## 2 Related Work
### Hybrid PSOGWO Principle
#### 2.2.2 Gwo
** To obtain more reliable data, we use Gaussian filtering to filter the signal strength obtained in Step 1. * **Step 3: Fit Data. ** The obtained signal strength and distance are fitted, and the relationship model between signal strength and distance is constructed. * **Step 4: Evaluate model. ** Use the model evaluation criteria to evaluate the relationship model between signal strength and distance constructed in step 3, and select a model with the best fitting degree. * **Step 5: Determine and narrow the selected region of reference point. ** Use the dichotomy to divide the room to be located, and further narrow the region where the target node is located. * **Step 6: Deploy the location of reference points. ** Several possible situations of reference point deployments are given, and the location of reference point deployment is limited. * **Step 7: Adopt the weighted distance strategy to select the reference points. ** The selection of reference points will directly affect the localization precision of the target node. This paper proposes to use the weighted distance strategy to select reference points with strong and stable signal strength. * **Step 8: Use the PSOGWO algorithm to locate. ** According to the location information obtained above, the hybrid PSOGWO algorithm is used to locate and optimize the target node location. The following chapters elaborate the above steps in detail. ### Construction and Analysis of the Relationship Model between the RSS and Distance

This section is mainly divided into the following three stages: data acquisition and processing, RSS and distance relationship model construction and model evaluation. The following introduces the three stages, respectively. #### 3.1.1 Data Acquisition and Processing

The localization method based on RSS locates the target node by detecting the RSS of the target node. In this paper, the RSS is measured at different locations from the target node. As shown in Figure 2, the closer the distance to the target node, the stronger the RSS (i.e., the detection distance is inversely proportional to the RSS). Figure 1: The basic principle framework of the ILP-PSOGWO. Figure 2 also depicts that RSS is usually affected by reflection, refraction, noise, etc., in the transmission process, resulting in RSS fluctuating up and down. Therefore, before building the relationship model between RSS and distance, it is necessary to filter the obtained RSS. Common filtering methods include mean filtering, median filtering, Gaussian filtering, etc. Considering that RSS follows or approximately follows the normal distribution, Gaussian filtering is selected to filter the obtained RSS [40]. In this method, the RSS value of the high-probability occurrence region is selected as the effective value by Gaussian model, and the average value of effective value is obtained as the measurement value. Suppose \(n\) RSS values are collected from a reference point, which are \(S_{n}=\{s_{1},s_{2},\cdots,s_{n}\}\), where the corresponding probability \(P\) is \(P_{n}=\{p_{1},p_{2},\cdots,p_{n}\}\) and mean and variance are \(\mu\) and \(\delta^{2}\), then the Gaussian filter model is

\[P(s)=\frac{1}{\delta\sqrt{2\pi}}e^{(-(-s-\mu)^{2})/(2\delta^{2})}, \tag{10}\]

where

\[\mu=\frac{s_{1}+s_{2}+\cdots+s_{n-1}+s_{n}}{n}=\sum\
olimits_{i=1}^{n}s_{i}p _{i} \tag{11}\]

\[L(t+1)=L_{p}(t)-A\times D,A=2a\times r_{1} \tag{4}\]0

The minimum value of high probability is set to be greater than or equal to 0.6 to reduce the influence of small probability events on the collected RSS value. Therefore, when, by substituting the \(\mu\) and \(\delta\) obtained from Equations (11)-(12) into Equation (10), we can obtain the corresponding probability density of each RSS. After that, the filtered RSS can be obtained by sifting out the probability density less than 0.6, and we can use Equation (13) to obtain the optimized RSS. \[L(t+1)=L_{p}(t)-A\times D,A=2a\times r_{1} \tag{4}\]1

Figure 3 shows the processing results of the RSS value.