, the general process of a coach rollover accident is analyzed in this study in combination with the contact form and freedom of motion characteristic of the coach body and external environment. According to the principle of conservation of energy, the mathematical models of critical rollover impact force in a collision between vehicles and obstacles and in a collision between two vehicles are established, allowing for analysis of the relationships between the critical tripped rollover impact forces required for a 90° rollover and the continuous action time and collision point height. During the collision between the vehicle and the obstacle, the occurrence of a vehicle rollover is related not only to the impact force in the collision process but also to the collision duration time. Even if the impact force is relatively small, the collision lasts long enough that a second collision may occur until the vehicle rolls over. In the process of a two-vehicle collision, the critical rollover impact force is not only related to the vehicle mass but also to the vehicle wheelbase and the height of the collision point. Based on the law of conservation of momentum, the mathematic models of 90-degree rollover and 180-degree rollover are established, and the critical rollover velocities are calculated. The purpose of this study is to provide reference and guidance for the research methods of vehicle rollover stability and anti-rollover control in the intelligent vehicle era. [ABSTRACT FROM AUTHOR]

In this paper, a fast online guidance law generation method is proposed to resolve the flight time control guidance design problem for time adjustable flight consensus via an analytical polynomial shaping approach. The obtained guidance command is explicit such that fast online trajectory generation is applicable without blind parameters to be designed or tuned. Specifically, the polynomial shaping approach is employed to construct a reference relative range profile by a cubic polynomial in terms of a look angle-based auxiliary. The reference profile is solved by initial and terminal flight conditions. Meanwhile, the field-of-view limit is also achieved by explicitly deriving the conditions to be met for the reference profile's coefficients. Notably, the proposed technique does not rely on the error-prone time-to-go approximation. The trajectory generation command is derived using the guidance model under the expected relative range profile, and is finally presented as a proportional navigation guidance-like law which has simple structure and guaranteed effectiveness. Extensive numerical simulations under various flight consensus scenarios, comparison study, as well as Monte Carlo test under measurement errors and uncertainties are conducted to validate the proposed method. [ABSTRACT FROM AUTHOR]

This paper investigates the impact-angle-control guidance problem for varying-speed flight vehicles with constrained acceleration. A learning-based bias proportional navigation guidance (L-BPN) law is proposed to achieve impact-angle-constrained impact by constructing a deep neural network (DNN) for nonlinear mapping between the impact angle and the bias term. During the process of dataset establishment, the impact of state variables is evaluated by sensitivity analysis to minimize the quantity of training data. This approach also effectively accelerates sample generation and improves the training efficiency. The simulation results verify the effectiveness of the proposed L-BPN law and demonstrate its advantages over the existing algorithms. [ABSTRACT FROM AUTHOR]

This paper proposes a dynamic encircling cooperative guidance (DECG) law to enable multiple interceptors to cooperatively intercept a superior target, considering low velocity, limited overload, impact angle and simultaneous arrival constraints. First, the feasible escaping area of the target is analyzed and a dynamic encircling strategy for the target is established. This strategy efficiently provides virtual escaping points, allowing interceptors to dynamically encircle the target without excessive energy consumption, ultimately leading to a successful interception. Second, to enhance the physical feasibility of the kinematic equations governing the interaction between interceptors and target at the virtual escaping points, the independent variable is substituted and the kinematic equations are remodeled. Convex optimization is employed to address the multi-constraint optimal guidance problem for each interceptor, thereby facilitating simultaneous interception. Compared with the existing guidance laws, DECG has a more practical and feasible cooperative strategy, is able to handle more constraints including the interceptor's own constraints and cooperative constraints, and does not rely on the precise calculation of explicit remaining flight time in the guidance law implementation. Lastly, the effectiveness, superiority and robustness of the DECG law are evaluated through a series of numerical simulations, and its performance is compared with that of the cooperative proportional navigation guidance law (CPNG). [ABSTRACT FROM AUTHOR]

Guidance commands of flight vehicles can be regarded as a series of data sets having fixed time intervals; thus, guidance design constitutes a typical sequential decision problem and satisfies the basic conditions for using the deep reinforcement learning (DRL) technique. In this paper, we consider the scenario where the escape flight vehicle (EFV) generates guidance commands based on the DRL technique, while the pursuit flight vehicles (PFVs) derive their guidance commands employing the proportional navigation method. For every PFV, the evasion distance is described as the minimum distance between the EFV and the PFV during the escape-and-pursuit process. For the EFV, the objective of the guidance design entails progressively maximizing the residual velocity, which is described as the EFV's velocity when the last evasion distance is attained, subject to the constraint imposed by the given evasion distance threshold. In the outlined problem, three dimensionalities of uncertainty emerge: (1) the number of PFVs requiring evasion at each time instant; (2) the precise time instant at which each of the evasion distances can be attained; (3) whether each attained evasion distance exceeds the given threshold or not. To solve the challenging problem, we propose an innovative solution that integrates the recurrent neural network (RNN) with the proximal policy optimization (PPO) algorithm, engineered to generate the guidance commands of the EFV. Initially, the model, trained by the RNN-based PPO algorithm, demonstrates effectiveness in evading a single PFV. Subsequently, the aforementioned model is deployed to evade additional PFVs, thereby systematically augmenting the model's capabilities. Comprehensive simulation outcomes substantiate that the guidance design method based on the proposed RNN-based PPO algorithm is highly effective. [ABSTRACT FROM AUTHOR]

Path following presents a pivotal challenge within the realm of small fixed-wing unmanned aerial vehicles. Firstly, a Lyapunovstable path guidance law was formulated to follow specific planar curved paths. To ensure differentiability of the guidance law, a modified, smooth saturation function was derived. Secondly, an analysis was conducted to ascertain the interrelationship between control parameters and input constraints, thereby identifying the relevant parameter domains. Thirdly, the nonlinear model predictive control technique was harnessed to optimize both guidance law parameters, enhancing the unmanned aerial vehicle's capacity to achieve optimal performance in both straight-line and circular path following, hereafter referred to as PFC_NMPC. By leveraging Lyapunov stability arguments for switched systems, the stability of the corresponding nonlinear switched system was guaranteed. In this study, square and circular paths were generated to assess the path-following control of a simulated fixed-wing unmanned aerial vehicle. The performance of various guidance laws, including those with fixed parameters (PFC), those with parameters tuned using fuzzy logic (PFC_FL), PFC_NMPC, vector field, and pure pursuit with line-of-sight, was compared. Notably, the proposed PFC_NMPC method exhibited the ability to expedite the unmanned aerial vehicle's convergence to the desired path while maximizing the effective flight path length. [ABSTRACT FROM AUTHOR]

To explore the spatial distribution characteristics of the blasting fragmentation(BF) of the open-pit bench, the UAV was used to shoot the image of the blasted heap, and the image recognition algorithm was combined to extract the block distribution features. Finally, the BF spatial distribution characteristics and influencing factors were analyzed by numerical analysis. The results show that the optimized Canny-Ostu algorithm can accurately identify the BF and can be used to evaluate the blasting quality quickly. The characteristic parameters of BF conform to the lognormal distribution. The average area of the top BF is three times that of the bottom, while the maximum diameter and length are 1. 5 times that of the bottom block. The filling ratio of the blast hole is directly proportional to the large block area, while the delay time, explosive unit consumption, and blast hole spacing are inversely proportional to the large block area. The research results can provide a reference for optimizing mine bench blasting parameters. [ABSTRACT FROM AUTHOR]

The powered aeroassisted orbital maneuver (AOM) is an emerging type of AOM manner, which can fulfill various complicated orbital transfer missions more flexibly and efficiently by virtue of aerodynamic forces and synergetic thrust. In this paper, an adaptive control strategy is presented for the reference trajectory tracking guidance of powered AOM under system uncertainties and input constraints. The presented controller is designed with an attack angle control law and a bank angle control law. The constrained control inputs are smoothly described through a hyperbolic tangent-type function. Then, the attack angle and bank angle control laws are separately developed by utilizing the first-order and second-order backstepping control methods. Besides, the parametric adaptive mechanism is incorporated to identify the squares of the upper bounds of the total uncertain items. Benefiting from this design, the presented controller can not only resist system uncertainties, but also accommodate input constraints. The stability evaluation shows that the radial distance and velocity tracking errors under the presented controller can eventually stabilize to the bounded minor fields around zero. Lastly, the derived results are verified through comparative studies with an existing controller and Monte Carlo simulations under different conditions. [ABSTRACT FROM AUTHOR]

Background: Research study participants can stop taking part early, in various circumstances. Sometimes this experience can be stressful. Providing participants with the information they want or need when they stop could improve participants' experiences, and may benefit individual studies' objectives and research in general. A group of public contributors and researchers at the Clinical Trials Research Unit, University of Leeds, aimed to develop a communication template and researcher guidance. This would address how to provide information sensitively around the time when participants stop or significantly reduce their level of participation. Methods: The project lead used scoping review methods to identify relevant prior evidence and derive a list of potential information topics to communicate to participants who stop taking part. The topic list was reviewed by research professionals and public contributors before finalisation. Further public contributors were identified from a range of networks. The contributors formed a 'development group', to work on the detail of the planned resources, and a larger 'review group' to review the draft output before finalisation. The involvement was planned so that the development group could shape the direction and pace of the work. Results: The literature review identified 413 relevant reports, resulting in 94 information topics. The review suggested that this issue has not been well explored previously. Some evidence suggested early-stopping participants are sometimes excluded from important communications (such as study results) without clear justification. The development group agreed early to focus on guidance with reusable examples rather than a template. We took time to explore different perspectives and made decisions by informal consensus. Review group feedback was broadly positive but highlighted the need to improve resource navigability, leading to its final online form. Conclusions: We co-developed a resource to provide support to research participants who stop taking part. A strength of this work is that several of the public contributors have direct lived experience of stopping research participation. We encourage others to review the resource and consider how they support these participants in their studies. Our work highlights the value of researchers and participants working together, including on complex and ethically challenging topics. Plain English summary: Participants in research sometimes stop taking part early. This can sometimes be stressful or difficult for them. Giving them information they want or need around that time could help them and the research. Public contributors and researchers worked together on this project. We wanted to help researchers get information to research participants who stop taking part. Some of the public contributors had experiences of stopping research participation early. The project lead first made a rough plan for the project, with public contributors' help. He left the plan open so the public contributors could help shape the project. The project lead searched for relevant information in published literature. This search showed there has not been much work before on how to help participants who stop taking part. He used the search results to make a list of topics that could be useful to give participants who stop taking part. He asked public contributors and researchers to review the list. Public contributors then joined one of two groups. A smaller group worked on the detail of the planned guidance. A larger group reviewed the draft guidance. The smaller group worked together to make the final guidance in six online meetings. The guidance includes example wording for others to use in their own participant communications. The reviewer group generally liked the guidance but had comments on making it easier to use. The final resource is available online and a link is in the references to this article. [ABSTRACT FROM AUTHOR]

Railway overhead contact lines are very low-damped structures with a high modal density in the low-frequency region. This has a significant impact on the interaction with the pantograph, especially in the high-speed case and in multiple pantographs operations. This paper studies the optimal spatial damping distribution in overhead contact lines obtained by introducing localised damping connections, resulting in a non-proportional damping distribution. To this end, the simulation software Cateway is presented and adopted in conjunction with evolutionary multi-objective optimisers to seek for the most efficient spatial damping distribution. The study is conducted on a high-speed reference model considering two different train speeds. The final goal of this optimisation is to obtain useful hints about the most and least sensitive regions to damping modifications. A dedicated study on the locus of the poles of the system is also proposed to corroborate the findings of the analysis. Results show that significant improvements on the current collection quality can be achieved by carefully designing the spatial damping distribution, especially for the rear (trailing) pantograph. On the other hand, wrong design choices can lead to a degradation of the contact forces. [ABSTRACT FROM AUTHOR]

To realize the visual navigation of agricultural robots in the complex environment of orchards, this study proposed a method for fruit tree recognition and navigation based on YOLOv5. The YOLOv5s model was selected and trained to identify the trunks of the left and right rows of fruit trees; the quadratic curve was fitted to the bottom center of the fruit tree recognition box, and the identified fruit trees were divided into left and right columns by using the extreme value point of the quadratic curve to obtain the left and right rows of fruit trees; the straight-line equation of the left and right fruit tree rows was further solved, the median line of the two straight lines was taken as the expected navigation path of the robot, and the path tracing navigation experiment was carried out by using the improved LQR control algorithm. The experimental results show that under the guidance of the machine vision system and guided by the improved LQR control algorithm, the lateral error and heading error can converge quickly to the desired navigation path in the four initial states of [0 m, -0.34 rad], [0.10 m, 0.34 rad], [0.15 m, 0 rad] and [0.20 m, -0.34 rad]. When the initial speed was 0.5 m/s, the average lateral error was 0.059 m and the average heading error was 0.2787 rad for the navigation trials in the four different initial states. Its average driving was 5.3 m into the steady state, the average value of steady state lateral error was 0.0102 m, the average value of steady state heading error was 0.0253 rad, and the average relative error of the robot driving along the desired navigation path was 4.6%. The results indicate that the navigation algorithm proposed in this study has good robustness, meets the operational requirements of robot autonomous navigation in orchard environment, and improves the reliability of robot driving in orchard. [ABSTRACT FROM AUTHOR]

A novel integrated guidance and control scheme is derived for STT missile with strict constraints as desired impact angle, input saturation and partial system state in three-dimensional space. The backstepping technique and command filter are adopted for achieving input constraints, and the improved compensation signals are constructed to correct tracking errors. The integral barrier Lyapunov function is introduced to prevent the partial system states from exceeding a predefined interval. A modified extended state observer is employed to strengthen the robustness of the system further. Theoretically, the required properties of a closed-form system are proved by Lyapunov theory in detail. Numerical simulations are conducted to exhibit the performance and robustness of the IGC scheme fully. [ABSTRACT FROM AUTHOR]

To make an Autonomous Underwater Vehicle (AUV) chase a moving target ship that generates wake, wake-responsive guidance can be used. This scenario is applicable to making an underwater torpedo pursue a moving target ship until hitting the target. The objective of our research is to make an AUV pursue a target ship assisted by passive sonar sensors as well as wake sensors. To track a maneuvering target without losing the target, the AUV applies both passive sonar sensors and two wake sensors. Two wake sensors are utilized to decide the turn direction of the AUV in zig-zag maneuvers. In practice, sharp maneuvers of the target can cause the AUV to exit the target's wake abruptly. As the target ship's wake is not detected by wake sensors and the AUV needs to search for the target ship, the AUV's passive sonar measures the direction of sound generated from the target ship. Thereafter, the AUV chases the target ship until the target's wake is detected again. As far as we know, our paper is novel in addressing wake-responsive AUV guidance assisted by passive sonar sensors. The effectiveness of the proposed guidance is verified using computer simulations. [ABSTRACT FROM AUTHOR]

This paper studies the salvo attack problem for multiple unmanned aerial vehicles (UAVs) against a maneuvering target, and a guidance scheme based on distributed model predictive control (DMPC) is presented to achieve cooperative interception with constraints of terminal impact angle and no-fly zone (or obstacle) avoidance. Firstly, for guaranteeing the synchronization of UAVs in calculating their acceleration commands, the assumed predictive trajectories are introduced, whose deviation from the actual state trajectories is limited by the designed compatibility constraints. Secondly, based on the velocity-obstacle model, the obstacle avoidance constraints are presented, and for guaranteeing the convergence of impact time and impact angles, the auxiliary controller and terminal ingredients are developed, which complete the design of DMPC cooperative guidance scheme. Subsequently, the rigorous proof for the convergence of the proposed guidance scheme is provided. Based on the above design, a complete implementation process of the guidance scheme is presented, in which each UAV uses the particle swarm optimization algorithm to solve the preprocessed local optimization problem, and only the shared information among neighbors is utilized for calculation. Finally, the numerical simulations are conducted under diverse cases, which demonstrate the effectiveness of the proposed guidance scheme when solving cooperative interception problems with terminal angle and obstacle avoidance constraints. [ABSTRACT FROM AUTHOR]

This paper presents a segmented guidance method for multi-UAVs (unmanned aerial vehicles) cooperative attack with spatio-temporal constraints, and successfully implemented in the flight tests. First, the uniform distribution of UAVs around the target is completed through cooperative path planning and tracking in the mid-course phase. The path planning method for cooperative arrival is proposed based on Dubins curve, and the guidance strategy for circular formation flight enables the UAVs to accurately track the reference points which are evenly distributed on the circle. Second, the terminal guidance law in 3D space with impact time cooperation is proposed during the cooperative attack stage, which would further eliminate the accumulated deviation. Finally, simulations and field flight tests for coordinated attack are carried out, which show the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

The use of affine maneuver control to maintain the desired configuration of unmanned aerial vehicle (UAV) swarms has been widely practiced. Nevertheless, the lack of capability to interact with obstacles and navigate autonomously could potentially limit its extension. To address this problem, we present an innovative formation flight system featuring a virtual leader that seamlessly integrates global control and local control, effectively addressing the limitations of existing methods that rely on fixed configuration changes to accommodate real-world constraints. To enhance the elasticity of an algorithm for configuration change in an obstacle-laden environment, this paper introduces a second-order differentiable virtual force-based metric for planning local trajectories. The virtual field comprises several artificial potential field (APF) forces that adaptively adjust the formation compared to the existing following control. Then, a distributed and decoupled trajectory optimization framework that considers obstacle avoidance and dynamic feasibility is designed. This novel multi-agent agreement strategy can efficiently coordinate the global planning and local trajectory optimizations of the formation compared to a single method. Finally, an affine-based maneuver approach is employed to validate an optimal formation control law for ensuring closed-loop system stability. The simulation results demonstrate that the proposed scheme improves track accuracy by 32.92% compared to the traditional method, while also preserving formation and avoiding obstacles simultaneously. [ABSTRACT FROM AUTHOR]

This paper proposes an analytic approach for impact time control guidance laws against stationary targets using biased proportional navigation. The proposed guidance scheme realizes the impact time control in two different ways: the first approach directly uses the exact time-to-go error to satisfy both the impact time control and the field-of-view constraint, while the second approach adopts a look angle tracking law to indirectly control the impact time, with the reference profile of the look angle generated using the exact time-to-go solution. The stability properties of the proposed guidance laws are discussed, and numerical simulations are carried out to evaluate their performance in terms of accuracy and efficiency. [ABSTRACT FROM AUTHOR]