An Improved Centroid Localization Algorithm for Wireless Sensor Networks Based on RSSI Ranging

This article explores an improved centroid localization algorithm for wireless Sensor Networks (WSNs) based on RSSI ranging techniques. First, let's understand the fundamental concept of Wireless Sensor Networks. WSNs consist of numerous distributed sensor nodes capable of monitoring environmental parameters and transmitting collected data to central processing units or other connected devices. Within these networks, localization algorithms play a critical role in determining node positions, enabling effective environmental monitoring and control systems.

Among existing localization methods, the Centroid Localization Algorithm stands out for its simplicity and effectiveness. This algorithm estimates node positions by calculating distances and relative positions between nodes. However, practical implementations reveal limitations including sensitivity to signal attenuation and multipath effects, as well as reduced accuracy in complex environments. The basic centroid calculation can be implemented as: centroid_x = Σ(x_i)/n, centroid_y = Σ(y_i)/n where (x_i, y_i) are anchor node coordinates and n is the number of anchors.

To address these challenges, we propose an enhanced centroid localization algorithm incorporating RSSI-based distance measurement. This approach utilizes RSSI values to estimate inter-node distances more accurately, thereby improving positioning precision. Specifically, the algorithm implements distance calculation using the log-normal shadowing model: d = d_0 * 10^((P_0 - P_r)/(10 * n)) where P_r is received signal power, P_0 is reference power at distance d_0, and n is the path loss exponent. These calculated distances are then integrated into the centroid localization framework, effectively mitigating the impact of signal attenuation and multipath propagation while enhancing performance in complex environments.

In conclusion, the RSSI-based improved centroid localization algorithm represents a promising positioning methodology that delivers more accurate and reliable location estimates in wireless sensor networks. By combining RSSI ranging technology with the centroid algorithm, we overcome limitations of traditional approaches and achieve superior node localization across various operational environments. The complete implementation typically involves three main stages: RSSI measurement and filtering, distance estimation using path loss models, and weighted centroid calculation based on signal quality metrics.