## 1 Introduction
Today, the Pixhawk controller is widely used for UAV applications due to its low cost and better performance [7; 8; 9] and it comes with autopilot open source software and firmware. The necessity for UAV simulations is increasing largely because there is a great deal of research taking place on UAV exploration [9; 10; 11]. A literature review revealed that many undesirable accidents have occurred during UAV operations due to the lack of professional pilot training [12; 13; 14]. Therefore, it is necessary, rather desirable, and perhaps inevitable, to develop a training device, such as the UAV simulator for new UAV users, and also for further research and development. UAV simulations have shown many benefits, including better understanding of a system and experimental flight tests before a real UAV fight. In the industry, a considerable number of flight simulation softwares are available, including X-Plane [15; 16; 17], FlightGear [18], Gazebo [9], and MAV3 DSim [19]. The three main types of existing simulations are virtual reality (VR) simulation [20], augmented reality (AR) simulation [21], and mixed reality (MR) simulation [22]. The virtual reality simulation is a fully immersive type of simulation; it is used in computer technology to create a simulated environment. The augmented reality simulation is overlaid digital information in the real world. The mixed reality simulation is a combination of the virtual part, together with the real part, and it interacts in real time. Various research methods have been conducted on these three simulations, including the UAV field. [PERSON] et al. (2016) [23] developed UAV-based virtual reality systems and [PERSON] et al. (2017) [24] constructed a virtual reality platform for UAV deep learning. [PERSON] et al. and [PERSON] et al. introduced UAV with augmented reality technologies [25; 26]. In MR simulation, [PERSON] et al. [27] proposed a design for a communication architecture in unmanned systems. [PERSON] et al. (2017) [28] discussed an initial phase of the MR simulator for autonomous UAVs. [PERSON] et al. (2019) [29] developed a stereoscopic MR for UAV search and rescue. Nowadays, UAVs are used for long-time missions for strategic defense, agricultural, surveillance, and rescue operations during a natural calamity. Additional surveillance applications include pipeline security, livestock monitoring, wildfire mapping, home security, road patrol, transportation, photography, and other entertainments. The main limitation of the long-time missions is the limited flight endurance due to the visibility problem of the UAV. It is well known that most UAVs have a live camera tracking system and global positioning system (GPS), but a user cannot see the overall view of an UAV during the use of these systems. Although a large volume of simulation studies on UAVs are available in the open literature, there are no studies that address the overall view and performance of MR simulation of UAVs [27; 28; 29], which we have addressed, herein, along with the preliminary design of a quadcopter UAV governed by dual-head EMP devices for high endurance planetary explorations. More specifically, in this paper, we introduce a new MR simulation based on a quadcopter UAV and an X-Plane flight simulator (version 10.51). Herein, we present an overall view of the real-time performance of an UAV, which enables us to see the live performance of a real UAV quadcopter on a simulation platform. Using this MR simulation technique, we can solve the problem of limited flight endurance due to visibility problems during a long-time mission of any quadcopter.