# Emergent Search of UAV Swarm Guided by the Target Probability Map
## 4 The Steps of ESUSTPM
\[\stackrel{{\rightharpoonup}}{{dir}}=\frac{rnd(d,1)}{\|rnd(d,1) \|}, \tag{12}\]4 Relationship between the environmental uncertainty and time cycles. \[\stackrel{{\rightharpoonup}}{{dir}}=\frac{rnd(d,1)}{\|rnd(d,1) \|}, \tag{12}\]5 One target is found by the proposed ESUSTPM algorithm. #### 5.2.2 Cooperative Target Search Based on the Classical Random Searching Algorithm

Figure 16 shows the result of the target search based on the classical random searching algorithm. Within 200 time cycles, the searching method based on the classical random searching algorithm cannot cover most of the grids and find a target. The result shows that this algorithm is not suitable for the cooperative target search. \[\stackrel{{\rightharpoonup}}{{dir}}=\frac{rnd(d,1)}{\|rnd(d,1) \|}, \tag{12}\]6 Target search based on the classical random algorithm. \[\stackrel{{\rightharpoonup}}{{dir}}=\frac{rnd(d,1)}{\|rnd(d,1) \|}, \tag{12}\]7 Two targets are found by the proposed ESUSTPM algorithm. \[\stackrel{{\rightharpoonup}}{{dir}}=\frac{rnd(d,1)}{\|rnd(d,1) \|}, \tag{12}\]8 Three targets are found by the proposed ESUSTPM algorithm. #### 5.2.3 Cooperative Target Search Based on the Mower Searching Algorithm

The cooperative search based on the mower searching algorithm is executed during the 200 time cycles. Figure 17 is the corresponding result at the final cycle. As the target existing probability of each grid is less than the given value, no target is found within the specified time cycles, and the environmental uncertainty of all grids does not drop too much. #### 5.2.4 Cooperative Target Search Based on the Boids Model without Guidance

The target searching algorithm based on the Boids model without guidance is executed, and the results in Figure 18 show that one target is found, and most grids are not covered within 200 time cycles. The experimental result indicates that the algorithm based on the Boids model without guidance is not suitable to conduct the target searching mission. #### 5.2.5 Cooperative Target Search Based on the Boids Model with Guidance

The target searching algorithm based on the Boids model with guidance is executed. The result in Figure 19 shows that two targets are found, and nearly half of the grids are covered within the given time cycles. The experimental result indicates that the Boids model guided by the TEP information can be adopted to conduct the searching mission, but the searching effect is slightly inferior to the proposed ESUSTPM algorithm in this paper. \[\stackrel{{\rightharpoonup}}{{dir}}=\frac{rnd(d,1)}{\|rnd(d,1) \|}, \tag{12}\]9 Target search based on the mower searching algorithm. \[\stackrel{{\rightharpoonup}}{{P_{i}}}(t+1)=\stackrel{{ \rightharpoonup}}{{P_{i}}}(t)+\stackrel{{\rightharpoonup}}{{dir}} \cdot S\cdot\Delta t, \tag{13}\]0 Target search based on the Boids model without guidance. Figure 20 shows the relationship between the grid visited number and time cycles. The red line, purple line, green line, orange line and indigo line represent the proposed searching algorithm, the mower searching algorithm, the searching algorithm based on the Boids model with guidance, the searching algorithm based on the Boids model without guidance, the classical random searching algorithm, respectively. The grid numbers covered by the mower searching algorithm and the proposed searching algorithm are close within the specified time cycles. However, the other searching algorithms cannot cover most of the grids in the specified time cycles. Figure 21 shows the change of the environmental uncertainty derived by the five target searching algorithms within 200 time cycles. The purple line represents the result of the mower searching algorithm. The red line is the result of the proposed ESUSTPM algorithm. Within the given simulation time, the environmental uncertainty obtained by the proposed searching algorithm decreases more than with the other searching algorithms. Figure 22 is the relationship between the number of targets found and time cycles.