Journal: Design of an Unmanned Cluster System Simulation Platform (Top) Unmanned Cluster and Its Simulation Technology

(2) Communicate by stimulating the working mechanism;

(3) Simple rules of individual behavior;

(4) The system organization mechanism is self-organized.

Inspired by the above ideas, many intelligent emergent models have emerged in the control field [5], and new systems such as “bee colony” and “wolf group” have been spawned. The US Navy is a pioneer in the field of "bee colony" operations. Its subordinate graduate school of naval research conducted an in-depth analysis of the "bee colony" operations. Among them, LV Pham et al. published "UAV swarm attack: protection system" in December 2012. Alternatives for destroyers has aroused widespread concern in the scientific and military sciences. An unmanned cluster system represented by "bee colony" is usually a large-scale, complex application environment, and it is difficult to achieve central control. It is a typical distributed system. Cluster cooperative control problem is the key technical problem of this type of system [6].

Taking the UAV cluster as an example, this paper starts with the analysis of the composition and functional characteristics of the cluster system, and takes the task execution capability and the cluster control capability as the main verification objects, and carries out the design of the unmanned cluster system simulation platform. Its innovation includes the following two points:

First, the cluster control algorithm is used as the core verification object, and the simulation model design and evaluation model design are carried out around it.

Second, the platform messaging architecture uses DDS to achieve spatio-temporal uniformity and high-quality network transmission between objects.

1 Unmanned cluster and its simulation technology

1.1 Unmanned cluster

Since the concept of unmanned clusters has been proposed, domestic and foreign research institutions have carried out a lot of research work. The United States is in a leading position in this field, and has carried out all-round research work such as combat style, recycling, cluster networking, and system demonstration. China is closely following the United States in this field, and some of its technological achievements are in a leading position.

Under the unified leadership of the US Department of Defense, the Defense Advanced Research Projects Agency (DARPA), the Office of Strategic Capabilities (SCO), and the Navy have launched the "Gremlins" and "Perdix" respectively. Projects such as low-cost UAV cluster technology (LOCUST). These projects are functionally independent and each have their own emphasis, complementing and integrating development in the system. In addition, the United Kingdom, Singapore, Brazil and other countries have also carried out research on the field of cluster control.

China has accumulated a certain amount of research on unmanned cluster theory, which provides a good foundation for China to make breakthroughs in this field. In November 2016, Zhuhai Airshow announced the news that China Electronic Technology Group and Tsinghua University and Beijing Poisong Technology Co., Ltd. completed the "67 fixed-wing UAV cluster formation flight" to break the world record of fixed-wing UAV cluster flight. . In May 2017, the joint team successfully completed the flight test of 119 fixed-wing UAV clusters, demonstrating the cluster ground-based intensive ejection, air assembly, formation flight, multi-target grouping, formation and enclosing.

1.2 Cluster Simulation

Some of the above projects have carried out physical tests, which are an important part of unmanned cluster research. However, due to problems such as airspace and financial constraints, simulation methods are generally used to verify the functional performance of the cluster. By constructing the simulation platform, the closed-loop operation of the system is realized, combined with the randomized processing of the simulation process events, so that the system has the ability of rapid batch operation, and provides experimental data for analysis and evaluation [7].

With regard to simulation technology, the US National Defense Modeling and Simulation Office (DMSO) developed a master plan for modeling and simulation in October 1995, proposing a common technical framework for future modeling/simulation, including three aspects: high-level architecture (HLA) ), Task Space Conceptual Model (CMMS) and Data Standard (DS). HLA provides the design idea of ​​simulation platform architecture. The core idea is to use object-oriented method to design, develop and implement different levels and granular object models of the system to obtain high-level interoperability between simulation components and simulation platform. Reusability. CMMS and DS specify model specifications and data standards for the simulation platform.

At present, most simulation platforms use the Operation Support Environment (RTI) to implement the HLA interface specification, and RTI provides functions similar to the distributed network operating system to realize information interaction between simulation objects. Among them, the efficient release of simulation data is an important function of RTI, which is the key and difficult point of implementing RTI. In January 2007, the Object Management Organization (OMG) released a specification for distributed real-time system data distribution, Data Distribution Services (DDS) version 1.2, which uses a publish/subscribe architecture to build a publish/subscribe with data as the center. Communication model and provides real-time performance level control. Currently, DDS is widely used in mission systems with high real-time requirements. The use of DDS for the real-time release of simulation data can well solve the problem of efficient data distribution in the HLA architecture.

The model is the basic element of the simulation platform, a simplified description of the object of recognition, and a specific form of simulation of the prototype [8]. As a distributed network system composed of a large number of entities, the unmanned cluster system includes at least a motion model, a sensor model, a weapon model, etc., which describe the behavior of the unmanned platform, and a network model describing the behavior of the cluster group. Barrier rule model, etc. The group behavior model is the key and difficult point in cluster simulation and flight test.

In 1927, the biomathematician AE Parr first proposed the modeling idea of ​​the interaction between individuals in the group by gravitation and repulsive force when explaining the cohesive phenomenon of the fish population [9]. In 1991, K. Warburton and J. Lazarus constructed a series of population dynamics models to study the cohesion of the population. Since then, various bio-cluster cluster models have been produced. The motion state of smart cells in a cluster is determined by the internal environment (the attraction/repulsive force between individuals within the group) and the external environment (local perception environment) [10]. The cluster unit has certain autonomy, including autonomous motion control, local range information sensing, processing and communication [11]. Therefore, accurate modeling of cluster single sensor, weapon system and cluster operating environment is an important task in building a cluster simulation platform.

2 analysis of technical elements of unmanned clusters

2.1 Unmanned Platform System with Cluster Control as the Core

Unmanned cluster systems are distributed in various fields such as land, sea and air, including unmanned vehicle groups, unmanned ship groups, submersible groups, unmanned aerial vehicles, satellite groups, etc., or they can be inter-domain hybrid clusters, such as open space coordinated unmanned clusters. Air and sea coordination unmanned clusters, etc.

Generally, an unmanned cluster system consists of two parts: an unmanned platform system and a control station system. Among them, the control station system can be divided into ground station system, airborne station system, vehicle station system, ship station system and satellite station system. The following is an example of a cluster system consisting of a drone platform to describe the components of a typical unmanned cluster system.

A typical UAV cluster system consists of two main parts: the UAV system and the ground station system, as shown in Figure 1.

Figure 1 Schematic diagram of the elements of the UAV cluster system

The UAV system includes an onboard task subsystem, a cluster control subsystem, a communication subsystem, a navigation subsystem, a flight control subsystem, an electromechanical subsystem, and an energy subsystem, as shown in FIG. 2 .

Figure 2 UAV system composition diagram

The airborne task subsystem realizes the task assignment and task tracking of the platform based on the overall task objectives of the cluster, and the task coordination between the platform and the cluster friend and the task interaction between the platform and the ground station system. The subsystem implements cluster task decomposition, including tasks such as intelligence gathering and interference attack. Among them, intelligence gathering tasks include intelligence detection, target recognition, and information distribution. Interference attacks include electronic reconnaissance interference, communication reconnaissance interference, and fire attack.

The cluster control subsystem implements collision avoidance detection and path planning based on cluster local information. Among them, the collision avoidance detection includes collision avoidance detection for geographical environment information, collision avoidance detection for the cluster friend machine, and collision avoidance detection for the enemy defense facility. Path planning implements the path planning and path tracking of the platform based on the overall task of the cluster and the collision avoidance strategy. The cluster control subsystem is the basis and guarantee for the operation of the entire cluster, and plays a key role in the correct execution of cluster tasks.

The communication subsystem implements the remote communication functions required for intra-cluster networking and external information interaction. Among them, cluster self-organizing network communication technology and micro-miniature remote communication technology are the key technologies of the cluster system. The navigation subsystem implements functions such as geolocation, space-time reference, and posture acquisition of the platform. The flight control subsystem and the electromechanical subsystem respectively implement the flight control function and mechanical control function of the platform. The energy subsystem provides the power and power energy required for the flight and calculation of the platform.

2.2 Ground management system centered on management evaluation

The ground station system includes a ground task subsystem, a human-computer interaction subsystem, a communication subsystem, and an evaluation subsystem, as shown in FIG.

Figure 3 Control station system composition diagram

The ground task subsystem mainly implements task management and situation management of the entire cluster. Among them, task management includes cluster task planning and cluster grouping control. Situation management includes the management of the global situation of the cluster system and the monitoring and management of the cluster members.

The human-computer interaction subsystem implements functions such as command interaction and data display between the operator and the cluster system. The command interaction includes keyboard, mouse, touch, gesture, voice, and the like. The data display includes desktop workstation display, large screen display, handheld mobile terminal display, virtual reality display and the like.

The communication subsystem realizes the remote communication function of the ground station and the drone, or realizes the remote communication through the relay of the large space-based platform, the sea-based platform and the space-based platform. The evaluation subsystem implements an assessment of cluster capabilities such as task execution and cluster control.

(To be continued)

Disclaimer: Copyright belongs to the Journal of China Academy of Electronic Sciences.

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