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This paper investigates the three-dimensional (3-D) homing guidance problem of intercepting an evasive target with maneuverability comparable to the missile. The guidance problem is first reformulated in the relative frame to help geometrically derive the necessary condition of interception without terminal maneuverability advantage in the 3-D space. A two-stage optimal guidance law is then analytically derived with bounded acceleration to satisfy the aforementioned necessary condition. Theoretical analysis is performed to interpret the working principle and physical meaning of the proposed law. The key feature of the proposed approach lies in its fast convergence rate and low acceleration requirement. Hence, in comparison with the existing optimal approaches, the proposed law can significantly improve the operational margin and decrease the risk of command saturation in the endgame. Extensive simulations are performed to support our findings.

This paper proposes an ensemble transfer learning guidance algorithm for angular-constrained midcourse guidance to maximize the terminal velocity. The algorithm developed improves the generalization capability of the trained deep neural network to adapt to a new environment. First several deep neural guidance networks are trained for some specific working environments via supervised learning. A small-scale ensemble transfer learning network is then leveraged to fuse the knowledge of different pretrained deep neural network. This requires much less labeled data to transfer existing knowledge to a new working environment and hence greatly improves the learning efficiency, compared to the supervised learning philosophy. Extensive numerical simulations are performed to demonstrate the effectiveness of the proposed algorithm.

This paper provides a unified formulation of optimal guidance-to-collision law for a target with an arbitrary acceleration or deceleration. The collision course for general target acceleration or deceleration is first determined from the engagement geometry in conjunction with the nonlinear engagement kinematics in the proposed approach. The heading error de_ned in the collision course is then adopted as a variable to be nullified for accomplishing the intercept condition. The proposed guidance law is derived based on the heading error dynamics and the optimal error dynamics to ensure optimality and finite-time convergence. As illustrative examples, the proposed guidance command for a constant target acceleration and a target deceleration in the form of a quadratic function of speed are provided. Additionally, the time-to-go prediction method is suggested for implementing the proposed method. The characteristics of the proposed guidance command are analytically investigated to provide insight into the proposed method. The key benefits of the proposed method lie in not producing unnecessary guidance commands near a target compared to other methods and ensuring optimality in guidance command even in the nonlinear engagement kinematics. Finally, numerical simulations are performed to validate the proposed method and to show our findings.

Differential dynamic programming (DDP) is a well-recognized method for trajectory optimization due to its fast convergence characteristics. However, the original DDP requires a predefined final time and cannot handle nonlinear constraints in optimization. This prohibits the application of DDP for autonomous vehicles due to the heuristic nature of setting a final time beforehand and the existence of inherent physical limits. This paper revisits DDP by dynamically optimizing the final time via the first-order optimality condition of the value function and using augmented Lagrangian method to tackle the issue of nonlinear constraints. The resultant algorithm is termed as Flexible Final Time Constrained Differential Dynamic Programming (FFT-CDDP). Extensive numerical simulations for a three-dimensional guidance problem are used to demonstrate the working of FFT-CDDP. The results indicate that the proposed FFT-CDDP provides much higher computational efficiency and stronger robustness against the initial solution guess, compared with the off-the-shelf GPOPS algorithm.

This paper investigates the problem of impact-angle-constrained guidance law design against maneuvering target with large initial heading error. The guidance problem is first formulated in the rang...

This article proposes a novel information-theoretic joint probabilistic data association filter for tracking unknown number of targets. The proposed information-theoretic joint probabilistic data association algorithm is obtained by the minimization of a weighted reverse Kullback–Leibler divergence to approximate the posterior Gaussian mixture probability density function. Theoretical analysis of mean performance and error covariance performance with ideal detection probability is presented to provide insights of the proposed approach. Extensive empirical simulations are undertaken to validate the performance of the proposed multitarget tracking algorithm.

This paper proposes a new three-dimensional optimal guidance law for impact time control with seeker’s Field-of-View (FOV) constraint to intercept a stationary target. The proposed guidance law is devised in conjunction with the concept of biased Proportional Navigation Guidance (PNG). The guidance law developed leverages a nonlinear function to ensure the boundedness of velocity lead angle to cater to the seeker’s FOV limit. It is proven that the impact time error is nullified in a finite-time under the proposed method. Additionally, the optimality of the biased command is theoretically analyzed. Numerical simulations confirm the superiority of the proposed method and validate the analytic findings.

Functionally gradient materials (FGM) widely exist in biological structures, which offer indispensable support and potential protection. In this paper, we expand topology optimization for coated-base materials to multi-gradient structure. In the process of modeling the biological bones, we define three levels of density gradients: a spongy bone as the base in between, wrapped by a layer of compact bone, and multi-layers of periosteum side by side. By defining the properties and thickness of each layer, the base domain is derived by the gradient norm while a modified non-monotone filter function is imposed to separate periosteum and compact bone. Meanwhile, periosteum is separated into multi-gradient layers by Heaviside projection function in order to further mimic the skeletal of bone structure. The method of robust control, using geometric constraints, is applied to the design domain in both solid and void phases to avoid local singularity during the optimal process. Finally, the validity of the algorithm is illustrated by two benchmark problems with a variety of layer combinations.

Due to the complex geological processes of Qinghai-Tibet Plateau, numerous deposits, especially the large-scale ancient landslide deposits, are characteristic features of the valleys incised in southwestern China. Intense water level fluctuations since 2011 in Maoergai Reservoir, China, registered the reactivation of Xierguazi ancient landslide, and presented a significant risk to neighboring facilities. Based on detailed field survey and drilling exploration, the landslide was divided into Zone A and Zone B, and other characterizations of landslide were studied as well. To precisely measure the extent of landslide displacement during filling and drawdown stage, surface displacement monitoring system was deployed on the landslide. The monitoring analyses data reveal that reservoir fluctuation is the dominant factor influencing landslide displacement, especially during drawdown stage. Moreover, a future sliding is anticipated in Zone A, while a creep had already existed in Zone B. A reservoir regulation was then established using the lead-lag correlation between reservoir fluctuation and landslide displacement and landslide stability analysis. In the end, the follow-up deformation monitoring demonstrates that the reservoir regulation controlled the landslide effectively. Landslide control by reservoir regulation in Maoergai can serve as a case study for other settlements involved in similar construction activities.

This paper addresses the problem of energy-optimal waypoint-following guidance for an Unmanned Aerial Vehicle with the consideration of a general autopilot dynamics model. The proposed guidance law is derived as a solution of a linear quadratic optimal control problem in conjunction with a linearized kinematics model. The algorithm developed integrates path planning and following into a single step and is able to be applied to a general waypoint-following mission. Theoretical analysis reveals that previously suggested optimal point-to-point guidance laws are special cases of the proposed approach. Nonlinear numerical simulations clearly demonstrate the effectiveness of the proposed formulations.

This paper aims to reveal the hidden physical meaning or the working principle of the three-loop autopilot. First, the minimal control structure that ensures the desired dynamic characteristics is analyzed. The results show that the three-loop autopilot has a redundant feedback loop from the minimal control structure standpoint. Based on this observation, its physical meaning is interpreted by utilizing the closed-loop tracking error dynamics in the presence of aerodynamic uncertainties. It turns out that the three-loop autopilot has the minimal control structure with an additional command which is based on the instantaneous direct model reference adaptive control. A clear mechanism of how the aerodynamic uncertainties are compensated is provided in the three-loop autopilot. Finally, numerical simulations are performed to validate our findings. The analysis results in this paper show the beauty of the three-loop autopilot: it can be considered as the most concise form to achieve desired dynamic characteristics and counteract model uncertainties. The potential importance of the results obtained is that they allow us to properly design the three-loop autopilot by reflecting its physical meaning and have potential directions to improve the performance of the three-loop autopilot as well as the adaptive control.

This paper investigates the problem of salvo attack guidance of multiple missiles and suggests a virtual leader-follower-based distributed cooperative guidance law to address this problem. The proposed guidance law is composed of two different parts: a baseline guidance law and an impact-time error feedback term. For scenarios with only impact-time constraint, the baseline guidance law is chosen as the classical pure proportional navigation for target capture. When considering both impact angle and impact time constraints, the well-known time-to-go weighted optimal guidance is leveraged as the baseline guidance law. Theoretical analysis reveals that the impact-time discrepancy among all missiles converges to zero at the time of impact. Finally, numerical analysis is conducted to demonstrate the effectiveness of the proposed algorithm.

This paper investigates the problem of distributed multitarget tracking (MTT) over a large-scale sensor network, consisting of low-cost sensors. Each local sensor runs a joint probabilistic data association filter to obtain local estimates and communicates with its neighbors for information fusion. The conventional fusion strategies, i.e., consensus on measurement (CM) and consensus on information (CI), are extended to MTT scenarios. This means that data association uncertainty and sensor fusion problems are solved simultaneously. Motivated by the complementary characteristics of these two different fusion approaches, a novel distributed MTT algorithm using a hybrid fusion strategy, e.g., a mix of CM and CI, is proposed. A distributed counting algorithm is incorporated into the tracker to provide the knowledge of the total number of sensor nodes. The new algorithm developed shows advantages in preserving boundedness of local estimates, guaranteeing global convergence to the optimal centralized version and being implemented without requiring no global information, compared with other fusion approaches. Simulations clearly demonstrate the characteristics and tracking performance of the proposed algorithm.

A novel approach to address the problem of integrated guidance and control(IGC) for a missile is studied in this paper. By taking target maneuver, aerodynamic uncertainty and fin servo dynamic uncertainty as external disturbances in the adaptive backstepping design procedure, the proposed controller requires no information on target maneuver and provides robustness against these uncertainties. Furthermore, the derivatives of the virtual control laws in the backstepping differentiation process are estimated by a smooth second-order sliding mode differentiator, this simplifies the calculation and avoids the explosion of terms phenomenon in the conventional backstepping method. The closed-loop stability of the overall system is supported by the Lyapunov stability theory. Numerical simulations of an air-to-air interception scenario are presented in the simulation part to verify the superior performance and the robustness of proposed IGC law.

This paper aims to examine the potential of using the emerging deep reinforcement learning techniques in missile guidance applications. To this end, a Markovian decision process that enables the application of reinforcement learning theory to solve the guidance problem is formulated. A heuristic way is used to shape a proper reward function that has tradeoff between guidance accuracy, energy consumption, and interception time. The state-of-the-art deep deterministic policy gradient algorithm is used to learn an action policy that maps the observed engagements states to a guidance command. Extensive empirical numerical simulations are performed to validate the proposed computational guidance algorithm.

This Correspondence proposes a new guidance law based on integral sliding mode control (ISMC) technique for maneuvering target interception with impact angle constraint. A time-varying function weighted line-of-sight (LOS) error dynamics, representing the nominal guidance performance, is introduced first. The proposed guidance law is derived by utilizing ISMC to follow the desired error dynamics. The convergence of the guidance law developed is supported by Lyapunov stability. Simulations with extensive comparisons explicitly demonstrate the effectiveness of the proposed approach.

This paper addresses the problem of minimum-effortwaypoint-following guidance with/without arrival angle constraints of an Unmanned Aerial Vehicle. By utilizing a linearized kinematics model, the proposed guidance laws are derived as the solutions of a linear quadratic optimal control problem with an arbitrary number of terminal boundary constraints. Theoretical analysis reveals that both optimal proportional navigation guidance and trajectory shaping guidance are special cases of the proposed guidance laws. The key feature of the proposed algorithms lies in their generic property. For this reason, the guidance laws developed can be applied to general waypoint-following missions with an arbitrary number of waypoints and an arbitrary number of arrival angle constraints. Nonlinear numerical simulations clearly demonstrate the effectiveness of the proposed formulations.

This paper considers the problem of twodimensional (2D) constrained trajectory optimisation of a pointmass aerial robot for constant-manoeuvring target localisation using bearing-only measurement. A performance metric that can be utilised in trajectory optimisation to maximise target observability is proposed first based on geometric conditions. One-step optimal manoeuvre that maximises the observability criterion is then derived analytically for moving targets. The heading angle constraint is also incorporated in the proposed optimal manoeuvre derivation to support practical application. Numerical simulations with some comparisons are presented to validate the analytical findings.

Introduction: The primary objective of missile guidance laws is to drive the missile to intercept a specific target with zero miss distance. Proportional navigation guidance (PNG) has been proved to be an efficient and simple guidance algorithm for missile systems, thus showing wide applications in the past few decades [1]. The optimality of PNG was analyzed in [2] and its extension to three-dimensional (3D) scenario can be found at [3]. In the context of modern warfare, many high-value battleships, like destroyers and aircraft carriers, are equipped with powerful self-defense systems against anti-ship missiles [4]. In order to penetrate these formidable defensive systems, the concept of salvo attack or simultaneous attack was introduced: many missiles are required to hit a battleship simultaneously, albeit their di.erent initial locations. One typical solution of simultaneous attack is impact time control guidance. Generally, impact time control can be classified into two categories: (1) specify the desired impact time and control each missile to satisfy the desired impact time constraint individually; and (2) synchronize the impact time either in a distributed or decentralized fashion through a communication network among all interceptors.

This paper addresses the problem of maneuver recognition and behavior anomaly detection for generic targets by means of pattern matching techniques. The problem analysis is performed making specific reference to moving vehicles in a multi-lane road scenario, but the proposed technique can be easily extended to significantly different monitoring contexts. The potential extensions include, but are not limited to, public surveillance in train station or airport, road incidents and relative precursors detection, and vehicle trajectories monitoring. The overall proposed solution consists of a trajectory analysis tool and a string-matching method. This allows the integration of two different approaches, to detect both a priori defined patterns of interest and generic maneuver/behavior standing out from those regularly exhibited. The proposed string matching algorithm is newly developed in this paper, based on Regular Expressions. For generating reference patterns, a technique for the automatic definition of a dictionary of regular expressions matching the commonly observed target maneuvers is developed. The advantages of the proposed approach are extensively analyzed and tested by means of numerical simulations and experiments.

In recent years, the development of UAV (Unmanned Aerial Vehicle) is rapid, but the development of structural design is slow, and the rack designed according to the experience of engineers still has great redundancy. With the rapid development of topology optimization and additive manufacturing, topology optimization design of integrated rack based on additive manufacturing is carried out. In the design process, manufacturing constraints are added and a variety of typical conditions to obtain the final optimization structure are considered. The influence of human empirical factors on the fuselage structure design is reduced scientifically and effectively by using this method. And the lightweight, topological and integrated design of the quadrotor frame is realized.