Rssi-based Wireless Sensor Network Indoor Positioning Research

Wireless sensor technology generates with the development oftechnology on sensor, wireless communication, microprocessors and theembedded. The wireless sensor network(WSN) consists of a lot of cheapmicro-sensor nodes in the monitoring region, and form a multi-hopself-organization network by wireless communication. Its purpose is tocooperatively sense, collect, process and transmit monitoring informationwithin the covered area, then reports to users. Because WSN is low-cost,low-power consumption, miniaturization and self-organization, it has broadapplication in areas such as industry, military,medical treatment and smarthome etc. However, many application of wireless sensor networks need toknow the location information of the sensor nodes. So, positioning is a keytechnology for wireless sensor networks. Positioning is not only related tothe applicated environment, but also impacted by the location algorithm. Inorder to improve the positioning accuracy, we should analyze theapplication environment and improve location algorithm according to theresult of analysis. Therefore, positioning algorithm can suitable for theapplication environment.This article describes several positioning algorithm and analyzes theirapplication environment. We use wireless sensor devices based on the ZigBee protocol to do experiment to obtain the relationship of RSSI anddistance in different environment. Then, we analyze how the complexindoor environment impact on the RSSI value by comparing the datemeasured in different environment, and propose an improved RSSIpositioning algorithm. The algorithm uses the RSSI average to eliminatethe serious distorted date and introduce the reference nodes in similarenvironment to the positioning algorithm. Thereby, we can reduce theestimated distance error.Finally, we established a simulation system based on the math toolsmatlab and do simulation experiment for positioning algorithm. The resultshow that the proposed algorithm significantly reduced the estimateddistance error and improved positioning accuracy, suitable for indoorpositioning environment.