# Emergent Search of UAV Swarm Guided by the Target Probability Map
## 4 The Steps of ESUSTPM
Within the 200 time cycle, only the proposed ESUSTPM algorithm can find all targets. The results verify that the efficiency of the proposed ESUSTPM is higher than the other searching algorithms. \[\stackrel{{\rightharpoonup}}{{P_{i}}}(t+1)=\stackrel{{ \rightharpoonup}}{{P_{i}}}(t)+\stackrel{{\rightharpoonup}}{{dir}} \cdot S\cdot\Delta t, \tag{13}\]1 Target search based on the Boids model with guidance. \[\stackrel{{\rightharpoonup}}{{P_{i}}}(t+1)=\stackrel{{ \rightharpoonup}}{{P_{i}}}(t)+\stackrel{{\rightharpoonup}}{{dir}} \cdot S\cdot\Delta t, \tag{13}\]2 Relationship between grid visited number and time cycles. ### Environment with Partial Prior Information of Static Targets

Three targets are assumed to exist at (400, 500), (400, 700) and (700, 500). Therefore, the initial distribution of the target existing probability density in the mission area is shown in Figure 23 according to Equation (2). \[\stackrel{{\rightharpoonup}}{{P_{i}}}(t+1)=\stackrel{{ \rightharpoonup}}{{P_{i}}}(t)+\stackrel{{\rightharpoonup}}{{dir}} \cdot S\cdot\Delta t, \tag{13}\]3 Relationship between the environment uncertainty and time cycles. \[\stackrel{{\rightharpoonup}}{{P_{i}}}(t+1)=\stackrel{{ \rightharpoonup}}{{P_{i}}}(t)+\stackrel{{\rightharpoonup}}{{dir}} \cdot S\cdot\Delta t, \tag{13}\]4 The results of target search in the five searching algorithms. \[\stackrel{{\rightharpoonup}}{{P_{i}}}(t+1)=\stackrel{{ \rightharpoonup}}{{P_{i}}}(t)+\stackrel{{\rightharpoonup}}{{dir}} \cdot S\cdot\Delta t, \tag{13}\]5 The distribution of the target existing probability density at the initial time. #### 5.3.1 The Mission Area with Accurate Prior Information

As the initial target existing probability map is known before executing the target search, UAV swarm based on the ESUSTPM algorithm tends to move to the area with the high probability information for detecting targets. Figure 24 shows that all targets are found, and the environmental uncertainty is also reduced after 200 time cycles. Figure 25 shows that the ESUSTPM algorithm without prior information takes more time to find three targets than ESUSTPM with prior information. The results prove that prior information is helpful to improve the searching efficiency. Figure 26 is the distribution of the statistical time cycles to find three targets. The yellow boxplots are the target searching cycle distribution of UAV swarm in the environment with prior information, and the green boxplots are the target searching cycle distribution of UAV swarm in the unknown environment without prior information. The results indicate that accurate prior information can improve the searching efficiency. \[\stackrel{{\rightharpoonup}}{{P_{i}}}(t+1)=\stackrel{{ \rightharpoonup}}{{P_{i}}}(t)+\stackrel{{\rightharpoonup}}{{dir}} \cdot S\cdot\Delta t, \tag{13}\]6 The results of the target search in the environment with accurate prior information. \[\stackrel{{\rightharpoonup}}{{P_{i}}}(t+1)=\stackrel{{ \rightharpoonup}}{{P_{i}}}(t)+\stackrel{{\rightharpoonup}}{{dir}} \cdot S\cdot\Delta t, \tag{13}\]7 The target searching results of ESUSTPM with and without prior information. #### 5.3.2 The Mission Area with Inaccurate Prior Information

According to prior information, three targets may be distributed in the area with high probability, as shown in \[\stackrel{{\rightharpoonup}}{{P_{i}}}(t+1)=\stackrel{{ \rightharpoonup}}{{P_{i}}}(t)+\stackrel{{\rightharpoonup}}{{dir}} \cdot S\cdot\Delta t, \tag{13}\]8 The target coordinates actually exist in (400, 500), (400, 700), but the target in (700, 500) is not true. Prior information is not accurate enough, but the UAV swarm cannot know this situation at the initial time. Figure 27a shows the corresponding results of the proposed ESUSTPM algorithm. The red grids indicate that the targets in (400, 500) and (400, 700) are found. Concurrently, the color of the grid in (700, 500) becomes white in the emergent searching process, and the algorithm identifies that the target does not exist in this grid.