Search Results (72)

Ballistic missiles exhibit high velocities and rapid maneuverability after atmospheric reentry, posing substantial challenges for anti-ballistic missile (ABM) interception. This paper presents an integrated interception framework that combines an input estimation method with an improved particle swarm optimization-based guidance law (IPSOG). The input estimation approach processes noisy radar measurements to estimate target states in the presence of unknown system inputs and measurement noise. Its performance is evaluated through simulations and compared with the extended Kalman filter (EKF), demonstrating improved estimation accuracy and robustness under highly maneuvering conditions. An improved particle swarm optimization algorithm is employed to design the interceptor guidance law. Compared with conventional proportional navigation guidance (PNG), the proposed guidance method provides enhanced adaptability to target maneuvers. Numerical simulations are conducted to evaluate interception performance against maneuvering ballistic missile targets. Results show reductions in miss distance and interception time while maintaining lower average lateral acceleration and a larger effective interception region. These results indicate that the proposed framework improves both target state estimation and interceptor guidance performance for highly maneuvering ballistic missile targets. Full article

This paper investigates an optimal cooperative guidance strategy for the active defense of an early-warning aircraft (EWA) escorted by two fighters against an incoming missile. The proposed framework extends classical three-body defense models (Target–Missile–Interceptor) into a more realistic four-body engagement (Target–Missile–Interceptor 1–Interceptor 2), allowing explicit coordination among multiple defenders. By projecting the 3D engagement kinematics onto two orthogonal 2D planes—a validated simplification for typical aerial combat geometries—a tractable dynamic model is obtained. Within this model, an analytical cooperative guidance law is derived using optimal control theory and the calculus of variations, minimizing a multi-objective cost function that combines miss distance, control effort, intercept geometry, and coordination terms. Extensive Monte Carlo simulations across 23 attack directions and multiple initial ranges demonstrate that the proposed method achieves an interception success rate of 99%, with an average miss distance of below 5 m. Robustness tests further confirm stable performance under target maneuver uncertainty, sensor noise, and modeling deviations. The algorithm features closed-form control commands with low computational complexity, enabling real-time onboard implementation. Full article

Missile-borne active phased array antennas have been widely used in missile guidance for their beam agility, multifunctionality, and strong anti-interference capabilities. However, due to space constraints on the platform and difficulty in heat dissipation, the thermal power consumption of the antenna array can easily lead to excessive temperature, causing two primary issues: first, temperature-induced drift in T/R components, resulting in amplitude and phase errors in the feed current; second, temperature-dependent ripple voltage in the array’s secondary power supply, which exacerbates feed errors. Both issues degrade the electromagnetic performance of the array antenna. To mitigate these effects, this paper investigates feed errors and compensation methods in high-temperature environments. First, a synchronous Buck circuit ripple coefficient model is developed, and an electromagnetic–temperature coupling model is established, incorporating temperature-dependent feed current characteristics, and the law of electromagnetic performance changes is analyzed. On this basis, an electromagnetic performance compensation method based on a genetic algorithm is proposed to optimize the quantization compensation amount of the amplitude and phase of each element under the effect of high temperature. Full article

This work presents a method for simulating balanced gliding trajectories of high-hypersonic flight vehicles, circumventing the challenges associated with trajectory modeling for these advanced vehicles. A typical hypersonic vehicle is used as a case study to create an external shape prototype. Aerodynamic simulations are performed using atmospheric data corresponding to various altitudes throughout the hypersonic flight. This process generates aerodynamic characteristic models for the vehicle across various Mach numbers and altitude conditions. Subsequently, ballistic modeling is conducted using the simulated aerodynamic data. The ballistic curve is refined iteratively during critical flight stages, taking into account the missile’s terminal guidance towards the target. As a result, the ballistic modeling curve is made relatively precise. Simulation results demonstrate that, compared to conventional equation-based ballistic curve modeling, the proposed iteration method yields ballistic curves that more accurately reflect actual flight conditions. This enhances flight state parameters and facilitates missile simulation for targeting moving objects. Notably, the terminal guidance accuracy error decreases from 0.12° to 0.03°, establishing a robust foundation for accurate ballistic modeling of hypersonic vehicles. Full article

This paper presents a stability analysis of single-channel, slow-rolling, Semi-Automatic Command to Line of Sight (SACLOS) missiles using a comparison of the Routh–Hurwitz and the Frank–Wall stability criteria and a nonlinear analysis. Beginning with a six-degree-of-freedom (6-DOF) model in the Resal frame, a linearized model for the commanded motion is developed. This linearized model, which features complex coefficients due to the coupling of longitudinal channels in rolling missiles, is used to define the structural scheme of the commanded object and its flight quality parameters. The guidance kinematic relations, guidance device equations, and actuator relations, incorporating a switching function specific to slow-rolling, single-channel missiles, are also defined and linearized within the Resal frame to construct a comprehensive structural diagram of the SACLOS missile. From this, the characteristic polynomial with complex coefficients is derived and analyzed by comparing the Routh–Hurwitz and the Frank–Wall stability criteria. This analysis determines a stability domain for the guidance gain and establishes a minimum limit for the guidance time. The stability domain defined through the linear model is then validated using a nonlinear model in the body frame. Full article

The article discusses the problem of a preliminary analytical method for modifying the shape of a rocket’s nose. The purpose of this method is to determine the shape that minimizes aerodynamic drag, in the context of modifying a ballistic missile to incorporate guidance systems. The traditional design process relies on numerical methods such as CFD (Computational Fluid Dynamics) or machine learning techniques; however, the method presented here can serve as a first iteration to support the design. Advanced simulation tools are often expensive and difficult to access for smaller companies, while open-source software can sometimes be unreliable, difficult to use, and incompatible with professional solutions. This can pose a challenge for businesses planning to collaborate in the future with large corporations that rely on advanced engineering tools. The proposed solution, as previously mentioned, provides a starting point for the entire design process. The approach has been shown to be sufficient from the design work. The entire process was validated during test range trials, during which rockets were launched, and the flight measurement results accurately reflected the aerodynamic properties of the missiles. In the next stages of the project, numerical methods including CFD simulations are planned to verify the analytical results and enable further aerodynamic modification of the design. Full article

In recent years, UAVs have faced increasingly severe and diversified missile threats. To address the challenge that reinforcement learning-based missile evasion algorithms struggle to adapt to various unknown missile types, we introduce a risk-sensitive PPO algorithm and propose a training framework incorporating multi-head attention mechanisms and dual-population adversarial training. The multi-head attention mechanism enables the policy network to extract latent features such as missile guidance laws from state sequences, while the dual-population adversarial approach ensures policy diversity and robustness. Compared to conventional self-play methods and GRU-based evasion strategies, our method demonstrates superior training efficiency and generates evasion policies with better adaptability to different missile types. Full article

We present a novel approach to generating a cooperative guidance strategy using deep reinforcement learning to address the challenge of cooperative multi-missile strikes under uncontrollable velocity conditions. This method employs the multi-agent proximal policy optimization (MAPPO) algorithm to construct a continuous action space framework for intelligent cooperative guidance. A heuristically reshaped reward function is designed to enhance cooperative guidance among agents, enabling effective target engagement while mitigating the low learning efficiency caused by sparse reward signals in the guidance environment. Additionally, a multi-stage curriculum learning approach is introduced to smooth agent actions, effectively reducing action oscillations arising from independent sampling in reinforcement learning. Simulation results demonstrate that the proposed deep reinforcement learning-based guidance law can successfully achieve cooperative attacks across a range of randomized initial conditions. Full article

In recent decades, missile guidance and control have advanced significantly, with methods like pure pursuit (PP), command to line-of-sight (CLOS), and proportional navigation (PN) enabling accurate target interception in uncertain environments through line-of-sight (LOS) tracking. In this work, we propose a novel 3D sliding pure pursuit guidance (3DSPP) law for controlling a surface-to-air missile against a maneuvering target. The algorithm is compared with established guidance laws such as zero-effort miss distance “ZEM-PN” and “3D-PP”, with performance metrics including the miss distance $M_d$ and time of closest approach $t_{cap}$. The results demonstrate that the 3DSPP outperforms the conventional methods by achieving the lowest $M_d=$ 0.1497 m and the fastest $t_{cap}=$ 7.3853 s, ensuring more precise and rapid interception. The algorithm also exhibits superior robustness to noise and efficient energy management, making it a promising solution for real-world missile guidance systems. Full article

This study presents an advanced second-order sliding-mode guidance law with a terminal impact angle constraint, which ingeniously combines reinforcement learning algorithms with the nonsingular terminal sliding-mode control (NTSM) theory. This hybrid approach effectively mitigates the inherent chattering issue commonly associated with sliding-mode control while maintaining high levels of control system precision. We introduce a parameter to the super-twisting algorithm and subsequently improve an intelligent parameter-adaptive algorithm grounded in the Twin-Delayed Deep Deterministic Policy Gradient (TD3) framework. During the guidance phase, a pre-trained reinforcement learning model is employed to directly map the missile’s state variables to the optimal adaptive parameters, thereby significantly enhancing the guidance performance. Additionally, a generalized super-twisting extended state observer (GSTESO) is introduced for estimating and compensating the lumped uncertainty within the missile guidance system. This method obviates the necessity for prior information about the target’s maneuvers, enabling the proposed guidance law to intercept maneuvering targets with unknown acceleration. The finite-time stability of the closed-loop guidance system is confirmed using the Lyapunov stability criterion. Simulations demonstrate that our proposed guidance law not only meets a wide range of impact angle constraints but also attains higher interception accuracy and faster convergence rate and better overall performance compared to traditional NTSM and the super-twisting NTSM (ST-NTSM) guidance laws, The interception accuracy is less than 0.1 m, and the impact angle error is less than 0.01°. Full article

The authors have designed a structure for a gyro system (used for the guidance of self-guided missiles) with two gimbals and a rotor in magnetic suspension (AMBs—active magnetic bearings). The system (double-gimbal magnetic suspension gyro system for guidance—DGMSGG) orients the common axis rotor AMB (the sight line) in the direction of the target line (the guide line) by means of some control system of the gyro rotor’s rotations and translations, as well as by means of some servo systems for the gimbals’ rotation angle control. The DGMSGG provides specific signals for the missile’s autopilot, to guide it toward the target, so that the guidance line translates parallel to itself to the point of interception of the target (according to the self-guidance method by parallel approach). Based on the DGMSGG’s established mathematical model, the authors propose and design adaptive control systems for the decoupled dynamics of the gyro rotor’s translations and rotations and of the gimbals’ rotations; the concept of dynamic inversion is used, as well as linear dynamic compensators (P.D.- and P.I.D.-type), state observers, reference models, and neural networks. The theoretical results are validated through numerical simulations, using Simulink/Matlab models’ stabilization and orientation operating regimes. Full article

To address the problem of multiple missiles attacking a maneuvering target simultaneously in three-dimensional space, we propose a new predefined-time cooperative guidance law based on an event-triggered mechanism. The settling time of the system states under this guidance law is independent of the initial states, and the upper bound of the settling time can be directly set by the explicit parameters in the guidance law. Firstly, the time-to-go estimate is taken as a consistency variable, and the communication failure and time-delay that are easily encountered during the communication process are taken into account; the event-triggered mechanism is introduced into the guidance law along the line of sight (LOS) direction, and the event-triggered threshold is given. Then, a predefined-time extended state observer is used to accurately estimate disturbances. In addition, the stability of the proposed guidance laws along and perpendicular to the LOS direction is proven by the Lyapunov theory. Finally, the superiority of the proposed guidance law introducing the event-triggered mechanism in reducing energy consumption and its effectiveness in encountering communication failure and time-delay are verified through simulations. Full article

This paper introduces a novel approach for modeling and optimizing the trajectory and behavior of small solid rocket missiles. The proposed framework integrates a six-degree-of-freedom (6DoF) simulation environment experimentally tuned for accuracy, with a combination of genetic algorithms (GAs) and machine learning (ML) to enhance the performance of the missile path. In the initial phase, a GA is employed to optimize the missile’s trajectory for efficient target acquisition, defining key launch parameters such as the ramp angle and lateral maneuver force to minimize positional errors and to ensure effective target engagement. Following trajectory optimization, the derived data are used to train an ML model that predicts setup parameters, significantly reducing computational costs and time. This close integration enables real-time adjustments for acquiring moving targets, thereby improving accuracy and minimizing maneuvering costs. This study also explores the application of fluidic thrust vectoring for small rockets, providing an innovative solution to enhance maneuverability and control, especially at low speeds. The proposed framework was validated using experimental launch data from the Icarus Team. The methodology offers a robust and cost-effective solution for precision targeting and improved maneuverability in aerospace and defense contexts. Full article

This paper proposes an improved multi-agent deep deterministic policy gradient algorithm called the equal-reward and action-enhanced multi-agent deep deterministic policy gradient (EA-MADDPG) algorithm to solve the guidance problem of multiple missiles cooperating to intercept a single intruding UAV in three-dimensional space. The key innovations of EA-MADDPG include the implementation of the action filter with additional reward functions, optimal replay buffer, and equal reward setting. The additional reward functions and the action filter are set to enhance the exploration performance of the missiles during training. The optimal replay buffer and the equal reward setting are implemented to improve the utilization efficiency of exploration experiences obtained through the action filter. In order to prevent over-learning from certain experiences, a special storage mechanism is established, where experiences obtained through the action filter are stored only in the optimal replay buffer, while normal experiences are stored in both the optimal replay buffer and normal replay buffer. Meanwhile, we gradually reduce the selection probability of the action filter and the sampling ratio of the optimal replay buffer. Finally, comparative experiments show that the algorithm enhances the agents’ exploration capabilities, allowing them to learn policies more quickly and stably, which enables multiple missiles to complete the interception task more rapidly and with a higher success rate. Full article

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. Full article