Multisensor Hybrid Dynamic Alliance Formation Problem Using Sensitive Particle-Based Dynamic Discrete PSO

In recent years, with the wide application and popularization of artificial intelligence algorithm in the field of multisensor information processing, it has been a research hotspot to solve the problem of sensor alliance formation in the battlefield environment by using multisensor cross-cueing technology. Based on the establishment of the multisensor hybrid dynamic alliance model and objective function, a multisensor cross-cueing algorithm based on dynamic discrete particle swarm optimization (DDPSO) with sensitive particles is proposed and a mechanism of “predict re-predict” is proposed in the process of sensor handover. Simulations have verified the good convergence effect and small detection error of multisensor cross-cueing technology in solving alliance formation problems. Meanwhile, compared with “measurement and then update” and “predict and update” mechanisms, the proposed mechanism is more suitable to the changing combat environment. At the same time, to some extent, it also shows that the artificial intelligence algorithm is more suitable for multisensor information processing.

Military Safety and Surveillance Robot with Two-Way Communication

This paper focuses on developing an Unmanned Ground Vehicle (UGV) wireless robot. It can sense the different parameters of the surroundings; transmit the data through a wireless medium and display data in LCD as well as on a Remote PC. It controls the direction of the robot from a remote location using wireless communication and thereby performing military surveillance and analysing the battlefield environment and challenges that the soldiers may potentially face. By using a Wi-Fi camera and many sensors the robot can help the soldiers in the war fields to examine various environmental conditions and challenges. The arduino and NRF (Nordic Radio Frequency) technologies are used to achieve the above tasks. The different sensors and the robotic arm are connected to the Arduino Uno which in turn is connected to the Nordic Radio Frequency module. Data transmission and receiving are done through Nordic Radio Frequency communication technology. The proposed model eliminates the limitations of the existing models and thus provides better assistance to the soldiers and enables them to handle their missions better.

A multi-objective sparse evolutionary framework for large-scale weapon target assignment based on a reward strategy

The asset-based weapon target assignment (ABWTA) problem is one of the important branches of the weapon target assignment (WTA) problem. Due to the current large-scale battlefield environment, the ABWTA problem is a multi-objective optimization problem (MOP) with strong constraints, large-scale and sparse properties. The novel model of the ABWTA problem with the operation error parameter is established. An evolutionary algorithm for large-scale sparse problems (SparseEA) is introduced as the main framework for solving large-scale sparse ABWTA problem. The proposed framework (SparseEA-ABWTA) mainly addresses the issue that problem-specific initialization method and genetic operators with a reward strategy can generate solutions efficiently considering the sparsity of variables and an improved non-dominated solution selection method is presented to handle the constraints. Under the premise of constructing large-scale cases by the specific case generator, two numerical experiments on four outstanding multi-objective evolutionary algorithms (MOEAs) show Runtime of SparseEA-ABWTA is faster nearly 50% than others under the same convergence and the gap between MOEAs improved by the mechanism of SparseEA-ABWTA and SparseEA-ABWTA is reduced to nearly 20% in the convergence and distribution.

A Comparative Study of Swarm Intelligence Algorithms for UCAV Path-Planning Problems

Path-planning for uninhabited combat air vehicles (UCAV) is a typically complicated global optimization problem. It seeks a superior flight path in a complex battlefield environment, taking into various constraints. Many swarm intelligence (SI) algorithms have recently gained remarkable attention due to their capability to address complex optimization problems. However, different SI algorithms present various performances for UCAV path-planning since each algorithm has its own strengths and weaknesses. Therefore, this study provides an overview of different SI algorithms for UCAV path-planning research. In the experiment, twelve algorithms that published in major journals and conference proceedings are surveyed and then applied to UCAV path-planning. Moreover, to demonstrate the performance of different algorithms in further, we design different scales of problem cases for those comparative algorithms. The experimental results show that UCAV can find the safe path to avoid the threats efficiently based on most SI algorithms. In particular, the Spider Monkey Optimization is more effective and robust than other algorithms in handling the UCAV path-planning problem. The analysis from different perspectives contributes to highlight trends and open issues in the field of UCAVs.

Dispersed Computing for Tactical Edge in Future Wars: Vision, Architecture, and Challenges

In the future, the tactical edge is far away from the command center, the resources of communication and computing are limited, and the battlefield situation is changing rapidly, which leads to the weak connection and fast changes of network topology in a harsh and complex battlefield environment. Thus, to meet the needs of communication and computing to build a new generation of computing architecture for real-time sharing and service collaboration of tactical edge resources to win the future war, the dispersed computing (DCOMP) seeks a new solution to satisfy the requirements of fast and efficient sensing, transmission, integrating, scheduling, and processing of various information in the tactical edge. Through the research of a traditional computing paradigm of mobile cloud computing (MCC), fog computing (FC), mobile edge computing (MEC), mobile ad hoc network (MANET), etc., it can be found that these computations have difficulty in meeting the high changing and complex battlefield environment and we propose a novel architecture of DCOMP to build a scalable, extensible, and robust decision-making system, to realize powerful and secure communication, computing, storage, and information processing capabilities for the tactical edge. We illustrate the fundamental principles of building a network model, channel allocation, and forwarding control mechanism of the network architecture for DCOMP called DANET and then design a new architecture, programming model, task awareness, and computing scheduling for DCOMP. Finally, we discuss the main requirements and challenges of DCOMP in future wars.

A Case based Online Trajectory Planning Method of Autonomous Unmanned Combat Aerial Vehicles with Weapon Release Constraints

As a challenging and highly complex problem, the trajectory planning for unmanned combat aerial vehicle (UCAV) focuses on optimising flight trajectory under such constraints as kinematics and complicated battlefield environment. An online case-based trajectory planning strategy is proposed in this study to achieve rapid control variables solution of UCAV flight trajectory for the of delivery airborne guided bombs. Firstly, with an analysis of the ballistic model of airborne guided bombs, the trajectory planning model of UCAVs is established with launch acceptable region (LAR) as a terminal constraint. Secondly, a case-based planning strategy is presented, which involves four cases depending on the situation of UCAVs at the current moment. Finally, the feasibility and efficiency of the proposed planning strategy is validated by numerical simulations, and the results show that the presented strategy is suitable for UCAV performing airborne guided delivery missions in dynamic environments.

Strategic Defense Management: transforming the military environment in face of the new demands in security and defense

The dynamics of wars have demanded new challenges from the military. Acting on the whole spectrum of conflicts, in an environment that may not have winners, achieve goals with the lowest number of military and civilian casualties, with minimal material losses, and manage the chaos that comes after the conflicts, the major challenges for states and international organizations. Alongside these challenges, the military structure, in times of peace, needs to be adapted to its strategic environment, that is, to what is imposed on it by governments and the society it must protect. Flexible, specialized, and better equipped military structures have become, not only an operational requirement of the new asymmetric battlefield environment, but a requirement of society. It is understood that the main result of this work will be to present a proposal of how the Armed Forces and Brazilian society need to face these new challenges, ranging from aid to natural catastrophes, support for major events, acting in a police environment, and at the same time, be able to act in an external environment, markedly in UN missions or regional cooperation.