# Cooperative Standoff Tracking of Moving Targets Using Modified Lyapunov Vector Field Guidance
## 5 Experiments and Results
### Hardware-in-the-Loop Simulation
#### 5.2.1 HIL Simulation Setup  
In this paper, we further use a HIL simulation platform to validate the proposed algorithm. The HIL simulation system consists of a X-Plane10 Flight Simulator, Pixhawk4 autopilots, and an onboard computer for each UAV, and a ground control station called Superstation. The simulation platform is shown in Figure 16. There are three simulation UAVs (UAV1, UAV2, UAV3) connected to the UAV (UAV3, UAV4) connected to the UAV (UAV4, UAV5) connected to the UAV (UAV6, UAV7) connected  
the ground control station via serial ports, and the detailed components of simulation for UAVs are placed on the right of Figure 16. The laptops and onboard computer used in the HIL simulation are shown in Figure 17.  
The high-fidelity aircraft simulation software X-plane 10 is a comprehensive and powerful flight simulator for the personal computer, which is often used in HIL simulation [23; 24]. We choose the HILStar 17F aircraft as the controlled object. Pixhawk 4 autopilot controls the UAV to fly along the commands. The onboard computer receives the states of the target and other UAVs and sends control policies generated by the proposed algorithm to Pixhawk 4. The ground control station monitors the states of the target and all UAVs, which are distributed to each UAV, and can control multiple UAVs by switch control modes. Figure 18 displays a snapshot of the target standoff tracking, and Figure 18a shows the controlled objective used in the HIL simulation, which is rolling right, indicating that the UAV is circling clockwise. Figure 18b displays the cooperative tracking of a moving target using three UAVs, all of which are circling clockwise. Figure 16: The architecture of the HIL simulation. The left part shows the Ground Control Station, and the right part places the detailed components (flight simulator, autopilot, and onboard computer) and the information flow among them. The modules are operated or connected in the robot operation system (ROS). Figure 17: The laptops and onboard computer used in the HIL simulation. The ground control station is in the upper right corner, and other laptops are simulations for UAVs. The detailed implementation process can be:  
1. The ground control station distributes three sets of pre-processed data obtained by onboard sensors to three UAVs;
2. The onboard computer estimates the state of the target using pre-process data received from the ground control station via the IMM-UKF and federated filter;
3. The onboard computer generates the desired course angle, modifies it with the predicted velocity vector, adjusts the desired speed if the phase difference needs to be adjusted, and sends the desired course and speed to the autopilot;
4. The autopilot sends control commands to the flight simulator, receives aircraft status, and forwards it to the onboard computer. As shown in Figure 19, the simulation environment is designed as follows: As soon as the fixed-wing UAVs takes off from the runway, they hover over the standby point until receiving the \"tracking\" command. Then, they track the ground moving target under the command generated by the tracking algorithm. The moving target moves from start point A, and finally stops at the end point D, passing the turning points B and C. The target moves at a relatively high speed \(v_{th}\) from A to B, and a relatively low speed \(v_{tl}\) from B to C. After a sharp turn on the right at C, the target moves at a constant acceleration at \(a_{t}\) and stops at D.  
Figure 18: The snapshots of the target standoff experiments in HIL simulation in different perspectives. (**a**) HILStar 17F used in the X-plane simulator, (**b**) The tracking trajectory of the UAV around the car. All key parameters in the HIL simulation are listed in Table 2.  
For simplicity, several stages are defined in this paper. When UAVs fly from the standby point to the start point, we call it the 'gathering' stage, and UAVs adjust the phase difference over the start point A during the 'adjusting' stage.