Research Of RSSI And APIT Based On Localization Algorithms Of Wireless Sensor Networks

Wireless Sensor Network is the wireless network which is combined by massivestationary or moving sensors self-organized style. Its aim is to help to sense, collect and solvethe monitor information inside the area covered by network. Then it can report to the user.WSN is combined by the single sensor nodes. How to locate the nodes inside the network is akey point in the WSN technology. Now the most widely used localization ways includelocating by distance and not by distance. This paper describes the development of wirelesssensor network positioning technology background, research status and development direction,and focuses on the RSSI-based location and improved positioning algorithm APIT positioningtechnology. Main tasks are summarized as follows:(1) In practical applications, due to factors related to the environment path loss, theWireless Sensor Networks will have a greater measurement error, to reduce the interference ofenvironmental factors, we propose a least square method to obtain environmental parametersand choose appropriate Gauss model for processing the measured RSSI data, then using theimproved trilateration localization algorithm to locate the target node, Experimental resultsshow that the algorithm reduces positioning influenced by environmental factors, while havehigher accuracy than traditional RSSI location algorithm, can be widely used WSNpositioning system.(2) In the node localization algorithm for wireless sensor networks, APIT is a range-freelocalization algorithm, which can achieve higher precision position estimation with smallcommunication cost in the intensive node density. However, the algorithm is prone to errors inrelative sparse node density environment. An improved APIT algorithm based on vector crossis proposed, using the vector cross to determine whether the unknown node inside the triangle,and reduce the typical errors effectively. The simulation show that this algorithm can reduceerrors effectively and improve the positioning precision compared with traditional algorithm.