## 2 Related Work
### Hybrid PSOGWO Principle
#### 2.2.2 Gwo
The experimental results are shown in Figure 16. In LOS, the standard deviation of PSO and GWO is below 0.7, and with the change in the number of experiments, the standard deviation also fluctuates greatly. EWCL and ILP-PSOGWO have good stability, and the standard deviation always stays below 0.4. In NLOS, the stability of the four methods is significantly decreased, but compared with EWCL and ILP-PSOGWO, PSO and GWO are less stable, and PSO even has the worst stability. Figure 15: Impact of iteration times on localization error. (**a**) LOS. (**b**) NLOS. Figure 17 depicts the cumulative frequency distribution and cumulative frequency distribution of 100 localization errors obtained by the four methods. The average localization errors obtained by PSO, GWO, EWCL and ILP-PSOGWO are 1.0848 m, 1.15672 m, 0.54455 m and 0.47539 m, respectively. Figure 17 also shows that the localization errors obtained by PSO and GWO are mostly distributed between 0.6m and 1.8 m, and the frequency of occurrence is fewer than 10 times, indicating that the stability of these two methods is poor. In contrast, the localization errors of EWCL and ILP-PSOGWO are mostly distributed between 0.3 m and 0.7 m, and the frequency of occurrence is as high as 20, indicating good stability. Figure 17d indicates that 90% of the localization errors of ILP-PSOGWO are less than 0.9012 m, and 50% are less than 0.4837 m, which is better than the other three methods. Figure 16: Standard deviation. (**a**) LOS. (**b**) NLOS. Figure 17: Cumulative probability distribution. (**a**) PSO. (**b**) GWO. (**c**) EWCL. (**d**) ILP-PSOGWO. ## 5 Conclusions

To obtain the indoor location of a wireless covert communication entity for post-steganalysis, this paper proposes a novel localization method based on hybrid particle swarm optimization and gray wolf optimization to improve the localization precision (ILP-PSOGWO). To verify the effectiveness and feasibility of ILP-PSOGWO, we carried out a series of comparative experiments. The experimental results indicate that ILP-PSOGWO can achieve higher localization precision and convergence speed. In addition, experimental results in the LOS and NLOS environments show that ILP-PSOGWO can maintain high stability in localization results. In future research, we will continue to focus and follow up on the indoor localization method of a wireless covert communication entity for post-steganalysis and further improve the localization precision of wireless covert communication entities. [PERSON] designed the study. [PERSON] and [PERSON] performed the experiments and analyzed the data. [PERSON] wrote the paper. [PERSON] and [PERSON] reviewed the manuscript. [PERSON] and [PERSON] guided the research. All authors have read and agreed to the published version of the manuscript. This work was supported by the National Nature Science Foundation of China (No. 62172435, No. U1804263 and No. 61872449), Zhongyuan Science and Technology Innovation Leading Talent Project of China (No. 214200510019). Not applicable. The data presented in this study are available on request from the corresponding author. The authors declare no conflict of interest. ## References

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